should we have a fast-path planning for OLTP starjoins?

Started by Tomas Vondra11 months ago61 messages
#1Tomas Vondra
tomas@vondra.me
5 attachment(s)

Hi,

While running benchmarks for my "performance over 20 years" talk [1]https://www.postgresql.eu/events/pgconfeu2024/schedule/session/5585-performance-archaeology/,
I've been been also looking for common cases that don't perform well
(and thus might be a good topic for optimization, with significant
speedup helping a lot of deployments).

One such simple example that I ran into is "OLTP starjoin". You're
probably familiar with star schema in the DSS field [2]https://en.wikipedia.org/wiki/Star_schema, as a large fact
table with many small-ish dimensions. The OLTP variant is exactly the
same thing, but with selective WHERE conditions on the fact table.

So you can imagine it as a query of this shape:

SELECT * FROM fact_table f
JOIN dim1 ON (f.id1 = dim1.id)
JOIN dim2 ON (f.id2 = dim2.id)
JOIN dim3 ON (f.id3 = dim3.id)
...
WHERE f.id = 2398723;

This is a surprisingly common query pattern in OLTP applications, thanks
to normalization. For example the "fact" may be a table of transactions
with some basic common details, dimensions are additional "details" for
special types of transactions. When loading info about a transaction of
unknown type, this allows you to load everything at once.

Or maybe the fact table is "users" and the dimensions have all kinds of
info about the user (address, primary e-mail address, balance, ...).

Anyway, this pattern is quite common, yet it performs quite poorly.
Let's join a fact table with 10 dimensions - see the attached create
script to build such schema, and the test.sql script for pgbench.

On my new ryzen machine, this peaks at about ~16k tps with 16 clients.
The machine can easily do 1M tps in read-only pgbench, for example. And
if you increase the join_collapse_limit to 12 (because the default 8 is
not enough for the 10 dimensions), the throughput drops to ~2k tps.
That's not great.

AFAIK this is a consequence of the star joins allowing arbitrary join
order of the dimensions - those only have join conditions to the fact
relation, so it allows many join orders. So exploring them takes a lot
of time, of course.

But for starjoins, a lot of this is not really needed. In the simplest
case (no conditions on dimensions etc) it does not really matter in what
order we join those, and filters on dimensions make it only a little bit
more complicated (join the most selective first).

So I've been wondering how difficult would it be to have a special
fast-path mode for starjoins, completely skipping most of this. I
cobbled together a WIP/PoC patch (attached) on the way from FOSDEM, and
it seems to help quite a bit.

I definitely don't claim the patch is correct for all interesting cases,
just for the example query. And I'm sure there's plenty of things to fix
or improve (e.g. handling of outer joins, more complex joins, ...).

But these are the rough results for 1 and 16 clients:

build 1 16
--------------------------------------
master 1600 16000
patched 4400 46000

So that about triples the throughput. If you bump join_collapse_limit to
12, it gets even clearer

build 1 16
--------------------------------------
master 200 2000
patched 4500 48000

That's a 20x improvement - not bad. Sure, this is on a tiny dataset, and
with larger data sets it might need to do I/O, diminishing the benefits.
It's just an example to demonstrate the benefits.

If you want to try the patch, there's a new GUC enable_starjoin to
enable this optimization (off by default).

The patch does roughly this:

1) It tries to detect a "star join" before doing the full join order
search. It simply looks for the largest relation (not considering the
conditions), and assumes it's a fact. And then it searches for relations
that only join to the fact - those are the dimensions.

2) With the relations found in (1) it just builds the join relations
directly (one per level), without exploring all the possibilities. This
is where the speedup comes from.

3) If there are additional relations, those are then left to the regular
join order search algorithm.

There's a lot of stuff that could / should be improved on the current
patch. For (1) we might add support for more complex cases with
snowflake schemas [3]https://en.wikipedia.org/wiki/Snowflake_schema or with multiple fact tables. At the same time (1)
needs to be very cheap, so that it does not regress every non-starjoin
query.

For (2) it might pick a particular order we join the dimensions (by
size, selectivity, ...), and it might consider whether to join them
before/after the other relations.

FWIW I suspect there's a fair amount of research papers looking at
starjoins and what is the optimal plan for such queries, but I didn't
have time to look at that yet. Pointers welcome!

But the bigger question is whether it makes sense to have such fast-path
modes for certain query shapes. The patch "hard-codes" the planning for
starjoin queries, but we clearly can't do that for every possible join
shape (because then why have dynamic join search at all?).

I do think starjoins might be sufficiently unique / special to justify
this, but maybe it would be possible to instead improve the regular join
order search to handle this case better? I don't have a very clear idea
what would that look like, though :-(

I did check what do some other databases do, and they often have some
sort of "hint" to nudge the let the optimizer know this is a starjoin.

I also looked at what are the main bottlenecks with the simpler starjoin
planning enabled - see the attached flamegraphs. The optimizations seem
to break the stacktraces a bit, so there's a svg for "-O0 -ggdb3" too,
that doesn't have this issue (the shape is different, but the conclusion
are about the same).

In both cases about 40% of the time is spent in initial_cost_mergejoin,
which seems like a lot - and yes, disabling mergejoin doubles the
throughput. And most of the cost is in get_actual_variable_range,
looking up the range in the btrees. That seems like a lot, considering
the indexes are perfectly clean (we used to have problems with deleted
tuples, but this is not the case). I wonder if maybe we could start
caching this kind of info somewhere.

regards

[1]: https://www.postgresql.eu/events/pgconfeu2024/schedule/session/5585-performance-archaeology/
https://www.postgresql.eu/events/pgconfeu2024/schedule/session/5585-performance-archaeology/

[2]: https://en.wikipedia.org/wiki/Star_schema

[3]: https://en.wikipedia.org/wiki/Snowflake_schema

--
Tomas Vondra

Attachments:

starjoin.sqlapplication/sql; name=starjoin.sqlDownload
starjoin-create.sqlapplication/sql; name=starjoin-create.sqlDownload
0001-WIP-simplified-planning-of-starjoins.patchtext/x-patch; charset=UTF-8; name=0001-WIP-simplified-planning-of-starjoins.patchDownload
From f049875acde5d4959c2dfef65313ad2b3ab6a8d4 Mon Sep 17 00:00:00 2001
From: Tomas Vondra <tomas@vondra.me>
Date: Mon, 3 Feb 2025 16:45:24 +0100
Subject: [PATCH] WIP: simplified planning of starjoins

---
 src/backend/optimizer/path/allpaths.c | 118 ++++++++++++++++++-
 src/backend/optimizer/path/joinrels.c | 157 +++++++++++++++++++++++++-
 src/backend/utils/misc/guc_tables.c   |  10 ++
 src/include/optimizer/paths.h         |   5 +
 4 files changed, 288 insertions(+), 2 deletions(-)

diff --git a/src/backend/optimizer/path/allpaths.c b/src/backend/optimizer/path/allpaths.c
index 1115ebeee29..6848055dbcc 100644
--- a/src/backend/optimizer/path/allpaths.c
+++ b/src/backend/optimizer/path/allpaths.c
@@ -77,6 +77,7 @@ typedef enum pushdown_safe_type
 
 /* These parameters are set by GUC */
 bool		enable_geqo = false;	/* just in case GUC doesn't set it */
+bool		enable_starjoin = false;
 int			geqo_threshold;
 int			min_parallel_table_scan_size;
 int			min_parallel_index_scan_size;
@@ -3389,6 +3390,114 @@ make_rel_from_joinlist(PlannerInfo *root, List *joinlist)
 	}
 }
 
+static int
+starjoin_join_search(PlannerInfo *root, List *initial_rels, int level)
+{
+	if (!enable_starjoin)
+		return level;
+
+	{
+		ListCell   *lc;
+		List *rels = plan_star_join(root, initial_rels);
+		RelOptInfo *fact = NULL;
+		RelOptInfo *rel = NULL;
+
+		/*
+		 * add the dimensions one by one, and adjust the start level
+		 *
+		 * XXX The first element is the fact table.
+		 */
+		foreach(lc, rels)
+		{
+			ListCell   *lc2;
+			RelOptInfo *old_rel = NULL;
+
+			rel = lfirst(lc);
+
+			/* us the first element as fact table, jump to the next one,
+			 * which is the first dimension */
+			if (fact == NULL)
+			{
+				fact = rel;
+				continue;
+			}
+
+			/* we're adding join for the first dimension, so set the level */
+			root->join_cur_level = level;
+
+			/*
+			 * XXX Subset of join_search_one_level. The main difference is
+			 * we don't need to walk any of the lower levels, because for
+			 * level=2 we already have the fact table, and for higher
+			 * levels there should be only a single joinrel.
+			 */
+
+			if (level == 2)
+				old_rel = fact;
+			else
+				old_rel = (RelOptInfo *) linitial(root->join_rel_level[level - 1]);
+
+			/* there should be no join relation yet */
+			Assert(root->join_rel_level[level] == NIL);
+
+			make_rel_by_clause_joins(root, old_rel, rel);
+
+			/*
+			 * If everything went fine, we should have exactly one join relation
+			 * for the current level.
+			 *
+			 * XXX This could happen if the current starjoin logic fails to
+			 * consider something that prevents creating the join, e.g. some
+			 * sort of join restriction. Not sure if that should be treated
+			 * as a bug, or something expected (in which case we could just
+			 * fallback to the regular planning).
+			 */
+			Assert(root->join_rel_level[startlev] != NIL);
+			Assert(list_length(root->join_rel_level[startlev]) == 1);
+
+			/* generate/set paths for the join relation we just created */
+
+			/*
+			 * Run generate_partitionwise_join_paths() and
+			 * generate_useful_gather_paths() for each just-processed joinrel.  We
+			 * could not do this earlier because both regular and partial paths
+			 * can get added to a particular joinrel at multiple times within
+			 * join_search_one_level.
+			 *
+			 * After that, we're done creating paths for the joinrel, so run
+			 * set_cheapest().
+			 */
+			foreach(lc2, root->join_rel_level[level])
+			{
+				rel = (RelOptInfo *) lfirst(lc2);
+
+				/* Create paths for partitionwise joins. */
+				generate_partitionwise_join_paths(root, rel);
+
+				/*
+				 * Except for the topmost scan/join rel, consider gathering
+				 * partial paths.  We'll do the same for the topmost scan/join rel
+				 * once we know the final targetlist (see grouping_planner's and
+				 * its call to apply_scanjoin_target_to_paths).
+				 */
+				if (!bms_equal(rel->relids, root->all_query_rels))
+					generate_useful_gather_paths(root, rel, false);
+
+				/* Find and save the cheapest paths for this rel */
+				set_cheapest(rel);
+
+	#ifdef OPTIMIZER_DEBUG
+				pprint(rel);
+	#endif
+			}
+
+			level++;
+		}
+	}
+
+	return level;
+}
+
 /*
  * standard_join_search
  *	  Find possible joinpaths for a query by successively finding ways
@@ -3422,6 +3531,7 @@ RelOptInfo *
 standard_join_search(PlannerInfo *root, int levels_needed, List *initial_rels)
 {
 	int			lev;
+	int			startlev = 2;
 	RelOptInfo *rel;
 
 	/*
@@ -3445,7 +3555,13 @@ standard_join_search(PlannerInfo *root, int levels_needed, List *initial_rels)
 
 	root->join_rel_level[1] = initial_rels;
 
-	for (lev = 2; lev <= levels_needed; lev++)
+	/*
+	 * Try simplified planning for starjoin. If it succeeds, we should
+	 * continue at level startlev.
+	 */
+	startlev = starjoin_join_search(root, initial_rels, 2);
+
+	for (lev = startlev; lev <= levels_needed; lev++)
 	{
 		ListCell   *lc;
 
diff --git a/src/backend/optimizer/path/joinrels.c b/src/backend/optimizer/path/joinrels.c
index c2eb300ea9b..e604f863078 100644
--- a/src/backend/optimizer/path/joinrels.c
+++ b/src/backend/optimizer/path/joinrels.c
@@ -224,7 +224,6 @@ join_search_one_level(PlannerInfo *root, int level)
 		foreach(r, joinrels[level - 1])
 		{
 			RelOptInfo *old_rel = (RelOptInfo *) lfirst(r);
-
 			make_rels_by_clauseless_joins(root,
 										  old_rel,
 										  joinrels[1]);
@@ -255,6 +254,19 @@ join_search_one_level(PlannerInfo *root, int level)
 	}
 }
 
+void
+make_rel_by_clause_joins(PlannerInfo *root,
+						 RelOptInfo *old_rel,
+						 RelOptInfo *other_rel)
+{
+	if (!bms_overlap(old_rel->relids, other_rel->relids) &&
+		(have_relevant_joinclause(root, old_rel, other_rel) ||
+		 have_join_order_restriction(root, old_rel, other_rel)))
+	{
+		(void) make_join_rel(root, old_rel, other_rel);
+	}
+}
+
 /*
  * make_rels_by_clause_joins
  *	  Build joins between the given relation 'old_rel' and other relations
@@ -1963,3 +1975,146 @@ get_matching_part_pairs(PlannerInfo *root, RelOptInfo *joinrel,
 		*parts2 = lappend(*parts2, child_rel2);
 	}
 }
+
+/*
+ * Try to identify a starjoin in the list of relations. Pick the largest
+ * relation, and the smaller dimensions.
+ *
+ * Happens in two steps. First, we find the largest relation and consider
+ * it to be the "fact" of the star schema. Then we walk the rest of the
+ * relations and check which can be treated as dimensions for the fact.
+ * This is possible only if the relation has join clause only to the fact
+ * and no other relations.
+ *
+ * XXX It can happen the largest table is not the fact, in which case we
+ * should just try the second largest one, etc. Or maybe there are multiple
+ * facts, in which case we detect the should try to build a group for each
+ * fact (fact + dimensions).
+ *
+ * Returns the list of relations to join, in the join order, with the fact
+ * table as the first element, followed by the dimensions.
+ */
+List *
+plan_star_join(PlannerInfo *root, List *rels)
+{
+	ListCell   *lc;
+	RelOptInfo *fact = NULL;
+	List	   *dimensions = NIL;
+
+	/*
+	 * We need at least 3 relations for a star join, to have a chance to
+	 * gain anything by simpler join order planning.
+	 */
+	if (list_length(rels) < 3)
+		return NIL;
+
+	/*
+	 * Find the largest relation, we'll try to use it as "fact" table.
+	 */
+	foreach(lc, rels)
+	{
+		RelOptInfo *rel = (RelOptInfo *) lfirst(lc);
+
+		/* first relation */
+		if (fact == NULL)
+		{
+			fact = rel;
+			continue;
+		}
+
+		/*
+		 * We look at total relation sizes, not the estimated cardinality
+		 * with conditions applied.
+		 */
+		if (fact->tuples < rel->tuples)
+		{
+			fact = rel;
+			continue;
+		}
+	}
+
+	/*
+	 * If the "fact" does not have any join clauses, we're done.
+	 *
+	 * XXX Seems has_join_restriction is not what we want to require for the
+	 * fact table - it checks for restrictions on join order, but that's not
+	 * what we want for the fact. Maybe we should do the exact opposite, i.e.
+	 * require that a fact table does not have that? Although, if we want to
+	 * support multiple "partial star joins" (query on multiple fact tables,
+	 * each with it's own dimensions).
+	 */
+	//if (!has_join_restriction(root, fact))
+	//	return NIL;
+
+	/* the fact must have no restrictions */
+	if (has_join_restriction(root, fact))
+		return NIL;
+
+	/*
+	 * Now go and try to detect dimensions, i.e. relations that have a join
+	 * with the fact table, and no other relations. We will order them by
+	 * selectivity (rows / tuples), because we prefer to reduce the join
+	 * size early.
+	 */
+	foreach(lc, rels)
+	{
+		RelOptInfo *rel = (RelOptInfo *) lfirst(lc);
+
+		/* ignore the fact table */
+		if (rel == fact)
+			continue;
+
+		// elog(WARNING, "> has_join_restriction %d", has_join_restriction(root, rel));
+		// elog(WARNING, "> has_legal_joinclause %d", has_legal_joinclause(root, rel));
+
+		/* ignore rels without any join clause */
+		// if (!has_join_restriction(root, rel))
+		//	continue;
+
+		/*
+		 * XXX Do not allow join restrictions for dimensions either, just like
+		 * for fact, although for dims we should be able to allow this ...
+		 */
+		if (has_join_restriction(root, rel))
+			continue;
+
+		/*
+		 * Must have join clause with the fact table. This is a subset of
+		 * has_legal_joinclause for a single (fact) table. We always look
+		 * at initial rels, so the relids overlap checks are not needed.
+		 */
+		if (have_relevant_joinclause(root, fact, rel))
+		{
+			Relids		joinrelids;
+			SpecialJoinInfo *sjinfo;
+			bool		reversed;
+
+			/* join_is_legal needs relids of the union */
+			joinrelids = bms_union(fact->relids, rel->relids);
+
+			if (join_is_legal(root, fact, rel, joinrelids,
+							  &sjinfo, &reversed))
+			{
+				/* Yes, this will work */
+				// bms_free(joinrelids);
+
+				// FIXME this should also check the rel does not have join
+				// clauses to any other relation;
+				dimensions = lappend(dimensions, rel);
+			}
+
+			bms_free(joinrelids);
+		}
+	}
+
+	/*
+	 * repeat the check we actually found a star join with at least 3 rels
+	 * (so two dimensions)
+	 */
+	if (list_length(dimensions) < 2)
+		return NIL;
+
+	/* FIXME sort the dimensions by selectivity */
+
+	return list_concat(list_make1(fact), dimensions);
+}
diff --git a/src/backend/utils/misc/guc_tables.c b/src/backend/utils/misc/guc_tables.c
index 71448bb4fdd..941545d9125 100644
--- a/src/backend/utils/misc/guc_tables.c
+++ b/src/backend/utils/misc/guc_tables.c
@@ -1018,6 +1018,16 @@ struct config_bool ConfigureNamesBool[] =
 		true,
 		NULL, NULL, NULL
 	},
+	{
+		{"enable_starjoin", PGC_USERSET, QUERY_TUNING_GEQO,
+			gettext_noop("Enables starjoin optimization."),
+			gettext_noop("This algorithm attempts to do faster planning for star joins."),
+			GUC_EXPLAIN
+		},
+		&enable_starjoin,
+		false,
+		NULL, NULL, NULL
+	},
 	{
 		/*
 		 * Not for general use --- used by SET SESSION AUTHORIZATION and SET
diff --git a/src/include/optimizer/paths.h b/src/include/optimizer/paths.h
index 46955d128f0..2eed48b560e 100644
--- a/src/include/optimizer/paths.h
+++ b/src/include/optimizer/paths.h
@@ -21,6 +21,7 @@
  * allpaths.c
  */
 extern PGDLLIMPORT bool enable_geqo;
+extern PGDLLIMPORT bool enable_starjoin;
 extern PGDLLIMPORT int geqo_threshold;
 extern PGDLLIMPORT int min_parallel_table_scan_size;
 extern PGDLLIMPORT int min_parallel_index_scan_size;
@@ -111,6 +112,10 @@ extern bool have_dangerous_phv(PlannerInfo *root,
 extern void mark_dummy_rel(RelOptInfo *rel);
 extern void init_dummy_sjinfo(SpecialJoinInfo *sjinfo, Relids left_relids,
 							  Relids right_relids);
+extern List *plan_star_join(PlannerInfo *root, List *rels);
+extern void make_rel_by_clause_joins(PlannerInfo *root,
+									 RelOptInfo *old_rel,
+									 RelOptInfo *other_rel);
 
 /*
  * equivclass.c
-- 
2.47.1

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#2Jeff Davis
pgsql@j-davis.com
In reply to: Tomas Vondra (#1)
Re: should we have a fast-path planning for OLTP starjoins?

On Tue, 2025-02-04 at 15:00 +0100, Tomas Vondra wrote:

This is a surprisingly common query pattern in OLTP applications,
thanks
to normalization.

+1. Creating a small lookup table should be encouraged rather than
penalized.

Your test data includes a fact table with 10k rows and no index on the
filter condition. In OLTP applications the fact table might often fit
in memory, but I'd still expect it to have an index on the filter
condition. That might not change your overall point, but I'm curious
why you constructed the test that way?

There's a lot of stuff that could / should be improved on the current
patch. For (1) we might add support for more complex cases with
snowflake schemas [3] or with multiple fact tables. At the same time
(1)
needs to be very cheap, so that it does not regress every non-
starjoin
query.

The patch only considers the largest table as the fact table, which is
a good heuristic of course. However, I'm curious if other approaches
might work. For instance, could we consider the table involved in the
most join conditions to be the fact table?

If you base it on the join conditions rather than the size of the
table, then detection of the star join would be based purely on the
query structure (not stats), which would be nice for predictability.

But the bigger question is whether it makes sense to have such fast-
path
modes for certain query shapes.

We should explore what kinds of surprising cases it might create, or
what maintenance headaches might come up with future planner changes.
But the performance numbers you posted suggest that we should do
something here.

Regards,
Jeff Davis

#3Tomas Vondra
tomas@vondra.me
In reply to: Jeff Davis (#2)
Re: should we have a fast-path planning for OLTP starjoins?

On 2/4/25 20:43, Jeff Davis wrote:

On Tue, 2025-02-04 at 15:00 +0100, Tomas Vondra wrote:

This is a surprisingly common query pattern in OLTP applications,
thanks
to normalization.

+1. Creating a small lookup table should be encouraged rather than
penalized.

Your test data includes a fact table with 10k rows and no index on the
filter condition. In OLTP applications the fact table might often fit
in memory, but I'd still expect it to have an index on the filter
condition. That might not change your overall point, but I'm curious
why you constructed the test that way?

No particular reason. I think I intended to make it a lookup by PK
(which would match the use case examples), and I forgot about that. But
yeah, I would expect an index too.

There's a lot of stuff that could / should be improved on the current
patch. For (1) we might add support for more complex cases with
snowflake schemas [3] or with multiple fact tables. At the same time
(1)
needs to be very cheap, so that it does not regress every non-
starjoin
query.

The patch only considers the largest table as the fact table, which is
a good heuristic of course. However, I'm curious if other approaches
might work. For instance, could we consider the table involved in the
most join conditions to be the fact table?

If you base it on the join conditions rather than the size of the
table, then detection of the star join would be based purely on the
query structure (not stats), which would be nice for predictability.

Right, there may be other (possibly better) ways to detect the star join
shape. I was thinking about also requiring for foreign keys on the join
clauses - in DWH systems FKeys are sometimes omitted, which would break
the heuristics, but in OLTP it's common to still have them.

I think the cost of the heuristic will be an important metric - I don't
know if the number of join conditions is more expensive to determine
than what the patch does now, though.

But the bigger question is whether it makes sense to have such fast-
path
modes for certain query shapes.

We should explore what kinds of surprising cases it might create, or
what maintenance headaches might come up with future planner changes.
But the performance numbers you posted suggest that we should do
something here.

Yes, it seems like an interesting opportunity for starjoin queries. It's
a pretty common query pattern, but it also happens to be very expensive
to plan because the dimensions can be reordered almost arbitrarily.

regards

--
Tomas Vondra

#4Tom Lane
tgl@sss.pgh.pa.us
In reply to: Tomas Vondra (#3)
Re: should we have a fast-path planning for OLTP starjoins?

Tomas Vondra <tomas@vondra.me> writes:

On 2/4/25 20:43, Jeff Davis wrote:

If you base it on the join conditions rather than the size of the
table, then detection of the star join would be based purely on the
query structure (not stats), which would be nice for predictability.

Right, there may be other (possibly better) ways to detect the star join
shape. I was thinking about also requiring for foreign keys on the join
clauses - in DWH systems FKeys are sometimes omitted, which would break
the heuristics, but in OLTP it's common to still have them.

I think you need to insist on foreign keys. Otherwise you don't know
whether the joins will eliminate fact-table rows. If that's a
possibility then it's no longer sensible to ignore different join
orders.

I'm kind of imagining a planner rule like "if table X is joined to
using a match of a foreign-key column to its PK (so that the join
removes no rows from the other table) and there are not other
restriction conditions on table X, then force X to be joined last.
And if there are multiple such tables X, it doesn't matter what
order they are joined in as long as they're last."

The interesting thing about this is we pretty much have all the
infrastructure for detecting such FK-related join conditions
already. Possibly the join order forcing could be done with
existing infrastructure too (by manipulating the joinlist).

regards, tom lane

#5Joe Conway
mail@joeconway.com
In reply to: Tomas Vondra (#1)
Re: should we have a fast-path planning for OLTP starjoins?

On 2/4/25 09:00, Tomas Vondra wrote:

There's a lot of stuff that could / should be improved on the current
patch. For (1) we might add support for more complex cases with
snowflake schemas [3] or with multiple fact tables. At the same time (1)
needs to be very cheap, so that it does not regress every non-starjoin
query.

For (2) it might pick a particular order we join the dimensions (by
size, selectivity, ...), and it might consider whether to join them
before/after the other relations.

FWIW I suspect there's a fair amount of research papers looking at
starjoins and what is the optimal plan for such queries, but I didn't
have time to look at that yet. Pointers welcome!

But the bigger question is whether it makes sense to have such fast-path
modes for certain query shapes. The patch "hard-codes" the planning for
starjoin queries, but we clearly can't do that for every possible join
shape (because then why have dynamic join search at all?).

+    /*
+     * Try simplified planning for starjoin. If it succeeds, we should
+     * continue at level startlev.
+     */
+    startlev = starjoin_join_search(root, initial_rels, 2);

(I should probably don a flame retardant suit, but...)

This sounds like an interesting idea, but it makes me wonder if we
should have a more generic mechanism here so that if "some pattern is
matched" then "use some simplified planning method" -- of which the
starjoin is the first and builtin example, but allowing for others to be
plugged in via extensions.

--
Joe Conway
PostgreSQL Contributors Team
RDS Open Source Databases
Amazon Web Services: https://aws.amazon.com

#6Tomas Vondra
tomas@vondra.me
In reply to: Joe Conway (#5)
Re: should we have a fast-path planning for OLTP starjoins?

On 2/4/25 21:34, Joe Conway wrote:

On 2/4/25 09:00, Tomas Vondra wrote:

There's a lot of stuff that could / should be improved on the current
patch. For (1) we might add support for more complex cases with
snowflake schemas [3] or with multiple fact tables. At the same time (1)
needs to be very cheap, so that it does not regress every non-starjoin
query.

For (2) it might pick a particular order we join the dimensions (by
size, selectivity, ...), and it might consider whether to join them
before/after the other relations.

FWIW I suspect there's a fair amount of research papers looking at
starjoins and what is the optimal plan for such queries, but I didn't
have time to look at that yet. Pointers welcome!

But the bigger question is whether it makes sense to have such fast-path
modes for certain query shapes. The patch "hard-codes" the planning for
starjoin queries, but we clearly can't do that for every possible join
shape (because then why have dynamic join search at all?).

+    /*
+     * Try simplified planning for starjoin. If it succeeds, we should
+     * continue at level startlev.
+     */
+    startlev = starjoin_join_search(root, initial_rels, 2);

(I should probably don a flame retardant suit, but...)

This sounds like an interesting idea, but it makes me wonder if we
should have a more generic mechanism here so that if "some pattern is
matched" then "use some simplified planning method" -- of which the
starjoin is the first and builtin example, but allowing for others to be
plugged in via extensions.

We already have join_search_hook_type. I haven't used that in the PoC,
because I wanted to use joinrels.c functions defined as static, etc.

The main challenge would be handling queries that have multiple of such
patterns. The current hook is expected to process the whole list, while
what we'd need is more like splitting the list into chunks (one chunk
per query pattern), and then calling the hooks to handle the chunks in
some order.

But I don't think the patch should be required to invent this. We don't
even have an example of a second pattern.

regards

--
Tomas Vondra

#7Tomas Vondra
tomas@vondra.me
In reply to: Tom Lane (#4)
Re: should we have a fast-path planning for OLTP starjoins?

On 2/4/25 21:23, Tom Lane wrote:

Tomas Vondra <tomas@vondra.me> writes:

On 2/4/25 20:43, Jeff Davis wrote:

If you base it on the join conditions rather than the size of the
table, then detection of the star join would be based purely on the
query structure (not stats), which would be nice for predictability.

Right, there may be other (possibly better) ways to detect the star join
shape. I was thinking about also requiring for foreign keys on the join
clauses - in DWH systems FKeys are sometimes omitted, which would break
the heuristics, but in OLTP it's common to still have them.

I think you need to insist on foreign keys. Otherwise you don't know
whether the joins will eliminate fact-table rows. If that's a
possibility then it's no longer sensible to ignore different join
orders.

Hmmm, yeah. But that's only for the INNER JOIN case. But I've seen many
of these star join queries with LEFT JOIN too, and then the FKs are not
needed. All you need is a PK / unique index on the other side.

Perhaps requiring (INNER JOIN + FK) or (LEFT JOIN + PK) would be enough
to make this work for most cases, and then the rest would simply use the
regular join order algorithm.

I was thinking that if we allow the dimensions to eliminate rows in the
fact table, we'd simply join them starting from the most selective ones.
But that doesn't work if the joins might have different per-row costs
(e.g. because some dimensions are much larger etc). Doing something
smarter would likely end up fairly close to the regular join order
algorithm ...

I'm kind of imagining a planner rule like "if table X is joined to
using a match of a foreign-key column to its PK (so that the join
removes no rows from the other table) and there are not other
restriction conditions on table X, then force X to be joined last.
And if there are multiple such tables X, it doesn't matter what
order they are joined in as long as they're last."

I think it'd need to be a bit smarter, to handle (a) snowflake schemas
and (b) additional joins referencing the starjoin result.

The (a) shouldn't be too hard, except that it needs to check the
'secondary dimension' is also joined by FK and has no restrictions, and
then do that join later.

For (b), I don't have numbers but I've seen queries that first do a
starjoin and then add more data to that, e.g. by joining to a
combination of attributes from multiple dimensions (think region +
payment type). Or by joining to some "summary" table that does not have
an explicit FK. Still, we could leave at least some of the joins until
the very end, I guess. But even for the dimensions joined earlier the
order does not really matter.

I think (a) is something we should definitely handle. (b) is more a
DWH/BI thing, not really an OLTP query (which is what this thread is about).

The interesting thing about this is we pretty much have all the
infrastructure for detecting such FK-related join conditions
already. Possibly the join order forcing could be done with
existing infrastructure too (by manipulating the joinlist).

Maybe, interesting. I've ruled out relying on the FKeys early in the
coding, but I'm sure there's infrastructure the patch could use. It'd
still need to check the transitive FK relationships for snowflake joins
to work, ofc. Which is not something we need to consider right now.

What kind of "manipulation" of the joinlist you have in mind?

regards

--
Tomas Vondra

#8Tom Lane
tgl@sss.pgh.pa.us
In reply to: Tomas Vondra (#7)
Re: should we have a fast-path planning for OLTP starjoins?

Tomas Vondra <tomas@vondra.me> writes:

The interesting thing about this is we pretty much have all the
infrastructure for detecting such FK-related join conditions
already. Possibly the join order forcing could be done with
existing infrastructure too (by manipulating the joinlist).

Maybe, interesting. I've ruled out relying on the FKeys early in the
coding, but I'm sure there's infrastructure the patch could use.

It would be very sad to do that work twice in a patch that purports
to reduce planning time. If it's done too late to suit you now,
could we move it to happen earlier?

What kind of "manipulation" of the joinlist you have in mind?

Right now, if we have four tables to join, we have a joinlist
(A B C D). (Really they're integer relids, but let's use names here.)
If we decide to force C to be joined last, it should be sufficient to
convert this to ((A B D) C). If C and D both look like candidates for
this treatment, we can make it be (((A B) C) D) or (((A B) D) C).
This is pretty much the same thing that happens if you set
join_collapse_limit to 1 and use JOIN syntax to force a join order.
In fact, IIRC we start out with nested joinlists and there is some
code that normally flattens them until it decides it'd be creating
too large a sub-problem. I'm suggesting selectively reversing the
flattening.

regards, tom lane

#9Jim Nasby
jnasby@upgrade.com
In reply to: Tomas Vondra (#7)
Re: should we have a fast-path planning for OLTP starjoins?

On Tue, Feb 4, 2025 at 3:42 PM Tomas Vondra <tomas@vondra.me> wrote:

On 2/4/25 21:23, Tom Lane wrote:

Tomas Vondra <tomas@vondra.me> writes:

On 2/4/25 20:43, Jeff Davis wrote:

If you base it on the join conditions rather than the size of the
table, then detection of the star join would be based purely on the
query structure (not stats), which would be nice for predictability.

Right, there may be other (possibly better) ways to detect the star join
shape. I was thinking about also requiring for foreign keys on the join
clauses - in DWH systems FKeys are sometimes omitted, which would break
the heuristics, but in OLTP it's common to still have them.

I think you need to insist on foreign keys. Otherwise you don't know
whether the joins will eliminate fact-table rows. If that's a
possibility then it's no longer sensible to ignore different join
orders.

Hmmm, yeah. But that's only for the INNER JOIN case. But I've seen many
of these star join queries with LEFT JOIN too, and then the FKs are not
needed. All you need is a PK / unique index on the other side.

Perhaps requiring (INNER JOIN + FK) or (LEFT JOIN + PK) would be enough
to make this work for most cases, and then the rest would simply use the
regular join order algorithm.

I was thinking that if we allow the dimensions to eliminate rows in the
fact table, we'd simply join them starting from the most selective ones.
But that doesn't work if the joins might have different per-row costs
(e.g. because some dimensions are much larger etc). Doing something
smarter would likely end up fairly close to the regular join order
algorithm ...

As long as the join is still happening there doesn't appear to be a
correctness issue here, so I'm not sure mandating FKs makes sense.

The reason this matters is that highly concurrent FK checks can get VERY
expensive (due to the cost of creating multiXacts). While it'd be great to
fix that issue the reality today is it's not uncommon for people to remove
FKs because of the high performance penalty.

#10Tom Lane
tgl@sss.pgh.pa.us
In reply to: Jim Nasby (#9)
Re: should we have a fast-path planning for OLTP starjoins?

Jim Nasby <jnasby@upgrade.com> writes:

On Tue, Feb 4, 2025 at 3:42 PM Tomas Vondra <tomas@vondra.me> wrote:

Perhaps requiring (INNER JOIN + FK) or (LEFT JOIN + PK) would be enough
to make this work for most cases, and then the rest would simply use the
regular join order algorithm.

As long as the join is still happening there doesn't appear to be a
correctness issue here, so I'm not sure mandating FKs makes sense.
The reason this matters is that highly concurrent FK checks can get VERY
expensive (due to the cost of creating multiXacts). While it'd be great to
fix that issue the reality today is it's not uncommon for people to remove
FKs because of the high performance penalty.

Meh. If we don't apply this optimization when there's no FK, we have
not made those folks' life any worse. If we apply it despite there
being no FK, we might choose a materially worse plan than before, and
that *will* make their lives worse.

regards, tom lane

#11Richard Guo
guofenglinux@gmail.com
In reply to: Tomas Vondra (#7)
Re: should we have a fast-path planning for OLTP starjoins?

On Wed, Feb 5, 2025 at 5:42 AM Tomas Vondra <tomas@vondra.me> wrote:

Hmmm, yeah. But that's only for the INNER JOIN case. But I've seen many
of these star join queries with LEFT JOIN too, and then the FKs are not
needed. All you need is a PK / unique index on the other side.

Perhaps requiring (INNER JOIN + FK) or (LEFT JOIN + PK) would be enough
to make this work for most cases, and then the rest would simply use the
regular join order algorithm.

I was thinking that if we allow the dimensions to eliminate rows in the
fact table, we'd simply join them starting from the most selective ones.
But that doesn't work if the joins might have different per-row costs
(e.g. because some dimensions are much larger etc). Doing something
smarter would likely end up fairly close to the regular join order
algorithm ...

Yeah, we need to ensure that the joins to the fact table don't affect
its rows; otherwise, the join order matters for the final query plan,
and we'd better run the regular join search algorithm in this case.

For inner joins, using the foreign key seems ideal for this. For left
joins, we might be able to leverage rel_is_distinct_for() to handle
that.

Thanks
Richard

#12Richard Guo
guofenglinux@gmail.com
In reply to: Tom Lane (#8)
Re: should we have a fast-path planning for OLTP starjoins?

On Wed, Feb 5, 2025 at 5:55 AM Tom Lane <tgl@sss.pgh.pa.us> wrote:

Right now, if we have four tables to join, we have a joinlist
(A B C D). (Really they're integer relids, but let's use names here.)
If we decide to force C to be joined last, it should be sufficient to
convert this to ((A B D) C). If C and D both look like candidates for
this treatment, we can make it be (((A B) C) D) or (((A B) D) C).
This is pretty much the same thing that happens if you set
join_collapse_limit to 1 and use JOIN syntax to force a join order.
In fact, IIRC we start out with nested joinlists and there is some
code that normally flattens them until it decides it'd be creating
too large a sub-problem. I'm suggesting selectively reversing the
flattening.

This should not be too difficult to implement. Outer joins seem to
add some complexity, though. We need to ensure that the resulting
joins in each sub-list are legal given the query's join order
constraints. For example, if we make the joinlist be (((A B) C) D),
we need to ensure that the A/B join and the (A/B)/C join are legal.

Thanks
Richard

#13Tomas Vondra
tomas@vondra.me
In reply to: Richard Guo (#12)
Re: should we have a fast-path planning for OLTP starjoins?

On 2/5/25 09:27, Richard Guo wrote:

On Wed, Feb 5, 2025 at 5:55 AM Tom Lane <tgl@sss.pgh.pa.us> wrote:

Right now, if we have four tables to join, we have a joinlist
(A B C D). (Really they're integer relids, but let's use names here.)
If we decide to force C to be joined last, it should be sufficient to
convert this to ((A B D) C). If C and D both look like candidates for
this treatment, we can make it be (((A B) C) D) or (((A B) D) C).
This is pretty much the same thing that happens if you set
join_collapse_limit to 1 and use JOIN syntax to force a join order.
In fact, IIRC we start out with nested joinlists and there is some
code that normally flattens them until it decides it'd be creating
too large a sub-problem. I'm suggesting selectively reversing the
flattening.

This should not be too difficult to implement. Outer joins seem to
add some complexity, though. We need to ensure that the resulting
joins in each sub-list are legal given the query's join order
constraints. For example, if we make the joinlist be (((A B) C) D),
we need to ensure that the A/B join and the (A/B)/C join are legal.

If the requirement is that all "dimensions" only join to the fact table
(which in this example would be "A" I think) through a FK, then why
would these joins be illegal?

We'd also need to require either an outer (left) join, or "NOT NULL" on
the fact table side, right? IIRC we already do that when using the FKeys
for join estimates.

Essentially, this defines a "dimension" as a relation that is joined
through a PK, without any other restrictions, both of which seems fairly
simple to check, and it's a "local" feature. And we'd simply mark those
as "join at the very end, in arbitrary order". Easy enough, I guess.

I'm thinking about some more complex cases:

(a) Query with multiple starjoins (a special case of that is snowflake
schema) - but I guess this is not too difficult, it just needs to
consider the FKs as "transitive" (a bit like Dijkstra's algorithm). In
the worst case we might need to "split" the whole query into multiple
smaller subproblems.

(b) Joining additional stuff to the dimensions (not through a FK,
possibly to multiple dimensions, ...). Imagine a "diamond join" with
some summary table, etc. IMHO this is a fairly rare case / expensive
enough to make the planning part less important.

I'm also wondering how this should interact with join_collapse_limit. It
would seems ideal to do this optimization before splitting the join list
into subproblems (so that the "dimensions" are do not even count against
the limit, pretty much). But that would mean join_collapse_limit can no
longer be used to enforce a join order like today ...

regards

--
Tomas Vondra

#14Corey Huinker
corey.huinker@gmail.com
In reply to: Tomas Vondra (#7)
Re: should we have a fast-path planning for OLTP starjoins?

Hmmm, yeah. But that's only for the INNER JOIN case. But I've seen many
of these star join queries with LEFT JOIN too, and then the FKs are not
needed. All you need is a PK / unique index on the other side.

Indeed, many installations specifically _remove_ foreign keys because of
the dreaded RI check on delete. Basically, if you delete one or more rows
in dim1 then the referencing fact1 must be scanned to ensure that it does
not contain a reference to the deleted row. Often the referencing field on
fact1 is not indexed, because the index is almost never useful in an actual
select query, so even if you did index it several unused index metrics will
identify it as a candidate for deletion. What you get is one sequential
scan of fact1 for every row deleted from dim1. Now, we could get around
this by changing how we do delete RI checks, either by moving to statement
level triggers or bypassing triggers entirely, but until we do so, it is
likely that many customers avoid otherwise useful FK references.

#15James Hunter
james.hunter.pg@gmail.com
In reply to: Tomas Vondra (#13)
Re: should we have a fast-path planning for OLTP starjoins?

On Wed, Feb 5, 2025 at 4:23 AM Tomas Vondra <tomas@vondra.me> wrote:

If the requirement is that all "dimensions" only join to the fact table
(which in this example would be "A" I think) through a FK, then why
would these joins be illegal?

...
Essentially, this defines a "dimension" as a relation that is joined
through a PK, without any other restrictions, both of which seems fairly
simple to check, and it's a "local" feature. And we'd simply mark those
as "join at the very end, in arbitrary order". Easy enough, I guess.

As I understand your proposal, you want to detect queries that join a
large number, N, of tables -- which means doing an exhaustive search
of all possible join orders is expensive -- where N - 1 of the tables
do not join to each other, but join only to the Nth table.

PostgreSQL already falls back on geqo when it hits some heuristic that
says exhaustive search is too expensive, but you're proposing an
additional, better heuristic.

Say we have F JOIN D1 JOIN D2 ... JOIN D(N-1). In the example you
gave, the single-table predicate on F makes it small enough, I think,
that F will be the "build" side of any Hash Join, right? You're
assuming, I think, that the cardinality |F| = 1, after applying the
filter to F. And so, |F JOIN Dk| will be approximately 1, for any 1 <=
k < N. So then the join order does not matter. I think this is what
you mean by "OLTP star join."

For *OLAP* star joins, Oracle's Star Transformation [1]https://blogs.oracle.com/optimizer/post/optimizer-transformations-star-transformation works
reasonably well, where Oracle scans D1, ..., D(N-1) first, constructs
Bloom filters, etc., and then "pushes" the N-1 joins down into the Seq
Scan on F.

So, I suggest:
1. Add an *OLTP* optimization similar to what you described, but
instead of classifying the largest table as fact F, look for the "hub"
of the star and classify it as F. And then enable your optimization if
and only if the estimated nrows for F is very small.

2. For an *OLAP* optimization, do something like Oracle's Star Transformation.

Re "OLTP" vs. "OLAP": the join order does not matter for *OLTP* star
queries, because the fact table F is *small* (post-filtering). And
because F is small, it doesn't matter so much in what order you join
the dimension tables, because the result is "likely" to be small as
well.

Tom correctly points out that you really need foreign key constraints
to ensure the previous sentence's "likely," but since your
optimization is just intended to avoid considering unnecessary join
orders, you may be able to get away with asking the optimizer what it
thinks the cardinality |(... (F JOIN D1) ... JOIN Dk)| would be, and
just fall back on the existing join-search logic when the optimizer
thinks that Dk will create lots of rows (and so the join order
matters...).

So much for the OLTP case. For completeness, some discussion about the
OLAP case; fwiw, let me start by plugging my "credentials" [2]https://patents.google.com/patent/US20150088856A1/en.

The OLAP case is more complicated than the OLTP case, in that the bad
thing about *OLAP* star joins is that joins are pairwise. With OLAP
star joins, you assume that |F| is always much larger than |Dk|, and
by extension |(... (F JOIN D1) ... JOIN Dk)| is generally larger than
|D(k+1)|. And the problem for OLAP is that while every Dk potentially
filters rows out from F, you have to join to the Dk's one at a time,
so you never get as much filtering as you'd like.

For OLAP, you can take the Cartesian product of D1, ..., DN , and then
scan F to aggregate into the resulting cube; see [3]https://docs.oracle.com/en/database/oracle/oracle-database/12.2/inmem/optimizing-in-memory-aggregation.html . (Link [2]https://patents.google.com/patent/US20150088856A1/en is
related to transformation.)

Or, you can scan D1, ..., DN first, without joining anything,
constructing Hash tables and Bloom filters from your scans; then push
the Bloom filters down to the scan of F; and finally join the
(Bloom-filtered) F back to D1, ..., DN. This is what link [1]https://blogs.oracle.com/optimizer/post/optimizer-transformations-star-transformation
describes. Note that [1]https://blogs.oracle.com/optimizer/post/optimizer-transformations-star-transformation came out before [3]https://docs.oracle.com/en/database/oracle/oracle-database/12.2/inmem/optimizing-in-memory-aggregation.html.

However... for OLAP, you see from the above discussion that it's not
compilation that takes too long, but rather execution. So the
optimizations require significant changes to the SQL executor.

What you're proposing, IIUC, is a nice optimization to compilation
times, which is why (I think) you're focused on the OLTP use case. In
that case, I suggest focusing on an OLTP-specific solution, maybe a
straw man like:
1. I see a query where N-1 relations join to the Nth relation, but not
to each other (except transitively, of course).
2. Estimated cardinality for F, after pushing down single table
predicates, is very small.
3. OK, let's start joining tables D1, ..., D(N-1) in order, since
we're assuming (thanks to (1) and (2)) that the join order won't
matter.
4. Continue joining tables in this fixed (arbitrary) order, unless we
come to a Dk where the optimizer thinks joining to Dk will generate a
significant number of rows.
5. Either we join all tables in order (fast compilation!); or we hit
the case in (4), so we just fall back on the existing join logic.

Thanks,
James

[1]: https://blogs.oracle.com/optimizer/post/optimizer-transformations-star-transformation
[2]: https://patents.google.com/patent/US20150088856A1/en
[3]: https://docs.oracle.com/en/database/oracle/oracle-database/12.2/inmem/optimizing-in-memory-aggregation.html

#16Tomas Vondra
tomas@vondra.me
In reply to: James Hunter (#15)
Re: should we have a fast-path planning for OLTP starjoins?

On 2/7/25 20:11, James Hunter wrote:

On Wed, Feb 5, 2025 at 4:23 AM Tomas Vondra <tomas@vondra.me> wrote:

If the requirement is that all "dimensions" only join to the fact table
(which in this example would be "A" I think) through a FK, then why
would these joins be illegal?

...
Essentially, this defines a "dimension" as a relation that is joined
through a PK, without any other restrictions, both of which seems fairly
simple to check, and it's a "local" feature. And we'd simply mark those
as "join at the very end, in arbitrary order". Easy enough, I guess.

As I understand your proposal, you want to detect queries that join a
large number, N, of tables -- which means doing an exhaustive search
of all possible join orders is expensive -- where N - 1 of the tables
do not join to each other, but join only to the Nth table.

Yes. Essentially, it reduces the size of the problem by ignoring joins
for which we know the optimal order. We know the dimensions can be
joined last, and it does not matter in which exact order we join them.

The starjoins are a bit of the "worst case" for our heuristics, because
there are no dependencies between the dimensions, and we end up
exploring the n! possible join orders, more or less. For other joins we
quickly prune the space.

PostgreSQL already falls back on geqo when it hits some heuristic that
says exhaustive search is too expensive, but you're proposing an
additional, better heuristic.

True, but most people will never actually hit the GEQO, because the
default threshold are set like this:

join_collapse_limit = 8
geqo_threshold = 12

So the planner will not "create" join search problems with more than 8
relations, but geqo only kicks in at 12. Most systems run with the
default values for these GUCs, so they don't really use GEQO.

FWIW I don't know a lot about the GEQO internals, but I heard it doesn't
work all that well for the join order problem anyway. Not sure.

Say we have F JOIN D1 JOIN D2 ... JOIN D(N-1). In the example you
gave, the single-table predicate on F makes it small enough, I think,
that F will be the "build" side of any Hash Join, right? You're
assuming, I think, that the cardinality |F| = 1, after applying the
filter to F. And so, |F JOIN Dk| will be approximately 1, for any 1 <=
k < N. So then the join order does not matter. I think this is what
you mean by "OLTP star join."

I don't think it matters very much on which side of the join the F will
end up (or if it's a hash join, it can easily be NL). It will definitely
be in the first join, though, because all other dimensions join to it
(assuming this is just a starjoin, with only fact + dimensions).

It also doesn't really matter what's the exact cardinality of |F|. The
example used a PK lookup, so that would be 1 row, but the point is that
this is (much) cheaper than the planning. E.g. the planning might take
3ms while the execution only takes 1ms, etc. In the OLAP cases this is
usually not the case, because the queries are processing a lot of data
from the fact table, and the planning is negligible.

For *OLAP* star joins, Oracle's Star Transformation [1] works
reasonably well, where Oracle scans D1, ..., D(N-1) first, constructs
Bloom filters, etc., and then "pushes" the N-1 joins down into the Seq
Scan on F.

I don't care about OLAP star joins, at least no in this patch. It's a
completely different / separate use case, and it affects very different
parts of the planner (and also the executor, which this patch does not
need to touch at all).

So, I suggest:
1. Add an *OLTP* optimization similar to what you described, but
instead of classifying the largest table as fact F, look for the "hub"
of the star and classify it as F. And then enable your optimization if
and only if the estimated nrows for F is very small.

Right. I believe this is mostly what looking for FKs (as suggested by
Tom) would end up doing. It doesn't need to consider the cardinality of
F at all.

2. For an *OLAP* optimization, do something like Oracle's Star
Transformation.

I consider that well outside the scope of this patch.

Re "OLTP" vs. "OLAP": the join order does not matter for *OLTP* star
queries, because the fact table F is *small* (post-filtering). And
because F is small, it doesn't matter so much in what order you join
the dimension tables, because the result is "likely" to be small as
well.

I don't think that's quite true. The order of dimension joins does not
matter because the joins do not affect the join size at all. The size of
|F| has nothing to do with that, I think. We'll do the same number of
lookups against the dimensions no matter in what order we join them. And
we know it's best to join them as late as possible, after all the joins
that reduce the size (and before joins that "add" rows, I think).

Tom correctly points out that you really need foreign key constraints
to ensure the previous sentence's "likely," but since your
optimization is just intended to avoid considering unnecessary join
orders, you may be able to get away with asking the optimizer what it
thinks the cardinality |(... (F JOIN D1) ... JOIN Dk)| would be, and
just fall back on the existing join-search logic when the optimizer
thinks that Dk will create lots of rows (and so the join order
matters...).

Possibly, but TBH the join cardinality estimates can be quite dubious
pretty easily. The FK is a much more reliable (definitive) information.

So much for the OLTP case. For completeness, some discussion about the
OLAP case; fwiw, let me start by plugging my "credentials" [2].

Thanks ;-)

The OLAP case is more complicated than the OLTP case, in that the bad
thing about *OLAP* star joins is that joins are pairwise. With OLAP
star joins, you assume that |F| is always much larger than |Dk|, and
by extension |(... (F JOIN D1) ... JOIN Dk)| is generally larger than
|D(k+1)|. And the problem for OLAP is that while every Dk potentially
filters rows out from F, you have to join to the Dk's one at a time,
so you never get as much filtering as you'd like.

For OLAP, you can take the Cartesian product of D1, ..., DN , and then
scan F to aggregate into the resulting cube; see [3] . (Link [2] is
related to transformation.)

Or, you can scan D1, ..., DN first, without joining anything,
constructing Hash tables and Bloom filters from your scans; then push
the Bloom filters down to the scan of F; and finally join the
(Bloom-filtered) F back to D1, ..., DN. This is what link [1]
describes. Note that [1] came out before [3].

However... for OLAP, you see from the above discussion that it's not
compilation that takes too long, but rather execution. So the
optimizations require significant changes to the SQL executor.

Agreed. I'm not against improving the OLAP case too, but it's not what
this thread was about. It seems it'll need changes in very different
places, etc.

What you're proposing, IIUC, is a nice optimization to compilation
times, which is why (I think) you're focused on the OLTP use case. In
that case, I suggest focusing on an OLTP-specific solution, maybe a
straw man like:
1. I see a query where N-1 relations join to the Nth relation, but not
to each other (except transitively, of course).
2. Estimated cardinality for F, after pushing down single table
predicates, is very small.
3. OK, let's start joining tables D1, ..., D(N-1) in order, since
we're assuming (thanks to (1) and (2)) that the join order won't
matter.
4. Continue joining tables in this fixed (arbitrary) order, unless we
come to a Dk where the optimizer thinks joining to Dk will generate a
significant number of rows.
5. Either we join all tables in order (fast compilation!); or we hit
the case in (4), so we just fall back on the existing join logic.

Yes, I think that's pretty much the idea. Except that I don't think we
need to look at the |F| at all - it will have more impact for small |F|,
of course, but it doesn't hurt for large |F|.

I think it'll probably need to consider which joins increase/decrease
the cardinality, and "inject" the dimension joins in between those.

regards

--
Tomas Vondra

#17James Hunter
james.hunter.pg@gmail.com
In reply to: Tomas Vondra (#16)
Re: should we have a fast-path planning for OLTP starjoins?

On Fri, Feb 7, 2025 at 12:09 PM Tomas Vondra <tomas@vondra.me> wrote:

...
Yes, I think that's pretty much the idea. Except that I don't think we
need to look at the |F| at all - it will have more impact for small |F|,
of course, but it doesn't hurt for large |F|.

I think it'll probably need to consider which joins increase/decrease
the cardinality, and "inject" the dimension joins in between those.

YMMV, but I suspect you may find it much easier to look at |F|, |F
JOIN D1|, |(F JOIN D1) JOIN D2|, etc., than to consider |F JOIN D1| /
|F|, etc. (In other words, I suspect that considering absolute
cardinalities will end up easier/cleaner than considering ratios of
increases/decreases in cardinalities.) But I have not thought about
this much, so I am not putting too much weight on my suspicions.

James

#18Tomas Vondra
tomas@vondra.me
In reply to: James Hunter (#17)
Re: should we have a fast-path planning for OLTP starjoins?

On 2/7/25 23:43, James Hunter wrote:

On Fri, Feb 7, 2025 at 12:09 PM Tomas Vondra <tomas@vondra.me> wrote:

...
Yes, I think that's pretty much the idea. Except that I don't think we
need to look at the |F| at all - it will have more impact for small |F|,
of course, but it doesn't hurt for large |F|.

I think it'll probably need to consider which joins increase/decrease
the cardinality, and "inject" the dimension joins in between those.

YMMV, but I suspect you may find it much easier to look at |F|, |F
JOIN D1|, |(F JOIN D1) JOIN D2|, etc., than to consider |F JOIN D1| /
|F|, etc. (In other words, I suspect that considering absolute
cardinalities will end up easier/cleaner than considering ratios of
increases/decreases in cardinalities.) But I have not thought about
this much, so I am not putting too much weight on my suspicions.

That's not what I meant when I mentioned joins that increase/decrease
cardinality. That wasn't referring to the "dimension" joins, which we
expect to have FK and thus should not affect the cardinality at all.

Instead, I was thinking about the "other" joins (if there are any), that
may add or remove rows. AFAIK we want to join the dimensions at the
place with the lowest cardinality - the discussion mostly assumed the
joins would only reduce the cardinality, in which case we'd just leave
the dimensions until the very end.

But ISTM that may not be necessarily true. Let's say there's a join that
"multiplies" each row. It'll probably be done at the end, and the
dimension joins should probably happen right before it ... not sure.

cheers

--
Tomas Vondra

#19Tom Lane
tgl@sss.pgh.pa.us
In reply to: Tomas Vondra (#18)
Re: should we have a fast-path planning for OLTP starjoins?

Tomas Vondra <tomas@vondra.me> writes:

Instead, I was thinking about the "other" joins (if there are any), that
may add or remove rows. AFAIK we want to join the dimensions at the
place with the lowest cardinality - the discussion mostly assumed the
joins would only reduce the cardinality, in which case we'd just leave
the dimensions until the very end.

But ISTM that may not be necessarily true. Let's say there's a join that
"multiplies" each row. It'll probably be done at the end, and the
dimension joins should probably happen right before it ... not sure.

I thought the idea here was to get rid of as much join order searching
as we could. Insisting that we get the best possible plan anyway
seems counterproductive, not to mention very messy to implement.
So I'd just push all these joins to the end and be done with it.

regards, tom lane

#20Tomas Vondra
tomas@vondra.me
In reply to: Tom Lane (#19)
Re: should we have a fast-path planning for OLTP starjoins?

On 2/8/25 01:23, Tom Lane wrote:

Tomas Vondra <tomas@vondra.me> writes:

Instead, I was thinking about the "other" joins (if there are any), that
may add or remove rows. AFAIK we want to join the dimensions at the
place with the lowest cardinality - the discussion mostly assumed the
joins would only reduce the cardinality, in which case we'd just leave
the dimensions until the very end.

But ISTM that may not be necessarily true. Let's say there's a join that
"multiplies" each row. It'll probably be done at the end, and the
dimension joins should probably happen right before it ... not sure.

I thought the idea here was to get rid of as much join order searching
as we could. Insisting that we get the best possible plan anyway
seems counterproductive, not to mention very messy to implement.
So I'd just push all these joins to the end and be done with it.

Right, cutting down on the join order searching is the point. But most
of the savings comes (I think) from not considering different ordering
of the dimensions, because those are all essentially the same.

Consider a join with 16 relations, 10 of which are dimensions. There are
10! possible orders of the dimensions, but all of them behave pretty
much exactly the same. In a way, this behaves almost like a join with 7
relations, one of which represents all the 10 dimensions.

I think this "join group" abstraction (a relation representing a bunch
of relations in a particular order) would make this reasonably clean to
implement. I haven't tried yet, though.

Yes, this means we'd explore more orderings, compared to just pushing
all the dimensions to the end. In the example above, that'd be 7!/6!, so
up to ~7x orderings.

I don't know if this is worth the extra complexity, of course.

thanks

--
Tomas Vondra

#21Tomas Vondra
tomas@vondra.me
In reply to: Richard Guo (#12)
Re: should we have a fast-path planning for OLTP starjoins?

On 2/5/25 09:27, Richard Guo wrote:

On Wed, Feb 5, 2025 at 5:55 AM Tom Lane <tgl@sss.pgh.pa.us> wrote:

Right now, if we have four tables to join, we have a joinlist
(A B C D). (Really they're integer relids, but let's use names here.)
If we decide to force C to be joined last, it should be sufficient to
convert this to ((A B D) C). If C and D both look like candidates for
this treatment, we can make it be (((A B) C) D) or (((A B) D) C).
This is pretty much the same thing that happens if you set
join_collapse_limit to 1 and use JOIN syntax to force a join order.
In fact, IIRC we start out with nested joinlists and there is some
code that normally flattens them until it decides it'd be creating
too large a sub-problem. I'm suggesting selectively reversing the
flattening.

This should not be too difficult to implement. Outer joins seem to
add some complexity, though. We need to ensure that the resulting
joins in each sub-list are legal given the query's join order
constraints. For example, if we make the joinlist be (((A B) C) D),
we need to ensure that the A/B join and the (A/B)/C join are legal.

I've not done anything like this with joins before, but I AFAICS the
interesting stuff happens in deconstruct_recurse(), especially close to
the end where we check join_collapse_limit and do

joinlist = list_make2(leftpart, rightpart);

So I guess one way to "reverse the flattening" could be to do something
in deconstruct_recourse(). But I don't think that'd work all that well,
because of the recursion. We don't want to add a "pipeline break" into
the join list, we want to move the "dimension" to the end - even if only
within the group defined by join_collapse_limit.

E.g. imagine we have a join of 8 relations, with F (fact), dimensions D1
and D2, and then some artibrary tables T1, T2, T3, T4, T5. And let's say
deconstruct_recurse() sees them in this particular order

[F, T1, T2, D1, D2, T3, T4, T5]

AFAICS doing something in deconstruct_recurse() would likely split the
joinlist into four parts

[F, T1, T2] [D1] [D2] [T3, T4, T5]

which does treat the D1,D2 as if join_collapse_limit=1, but it also
splits the remaining relations into two groups, when we'd probably want
something more like this:

[F, T1, T2, T3, T4, T5] [D1] [D2]

Which should be legal, because a requirement is that D1/D2 don't have
any other join restrictions (I guess this could be relaxed a bit to only
restrictions within that particular group).

Which leads me to the conclusion that the best place to do this kind of
stuff is deconstruct_jointree(), once we have the "complete" joinlist.
We could walk it and reorder/split some of the joinlists again.

regards

--
Tomas Vondra

#22Richard Guo
guofenglinux@gmail.com
In reply to: Tomas Vondra (#21)
Re: should we have a fast-path planning for OLTP starjoins?

On Mon, Feb 10, 2025 at 9:32 AM Tomas Vondra <tomas@vondra.me> wrote:

E.g. imagine we have a join of 8 relations, with F (fact), dimensions D1
and D2, and then some artibrary tables T1, T2, T3, T4, T5. And let's say
deconstruct_recurse() sees them in this particular order

[F, T1, T2, D1, D2, T3, T4, T5]

AFAICS doing something in deconstruct_recurse() would likely split the
joinlist into four parts

[F, T1, T2] [D1] [D2] [T3, T4, T5]

which does treat the D1,D2 as if join_collapse_limit=1, but it also
splits the remaining relations into two groups, when we'd probably want
something more like this:

[F, T1, T2, T3, T4, T5] [D1] [D2]

Which should be legal, because a requirement is that D1/D2 don't have
any other join restrictions (I guess this could be relaxed a bit to only
restrictions within that particular group).

Hmm, I'm still a little concerned about whether the resulting joins
are legal. Suppose we have a join pattern like the one below.

F left join
(D1 inner join T on true) on F.b = D1.b
left join D2 on F.c = D2.c;

For this query, the original joinlist is [F, D1, T, D2]. If we
reorder it to [[F, T], D1, D2], the sub-joinlist [F, T] would fail to
produce any joins, as the F/T join is not legal.

This may not be the pattern we are targeting. But if we intend to
support it, I think we need a way to ensure that the resulting joins
are legal.

Thanks
Richard

#23Tomas Vondra
tomas@vondra.me
In reply to: Richard Guo (#22)
Re: should we have a fast-path planning for OLTP starjoins?

On 2/10/25 08:29, Richard Guo wrote:

On Mon, Feb 10, 2025 at 9:32 AM Tomas Vondra <tomas@vondra.me> wrote:

E.g. imagine we have a join of 8 relations, with F (fact), dimensions D1
and D2, and then some artibrary tables T1, T2, T3, T4, T5. And let's say
deconstruct_recurse() sees them in this particular order

[F, T1, T2, D1, D2, T3, T4, T5]

AFAICS doing something in deconstruct_recurse() would likely split the
joinlist into four parts

[F, T1, T2] [D1] [D2] [T3, T4, T5]

which does treat the D1,D2 as if join_collapse_limit=1, but it also
splits the remaining relations into two groups, when we'd probably want
something more like this:

[F, T1, T2, T3, T4, T5] [D1] [D2]

Which should be legal, because a requirement is that D1/D2 don't have
any other join restrictions (I guess this could be relaxed a bit to only
restrictions within that particular group).

Hmm, I'm still a little concerned about whether the resulting joins
are legal. Suppose we have a join pattern like the one below.

F left join
(D1 inner join T on true) on F.b = D1.b
left join D2 on F.c = D2.c;

For this query, the original joinlist is [F, D1, T, D2]. If we
reorder it to [[F, T], D1, D2], the sub-joinlist [F, T] would fail to
produce any joins, as the F/T join is not legal.

This may not be the pattern we are targeting. But if we intend to
support it, I think we need a way to ensure that the resulting joins
are legal.

It's quite possible the PoC patch I posted fails to ensure this, but I
think the assumption is we'd not reorder joins for dimensions that any
any join order restrictions (except for the FK join).

regards

--
Tomas Vondra

#24Robert Haas
robertmhaas@gmail.com
In reply to: Tomas Vondra (#16)
Re: should we have a fast-path planning for OLTP starjoins?

On Fri, Feb 7, 2025 at 3:09 PM Tomas Vondra <tomas@vondra.me> wrote:

I don't think that's quite true. The order of dimension joins does not
matter because the joins do not affect the join size at all. The size of
|F| has nothing to do with that, I think. We'll do the same number of
lookups against the dimensions no matter in what order we join them. And
we know it's best to join them as late as possible, after all the joins
that reduce the size (and before joins that "add" rows, I think).

This is often not quite true, because there are often restriction
clauses on the fact tables that result in some rows being eliminated.

e.g. SELECT * FROM hackers h JOIN languages l ON h.language_id = l.id
JOIN countries c ON h.country_id = c.id WHERE c.name = 'Czechia';

However, I think that trying to somehow leverage the existence of
either FK or LJ+UNIQUE is still a pretty good idea. In a lot of cases,
many of the joins don't change the row count, so we don't really need
to explore all possible orderings of those joins. We might be able to
define some concept of "join that does't change the row count at all"
or maybe better "join that doesn't change the row count very much".
And then if we have a lot of such joins, we can consider them as a
group. Say we have 2 joins that do change the row count significantly,
and then 10 more than don't. The 10 that don't can be done before,
between, or after the two that do, but it doesn't seem necessary to
consider doing some of them at one point and some at another.

Maybe that's not the right way to think about this problem; I haven't
read the academic literature on star-join optimization. But it has
always felt stupid to me that we spend a bunch of time considering
join orders that are not meaningfully different, and I think what
makes two join orders not meaningfully different is that we're
commuting joins that are not changing the row count.

(Also worth noting: even joins of this general form change the row
count, they can only reduce it.)

--
Robert Haas
EDB: http://www.enterprisedb.com

#25Richard Guo
guofenglinux@gmail.com
In reply to: Tomas Vondra (#23)
Re: should we have a fast-path planning for OLTP starjoins?

On Mon, Feb 10, 2025 at 5:35 PM Tomas Vondra <tomas@vondra.me> wrote:

On 2/10/25 08:29, Richard Guo wrote:

Hmm, I'm still a little concerned about whether the resulting joins
are legal. Suppose we have a join pattern like the one below.

F left join
(D1 inner join T on true) on F.b = D1.b
left join D2 on F.c = D2.c;

For this query, the original joinlist is [F, D1, T, D2]. If we
reorder it to [[F, T], D1, D2], the sub-joinlist [F, T] would fail to
produce any joins, as the F/T join is not legal.

This may not be the pattern we are targeting. But if we intend to
support it, I think we need a way to ensure that the resulting joins
are legal.

It's quite possible the PoC patch I posted fails to ensure this, but I
think the assumption is we'd not reorder joins for dimensions that any
any join order restrictions (except for the FK join).

Then, we'll need a way to determine if a given relation has join-order
restrictions, which doesn't seem like a trivial task. We do have the
has_join_restriction() function, but it considers any relations
involved in an outer join as having join restrictions, and that makes
it unsuitable for our needs here.

Thanks
Richard

#26Tomas Vondra
tomas@vondra.me
In reply to: Robert Haas (#24)
Re: should we have a fast-path planning for OLTP starjoins?

On 2/10/25 22:36, Robert Haas wrote:

On Fri, Feb 7, 2025 at 3:09 PM Tomas Vondra <tomas@vondra.me> wrote:

I don't think that's quite true. The order of dimension joins does not
matter because the joins do not affect the join size at all. The size of
|F| has nothing to do with that, I think. We'll do the same number of
lookups against the dimensions no matter in what order we join them. And
we know it's best to join them as late as possible, after all the joins
that reduce the size (and before joins that "add" rows, I think).

This is often not quite true, because there are often restriction
clauses on the fact tables that result in some rows being eliminated.

e.g. SELECT * FROM hackers h JOIN languages l ON h.language_id = l.id
JOIN countries c ON h.country_id = c.id WHERE c.name = 'Czechia';

True. I think this was discussed earlier in this thread - dimensions
with additional restrictions may affect the row count, and thus would be
exempt from this (and would instead go through the "regular" join order
search algorithm). So I assumed the "dimensions" don't have any such
restrictions in my message, I should have mentioned that.

However, I think that trying to somehow leverage the existence of
either FK or LJ+UNIQUE is still a pretty good idea. In a lot of cases,
many of the joins don't change the row count, so we don't really need
to explore all possible orderings of those joins. We might be able to
define some concept of "join that does't change the row count at all"
or maybe better "join that doesn't change the row count very much".
And then if we have a lot of such joins, we can consider them as a
group. Say we have 2 joins that do change the row count significantly,
and then 10 more than don't. The 10 that don't can be done before,
between, or after the two that do, but it doesn't seem necessary to
consider doing some of them at one point and some at another.

Maybe that's not the right way to think about this problem; I haven't
read the academic literature on star-join optimization. But it has
always felt stupid to me that we spend a bunch of time considering
join orders that are not meaningfully different, and I think what
makes two join orders not meaningfully different is that we're
commuting joins that are not changing the row count.

(Also worth noting: even joins of this general form change the row
count, they can only reduce it.)

I searched for papers on star-joins, but pretty much everything I found
focuses on the OLAP case. Which is interesting, I think the OLTP
star-join I described seems quite different, and I'm not sure the trade
offs are necessarily the same.

My gut feeling is that in the first "phase" we should focus on the case
with no restrictions - that makes it obvious what the optimal order is,
and it will help a significant fraction of cases.

And then in the next step we can try doing something for cases with
restrictions - be it some sort of greedy algorithm, something that
leverages knowledge of the selectivity to prune join orders early
(instead of actually exploring all N! join orders like today). Or
something else, not sure.

regards

--
Tomas Vondra

#27Tomas Vondra
tomas@vondra.me
In reply to: Richard Guo (#25)
Re: should we have a fast-path planning for OLTP starjoins?

On 2/11/25 10:28, Richard Guo wrote:

On Mon, Feb 10, 2025 at 5:35 PM Tomas Vondra <tomas@vondra.me> wrote:

On 2/10/25 08:29, Richard Guo wrote:

Hmm, I'm still a little concerned about whether the resulting joins
are legal. Suppose we have a join pattern like the one below.

F left join
(D1 inner join T on true) on F.b = D1.b
left join D2 on F.c = D2.c;

For this query, the original joinlist is [F, D1, T, D2]. If we
reorder it to [[F, T], D1, D2], the sub-joinlist [F, T] would fail to
produce any joins, as the F/T join is not legal.

This may not be the pattern we are targeting. But if we intend to
support it, I think we need a way to ensure that the resulting joins
are legal.

It's quite possible the PoC patch I posted fails to ensure this, but I
think the assumption is we'd not reorder joins for dimensions that any
any join order restrictions (except for the FK join).

Then, we'll need a way to determine if a given relation has join-order
restrictions, which doesn't seem like a trivial task. We do have the
has_join_restriction() function, but it considers any relations
involved in an outer join as having join restrictions, and that makes
it unsuitable for our needs here.

I admit knowing next to nothing about join order planning :-( Could you
maybe explain why it would be non-trivial to determine if a relation has
join-order restrictions? Surely we already determine that, no? So what
would we need to do differently?

Or are you saying that because has_join_restriction() treats each
relation with an outer join as having a restriction, that makes it
unusable for the purpose of this optimization/patch? And we'd need to
invent something more elaborate?

I'm not sure that's quite true. The problem with joining the dimensions
(with inner joins) is *exactly* the lack of restrictions, which means
that explore possible orders of those dimensions (all N! of them). With
the restrictions (e.g. from LEFT JOIN), that's no longer true - in a
way, this is similar to what the patch does. And in fact, replacing the
inner joins with LEFT JOINs makes the queries much faster. I've seen
this used as a workaround to cut down on planning time ...

So I don't think treating outer joins as "having restriction" is a
problem. It doesn't regress any queries, although it might lead to a bit
strange situation that "less restricted" joins are faster to plan.

regards

--
Tomas Vondra

#28Tomas Vondra
tomas@vondra.me
In reply to: Tomas Vondra (#20)
1 attachment(s)
Re: should we have a fast-path planning for OLTP starjoins?

On 2/4/25 22:55, Tom Lane wrote:

Tomas Vondra <tomas@vondra.me> writes:

The interesting thing about this is we pretty much have all the
infrastructure for detecting such FK-related join conditions
already. Possibly the join order forcing could be done with
existing infrastructure too (by manipulating the joinlist).

Maybe, interesting. I've ruled out relying on the FKeys early in the
coding, but I'm sure there's infrastructure the patch could use.

It would be very sad to do that work twice in a patch that purports
to reduce planning time. If it's done too late to suit you now,
could we move it to happen earlier?

What kind of "manipulation" of the joinlist you have in mind?

Right now, if we have four tables to join, we have a joinlist
(A B C D). (Really they're integer relids, but let's use names here.)
If we decide to force C to be joined last, it should be sufficient to
convert this to ((A B D) C). If C and D both look like candidates for
this treatment, we can make it be (((A B) C) D) or (((A B) D) C).
This is pretty much the same thing that happens if you set
join_collapse_limit to 1 and use JOIN syntax to force a join order.
In fact, IIRC we start out with nested joinlists and there is some
code that normally flattens them until it decides it'd be creating
too large a sub-problem. I'm suggesting selectively reversing the
flattening.

regards, tom lane

Here's a patch trying to do it more like this - by manipulating the
lists describing the join problems, before it's passed the the actual
join search algorithm (which is where the PoC patch did this).

I wonder if this is roughly the place where you imagined this would be
done, or if you envision some other issue with this approach. The patch
is definitely incomplete, there's plenty of XXX comments about places
missing some code, etc.

I initially tried to manipulate the joinlist much earlier - pretty much
right at the end of deconstruct_jointree. But that turned out to be way
too early. To identify dimensions etc. we need to check stuff about
foreign keys, join clauses, ... and that's not available that early.

So I think this needs to happen much later in query_planner(), and the
patch does it right before the make_one_rel() call. Maybe that's too
late, but it needs to happen after match_foreign_keys_to_quals(), as it
relies on some of the FK info built by that call. Maybe we could call
match_foreign_keys_to_quals() earlier, but I don't quite see any
benefits of doing that ...

On 2/8/25 02:49, Tomas Vondra wrote:

On 2/8/25 01:23, Tom Lane wrote:

Tomas Vondra <tomas@vondra.me> writes:

Instead, I was thinking about the "other" joins (if there are any), that
may add or remove rows. AFAIK we want to join the dimensions at the
place with the lowest cardinality - the discussion mostly assumed the
joins would only reduce the cardinality, in which case we'd just leave
the dimensions until the very end.

But ISTM that may not be necessarily true. Let's say there's a join that
"multiplies" each row. It'll probably be done at the end, and the
dimension joins should probably happen right before it ... not sure.

I thought the idea here was to get rid of as much join order searching
as we could. Insisting that we get the best possible plan anyway
seems counterproductive, not to mention very messy to implement.
So I'd just push all these joins to the end and be done with it.

Right, cutting down on the join order searching is the point. But most
of the savings comes (I think) from not considering different ordering
of the dimensions, because those are all essentially the same.

Consider a join with 16 relations, 10 of which are dimensions. There are
10! possible orders of the dimensions, but all of them behave pretty
much exactly the same. In a way, this behaves almost like a join with 7
relations, one of which represents all the 10 dimensions.

I think this "join group" abstraction (a relation representing a bunch
of relations in a particular order) would make this reasonably clean to
implement. I haven't tried yet, though.

Yes, this means we'd explore more orderings, compared to just pushing
all the dimensions to the end. In the example above, that'd be 7!/6!, so
up to ~7x orderings.

I don't know if this is worth the extra complexity, of course.

I'm still concerned about regressions when happen to postpone some
expensive dimension joins after a join that increases the cardinality.
And the "join group" would address that. But It probably is not a very
common query pattern, and it'd require changes to join_search_one_level.

I'm not sure what could / should count as 'dimension'. The patch doesn't
implement this yet, but I think it can mostly copy how we match the FK
to the join in get_foreign_key_join_selectivity. There's probably more
to think about, though. For example, don't we need to check NOT NULL /
nullfrac on the referencing side? Also, it probably interacts with
LEFT/OUTER joins. I plan to start strict and then relax and handle some
additional cases.

I'm however struggling with the concept of join order restrictions a
bit. I suspect we need to worry about that when walking the relation
list and figuring out what can be a dimension, but I've never worked
with this, so my mental model of how this works is not great.

Another question is if this planning shortcut (which for the dimensions
mostly picks a random join order) could have some unexpected impact on
the rest of the planning. For example, could we "miss" some join
producing tuples in an interesting order? Or could we fail to consider a
partition-wise join?

Could this "shortcut" restrict the rest of the plan in some undesirable
way? For example, if some of the tables are partitioned, could this mean
we no longer can do partition-wise joins with the (mostly arbitrary)
join order we picked?

There's also a "patch" directory, with some SQL scripts creating two
simple examples of schemas/queries that would benefit from this. The
"create-1/select-1" examples are the simple starjoins, this thread
focuses on. It might be modified to do "snowflake" join, which is
fundamentally a variant of this query type.

The second example (create-2/select-2) is quite different, in that it's
nor a starjoin schema. It still joins one "main" table with multiple
"dimensions", but the FKs go in the other direction (to a single column
in the main table). But it has a very similar bottleneck - the order of
the joins is expensive, but it often does not matter very much, because
the query matches just one row anyway. And even if it returns more rows,
isn't the join order determined just by the selectivity of each join?
Maybe the starjoin optimization could be made to work for this type too?

regards

--
Tomas Vondra

Attachments:

v2-0001-Simplify-planning-of-starjoin-queries.patchtext/x-patch; charset=UTF-8; name=v2-0001-Simplify-planning-of-starjoin-queries.patchDownload
From a821bf2382cd08829b36cd67cfb424340d9f6408 Mon Sep 17 00:00:00 2001
From: Tomas Vondra <tomas@vondra.me>
Date: Thu, 26 Jun 2025 17:49:29 +0200
Subject: [PATCH v2] Simplify planning of starjoin queries

---
 patch/create-1.sql                        |  18 +
 patch/create-2.sql                        |  11 +
 patch/select-1.sql                        |   9 +
 patch/select-2.sql                        |   9 +
 src/backend/optimizer/plan/analyzejoins.c | 425 ++++++++++++++++++++++
 src/backend/optimizer/plan/planmain.c     |  10 +
 src/backend/utils/misc/guc_tables.c       |  10 +
 src/include/optimizer/planmain.h          |   2 +
 8 files changed, 494 insertions(+)
 create mode 100644 patch/create-1.sql
 create mode 100644 patch/create-2.sql
 create mode 100644 patch/select-1.sql
 create mode 100644 patch/select-2.sql

diff --git a/patch/create-1.sql b/patch/create-1.sql
new file mode 100644
index 00000000000..8df04fd0677
--- /dev/null
+++ b/patch/create-1.sql
@@ -0,0 +1,18 @@
+create table dim1 (id int primary key, val1 text);
+create table dim2 (id int primary key, val2 text);
+create table dim3 (id int primary key, val3 text);
+create table dim4 (id int primary key, val4 text);
+create table dim5 (id int primary key, val5 text);
+create table dim6 (id int primary key, val6 text);
+create table dim7 (id int primary key, val7 text);
+
+create table t (id serial primary key,
+                id1 int references dim1(id),
+                id2 int references dim2(id),
+                id3 int references dim3(id),
+                id4 int references dim4(id),
+                id5 int references dim5(id),
+                id6 int references dim6(id),
+                id7 int references dim7(id));
+
+vacuum analyze;
diff --git a/patch/create-2.sql b/patch/create-2.sql
new file mode 100644
index 00000000000..cdf612dde8f
--- /dev/null
+++ b/patch/create-2.sql
@@ -0,0 +1,11 @@
+create table t (id serial primary key, a text);
+
+create table dim1 (id1 int primary key references t(id), val1 text);
+create table dim2 (id2 int primary key references t(id), val2 text);
+create table dim3 (id3 int primary key references t(id), val3 text);
+create table dim4 (id4 int primary key references t(id), val4 text);
+create table dim5 (id5 int primary key references t(id), val5 text);
+create table dim6 (id6 int primary key references t(id), val6 text);
+create table dim7 (id7 int primary key references t(id), val7 text);
+
+vacuum analyze;
diff --git a/patch/select-1.sql b/patch/select-1.sql
new file mode 100644
index 00000000000..1535ddcdc8f
--- /dev/null
+++ b/patch/select-1.sql
@@ -0,0 +1,9 @@
+--set join_collapse_limit = 1;
+select * from t
+    join dim1 on (dim1.id = id1)
+    join dim2 on (dim2.id = id2)
+    join dim3 on (dim3.id = id3)
+    join dim4 on (dim4.id = id4)
+    join dim5 on (dim5.id = id5)
+    join dim6 on (dim6.id = id6)
+    join dim7 on (dim7.id = id7);
diff --git a/patch/select-2.sql b/patch/select-2.sql
new file mode 100644
index 00000000000..4e1d2a7b0e7
--- /dev/null
+++ b/patch/select-2.sql
@@ -0,0 +1,9 @@
+-- set join_collapse_limit = 1;
+select * from t
+    left join dim1 on (id = id1)
+    left join dim2 on (id = id2)
+    left join dim3 on (id = id3)
+    left join dim4 on (id = id4)
+    left join dim5 on (id = id5)
+    left join dim6 on (id = id6)
+    left join dim7 on (id = id7);
diff --git a/src/backend/optimizer/plan/analyzejoins.c b/src/backend/optimizer/plan/analyzejoins.c
index 4d55c2ea591..c57c3db94ef 100644
--- a/src/backend/optimizer/plan/analyzejoins.c
+++ b/src/backend/optimizer/plan/analyzejoins.c
@@ -51,6 +51,7 @@ typedef struct
 } SelfJoinCandidate;
 
 bool		enable_self_join_elimination;
+bool		enable_starjoin_join_search;
 
 /* local functions */
 static bool join_is_removable(PlannerInfo *root, SpecialJoinInfo *sjinfo);
@@ -2512,3 +2513,427 @@ remove_useless_self_joins(PlannerInfo *root, List *joinlist)
 
 	return joinlist;
 }
+
+/*
+ * starjoin_match_to_foreign_key
+ *		Try to match a join to a FK constraint.
+ *
+ * For a relation to be a dimension (for the starjoin heuristics), it needs
+ * to be joined through a FK constraint. The dimension is expected to be
+ * on the PK side of the join. The relation must not have any additional
+ * join clauses, beyond those matching the foreign key.
+ *
+ * We already have a list of relevant foreign keys, and we use that info
+ * for selectivity estimation in get_foreign_key_join_selectivity(). And
+ * we're actually doing something quite similar here.
+ *
+ * XXX Do we need to worry about the join type, e.g. inner/outer joins,
+ * semi/anti? get_foreign_key_join_selectivity() does care about it, and
+ * ignores some of those cases. Maybe we should too?
+ *
+ * XXX Check there are no other join clauses, beyond those matching the
+ * foreign key. But do we already have the joininfo at this point? Some
+ * of this stuff gets build only during the join order search later.
+ * The match_foreign_keys_to_quals() probably needs to be aware of all
+ * this, so how does it do that?
+ */
+static bool
+starjoin_match_to_foreign_key(PlannerInfo *root, RelOptInfo *rel)
+{
+	ListCell   *lc;
+
+	/* Consider each FK constraint that is known to match the query */
+	foreach(lc, root->fkey_list)
+	{
+		ForeignKeyOptInfo *fkinfo = (ForeignKeyOptInfo *) lfirst(lc);
+		int			nmatches = 0;
+
+		/* rel is not the referenced table of the FK */
+		if (fkinfo->ref_relid != rel->relid)
+			continue;
+
+		/*
+		 * Do we have a match for each key of the FK?
+		 *
+		 * XXX get_foreign_key_join_selectivity checks EquivalenceClasses,
+		 * we should probably (definitely) do that here too.
+		 *
+		 * XXX We should check that all the clauses have the same relation
+		 * on the other side (for multi-column keys). And that there are
+		 * no other join clauses other than those matching the FK.
+		 *
+		 * XXX Do we need to check that the FK side of the join (i.e. the fact
+		 * table) has the columns referenced as NOT NULL? Otherwise we could
+		 * have a FK join that reduces the cardinality, which is one of
+		 * the arguments why it's fine to move the join (that it doesn't
+		 * change the cardinality). But if the join is LEFT JOIN, this
+		 * should be fine too - but do we get here with LEFT JOINs?
+		 *
+		 * XXX Do we need to check if the other side of the FK is in the
+		 * current join list? Maybe it's in some later one?
+		 */
+		for (int i = 0; i < fkinfo->nkeys; i++)
+		{
+			bool		has_matching_clause = false;
+
+			/*
+			 * Is there a clause matching this FK key?
+			 *
+			 * XXX We need to make sure it's a valid match, e.g. that the
+			 * same referencing table matches all keys in a composite FK,
+			 * and so on.
+			 *
+			 * XXX Do we need to check some relationship to other rels in
+			 * the same jointree item? E.g. the referencing table should
+			 * not be a dimensions we already removed.
+			 */
+			if ((fkinfo->rinfos[i] != NULL) || (fkinfo->eclass[i] != NULL))
+			{
+				has_matching_clause = true;
+				nmatches++;
+				continue;
+			}
+
+			/* found a FK key without a matching join clause, ignore the FK */
+			if (has_matching_clause)
+				break;
+		}
+
+		/* matched all FK keys */
+		if (nmatches == fkinfo->nkeys)
+		{
+			return true;
+		}
+	}
+
+	return false;
+}
+
+
+/*
+ * starjoin_is_dimension
+ *		Determine if a range table entry is a dimension in a starjoin.
+ *
+ * To be considered a dimension for the simplified join order search, the
+ * join must not affect the cardinality of the join. We ensure that by
+ * requiring a couple things:
+ *
+ * 1) the join clause has to match a FK (that is, the fact does have at
+ *    most one matching row in the dimension)
+ *
+ * 2) the FK side (the fact table) should be marked as NOT NULL, so that
+ *    we know there's exactly one dimension row for each fact table row
+ *
+ * 3) there must be no additional restrictions on the relation (that
+ *    might eliminate some of the rows, reducing the cardinality)
+ *
+ * XXX The Implementation is incomplete. It probably needs more thought,
+ * considering some join types would allow relaxing some of the checks
+ * (e.g. outer joins may not require checking (2) or possibly even (3),
+ * depending on where the condition is, what varnullingrels it has).
+ *
+ * XXX I wonder if we could handle (3) by ordering the dimensions by the
+ * selectivity of the restriction. There are no join clauses between the
+ * dimensions (ignoring the snowflake joins, but even there the clauses
+ * don't go between branches), so the selectivity could be treated as
+ * a measure of how much it shrinks the join result. So we could just
+ * sort the dimensions by this, starting with the lowest selectivity
+ * (close to 0.0), and ending with dimensions without restrictions (in
+ * which case the selectivity is 1.0).
+ *
+ * XXX If the join in INNER, and the fact side has NULL values in the
+ * join key, we might consider nullfrac as restriction.
+ *
+ * XXX I'm not sure how careful this needs to be about join order
+ * restrictions. Maybe it should call have_relevant_joinclause and
+ * have_join_order_restriction, to ensure the join order is OK?
+ *
+ * The optimizer/README is not very clear about this, but maybe it's
+ * a too specific question. It seems to say the relations in those
+ * lists can be joined in any order (lines 94 and 106). Maybe that's
+ * not what it means, or I'm misunderstanding it.
+ *
+ * It however seems has_join_restrictions() in join_search_one_level()
+ * forces the code to look only at "earlier" rels in the list
+ *
+ *     first_rel = foreach_current_index(r) + 1
+ *
+ * So maybe we just need to stop once we find a rel with a restriction,
+ * as determined byhas_join_restrictions()?
+ *
+ * But there's also join_is_legal() to check legality of joins, with
+ * LEFT/RIGHT joins, and IN/EXISTS clauses. See README line 188. And it
+ * also looks-up the SpecialJoinInfo for the join. So maybe we should
+ * lookup RelOptInfo for both sides of the join, and call join_is_legal
+ * on that? Might be too expensive, though. Maybe do that only when
+ * has_join_restrictions already says yes?
+ *
+ * Maybe we should use has_join_restrictions(), but in a  different way.
+ * We could still treat rels with restrictions as dimensions, and move
+ * that to the separate list (that doesn't change the join order), but
+ * stop once we hit the first non-dimension with a restriction? Because
+ * if any relation after that was a dimention, we wouldn't be able to
+ * move it to the separate list. It'd change the join order in a way
+ * that might violate the restriction. I believe that's the idea behind
+ * first_rel in join_search_one_level(), but maybe not.
+ *
+ * Perhaps have_join_order_restriction and have_relevant_joinclause are
+ * useful for this, rather than has_join_restrictions? We might look at
+ * actual pairs of relations, and/or check there's no join order
+ * restriction with respect to the relations we skipped/moved to the
+ * list of dimension?
+ *
+ * AFAICS it's just the skipping that can break the order restrictions?
+ * Adding something to the list of dimensions keeps the order (at least
+ * with respect to the rels after it).
+ */
+static bool
+starjoin_is_dimension(PlannerInfo *root, RangeTblRef *rtr)
+{
+	Index			rti = rtr->rtindex;
+	RangeTblEntry  *rte = root->simple_rte_array[rti];
+	RelOptInfo	   *rel = root->simple_rel_array[rti];
+
+	/* only plain relations can be dimensions (we need FK/PK join) */
+	if ((rte->rtekind != RTE_RELATION) ||
+		(rel->reloptkind != RELOPT_BASEREL))
+		return false;
+
+	/*
+	 * Does it have any conditions/restrictions that may affect the number
+	 * of rows matched? If yes, don't treat as dimension.
+	 *
+	 * Dimensions in a starjoin may have restrictions, but that means it'll
+	 * change cardinality of the joins (reduce it), so it may be better to
+	 * join it early. We leave it to the regular join order planning. The
+	 * expectation is that most dimensions won't have extra restrictions.
+	 *
+	 * XXX Should we check some other fields, like lateral references, and
+	 * so on? Or is that unnecessary? What about eclasses?
+	 */
+	if (rel->baserestrictinfo != NIL)
+		return false;
+
+	/*
+	 * See if the join clause matches a foreign key. It should match a
+	 * single relation on the other side, and the dimension should be on
+	 * the PK side.
+	 *
+	 * XXX loosely inspired by get_foreign_key_join_selectivity()
+	 */
+	if (!starjoin_match_to_foreign_key(root, rel))
+		return false;
+
+	/*
+	 * XXX Maybe some additional checks here ...
+	 */
+
+	return true;
+}
+
+/*
+ * starjoin_adjust_joins
+ *		Adjust the jointree for starjoins, to simplify the join order search.
+ *
+ * The join search for starjoin queries is surprisingly expensive, because
+ * there are very few join order restrictions. Consider a starjoin query
+ *
+ *  SELECT * FROM f
+ *     JOIN d1 ON (f.id1 = d1.id)
+ *     JOIN d2 ON (f.id2 = d2.id)
+ *     ...
+ *     JOIN d9 ON (f.id9 = d9.id)
+ *
+ * There are no clauses between the dimension tables (d#), which means those
+ * tables can be joined in almost arbitrary order. This means the standard
+ * join_order_search() would explore a N! possible join orders. It is not
+ * that bad in practice, because we split the problem by from_collapse_limit
+ * into a sequence of smaller problems, but even for the default limit of
+ * 8 relations it's quite expensive. This can be easily demonstrated by
+ * setting from_collapse_limit=1 for example starjoin queries.
+ *
+ * The idea here is to apply a much simpler join order search for this type
+ * of queries, without too much risk of picking a much worse plans. It is
+ * however a trade off between how expensive we allow this to be, and how
+ * good the decisions will be. This can help only starjoins with multiple
+ * dimension tables, and we don't want to harm planning of other queries,
+ * so the basic "query shape" detection needs to be very cheap. And then
+ * it needs to be cheaper than the regular join order search.
+ *
+ * If a perfect check is impossible or too expensive, it's better to end
+ * up with a cheap false negative (i.e. and not use the optimization),
+ * rather than risk regressions in other cases.
+ *
+ * The simplified join order search relies on the fact that if the joins
+ * to dimensions do not alter the cardinality of the join relation, then
+ * the relative order of those joins does not matter. All the possible
+ * orders are guaranteed to perform the same. So we can simply pick one
+ * of those orders, and "hardcode" it in the join tree later passed to the
+ * join_order_search().
+ *
+ * The query may involve joins to additional (non-dimension) tables, and
+ * those may alter cardinality. Some joins may increase it, other joins
+ * may decrease it. In principle, it'd be best to first perform all the
+ * joins that reduce join size, then join all the dimensions, and finally
+ * perform joins that may increase the join size. But this is not done
+ * now, currently we simply apply all the dimensions at the end, hoping
+ * that the earlier joins did not inflate the join too much.
+ *
+ * The definition of a dimension is a bit vague. For our definition see
+ * the comment at starjoin_is_dimension().
+ *
+ * The optimization works by manipulating the joinlist (originally built
+ * by deconstruct_jointree), which decomposed the original jointree into
+ * smaller "problems" depending on join type and join_collapse_limit. We
+ * inspect those smaller lists, and selectively split them into smaller
+ * problems to force a join order. This may effectively undo some of the
+ * merging done by deconstruct_jointree(), which tries to build problems
+ * with up to join_collapse_limit relations.
+ *
+ * For example, imagine a join problem with 8 rels - one fact table and
+ * then 7 dimensions, which we can represent a joinlist with 8 elements.
+ *
+ * (D7, D6, D5, D4, D3, D2, D1, F)
+ *
+ * Assuming all those joins meet the requirements (have a matching FK,
+ * don't affect the join cardinality, ...), then we can split this into
+ *
+ * (D7, (D6, (D5, (D4, (D3, (D2, (D1, F)))))))
+ *
+ * which is a nested joinlist, with only two elements on each level. That
+ * means there's no need for expensive join order search, there's only
+ * one way to join the relations (two, if we consider the relations may
+ * switch sides).
+ *
+ * The joinlist may already be nested, with multiple smaller subproblems.
+ * We look at each individual join problem independently, i.e. we don't
+ * try to merge problems to build join_collapse_limit problems again.
+ * This is partially to keep it cheap/simple, but also so not change
+ * behavior for cases when people use join_collapse_limit to force some
+ * particular join shape.
+ *
+ * XXX A possible improvement is to allow handling snowflake joins, i.e.
+ * recursive dimensions. That would require a somewhat more complicated
+ * processing, because a dimension would be allowed other rels, as long
+ * as those are dimensions too. And we'd need to be more careful about
+ * the order in which join them to the top of the join.
+ *
+ * XXX One possible risk is that moving the dimension joins at the very
+ * end may move that after joins that increase the cardinality. Which
+ * may cause a regression. Such joins however don't seem very common, at
+ * least in regular starjoin queries. So maybe we could simply check if
+ * there are any such joins and disable this optimization. Is there a
+ * cheap way to identify that a join increases cardinality?
+ *
+ * XXX Ideally, we'd perform the dimension joins at the place with the
+ * lowest cardinality. Imagine a joinlist
+ *
+ * (D1, D2, A, B, F)
+ *
+ * Where A increases join cardinality, while B does not (possibly even
+ * reduces it). Ideally, we'd do the join like this
+ *
+ * (A, (D2, (D1, (B, F))))
+ *
+ * so D1/D2 get joined at the point of "lowest cardinality". We probably
+ * don't want to do all this cardinality estimation work here, it'd copy
+ * what we already do in the join_order_search(). Perhaps we could invent
+ * a "join item" representing a join to all those dimensions, and pass it
+ * to join_order_search()? And let it pick the right place for it? It'd
+ * always join them in the same order, it'd not reorder them. It would
+ * still do the regular cardinality estimations etc. It would be trivial
+ * to disable the optimization if needed - don't collapse the dimensions
+ * into the new type of join item.
+ */
+List *
+starjoin_adjust_joins(PlannerInfo *root, List *joinlist)
+{
+	ListCell *lc;
+	List *newlist = NIL;
+	List *dimensions = NIL;
+
+	/*
+	 * Do nothing if starjoin optimization not enabled / not applicable.
+	 *
+	 * XXX It might seems we can skip this for lists with <= 2 items, but
+	 * that does not work, the elements may be nested list, and we need to
+	 * descend into those. So do what remove_useless_self_joins() does, and
+	 * only bail out for the simplest single-relation case (i.e. no joins).
+	 */
+	if (!enable_starjoin_join_search || joinlist == NIL ||
+		(list_length(joinlist) == 1 && !IsA(linitial(joinlist), List)))
+		return joinlist;
+
+	/*
+	 * Process the current join problem - split the elements into dimensions
+	 * and non-dimensions. If there are dimensions, add them back at the end,
+	 * as small single-rel joins.
+	 *
+	 * The list may contain various types of elements. It may contain a list,
+	 * which means it's an independent join search problem and we need to
+	 * process it recursively. Or it may be RangeTblRef, in which case we
+	 * need to check if it's a dimension. Other types of elements are just
+	 * added back to the list as-is.
+	 *
+	 * XXX I think we need to be careful to keep the order of the list (for
+	 * the non-dimension entries). The join_search_one_level() relies on
+	 * that when handling join order restrictions.
+	 *
+	 * XXX It might be better to only create a new list if needed, i.e. once
+	 * we find the first dimension. So that non-starjoin queries don't pay
+	 * for something they don't need. A mutable iterator might be a way, but
+	 * I'm not sure how expensive this really is.
+	 */
+	foreach (lc, joinlist)
+	{
+		Node *item = (Node *) lfirst(lc);
+
+		/* a separate join search problem, handle it recursively */
+		if (IsA(item, List))
+		{
+			newlist = lappend(newlist,
+							  starjoin_adjust_joins(root, (List *) item));
+			continue;
+		}
+
+		/*
+		 * Non-RangeTblRef elements can't be considered a dimension (only
+		 * baserels can have FK, etc.), so just add those to the list.
+		 */
+		if (!IsA(item, RangeTblRef))
+		{
+			newlist = lappend(newlist, item);
+			continue;
+		}
+
+		/*
+		 * An entry representing a baserel. If it's a dimension, save it in
+		 * a separate list, and we'll add it at the "top" of the join at the
+		 * end. Otherwise add it to the list just like other elements.
+		 */
+		if (starjoin_is_dimension(root, (RangeTblRef *) item))
+		{
+			dimensions = lappend(dimensions, item);
+			continue;
+		}
+
+		/* not a dimension, add it to the list directly */
+		newlist = lappend(newlist, item);
+	}
+
+	/*
+	 * If we found some dimensions, add them to the join tree one by one.
+	 * The exact order does not matter, so we add them in the order we
+	 * found them in the original list.
+	 *
+	 * We need to add them by creating smaller 2-element lists, with the
+	 * rest of the list on one side and the dimension on the other. This
+	 * is how we force the explicit join order.
+	 */
+	foreach (lc, dimensions)
+	{
+		newlist = list_make2(newlist, list_make1(lfirst(lc)));
+	}
+
+	return newlist;
+}
diff --git a/src/backend/optimizer/plan/planmain.c b/src/backend/optimizer/plan/planmain.c
index 5467e094ca7..c75a5203aae 100644
--- a/src/backend/optimizer/plan/planmain.c
+++ b/src/backend/optimizer/plan/planmain.c
@@ -282,6 +282,16 @@ query_planner(PlannerInfo *root,
 	 */
 	distribute_row_identity_vars(root);
 
+	/*
+	 * Try to simplify the join search problem for starjoin-like joins, with
+	 * joins over FK relationships. The dimensions can be joined in almost
+	 * any order, so the join search can be close to factorial complexity.
+	 * But there's not much difference between such join orders, so we just
+	 * leave the dimensions at the end of each group (as determined by the
+	 * join_collapse_limit earlier).
+	 */
+	joinlist = starjoin_adjust_joins(root, joinlist);
+
 	/*
 	 * Ready to do the primary planning.
 	 */
diff --git a/src/backend/utils/misc/guc_tables.c b/src/backend/utils/misc/guc_tables.c
index d14b1678e7f..4c7642b3102 100644
--- a/src/backend/utils/misc/guc_tables.c
+++ b/src/backend/utils/misc/guc_tables.c
@@ -1036,6 +1036,16 @@ struct config_bool ConfigureNamesBool[] =
 		true,
 		NULL, NULL, NULL
 	},
+	{
+		{"enable_starjoin_join_search", PGC_USERSET, QUERY_TUNING_METHOD,
+			gettext_noop("Enables simplified join order planning for starjoins."),
+			NULL,
+			GUC_EXPLAIN
+		},
+		&enable_starjoin_join_search,
+		false,
+		NULL, NULL, NULL
+	},
 	{
 		{"geqo", PGC_USERSET, QUERY_TUNING_GEQO,
 			gettext_noop("Enables genetic query optimization."),
diff --git a/src/include/optimizer/planmain.h b/src/include/optimizer/planmain.h
index 9d3debcab28..fee6c695d03 100644
--- a/src/include/optimizer/planmain.h
+++ b/src/include/optimizer/planmain.h
@@ -21,6 +21,7 @@
 #define DEFAULT_CURSOR_TUPLE_FRACTION 0.1
 extern PGDLLIMPORT double cursor_tuple_fraction;
 extern PGDLLIMPORT bool enable_self_join_elimination;
+extern PGDLLIMPORT bool enable_starjoin_join_search;
 
 /* query_planner callback to compute query_pathkeys */
 typedef void (*query_pathkeys_callback) (PlannerInfo *root, void *extra);
@@ -119,6 +120,7 @@ extern bool innerrel_is_unique_ext(PlannerInfo *root, Relids joinrelids,
 								   JoinType jointype, List *restrictlist,
 								   bool force_cache, List **extra_clauses);
 extern List *remove_useless_self_joins(PlannerInfo *root, List *joinlist);
+extern List *starjoin_adjust_joins(PlannerInfo *root, List *joinlist);
 
 /*
  * prototypes for plan/setrefs.c
-- 
2.50.1

#29Tom Lane
tgl@sss.pgh.pa.us
In reply to: Tomas Vondra (#28)
1 attachment(s)
Re: should we have a fast-path planning for OLTP starjoins?

[ sorry for ridiculously slow response to this ]

Tomas Vondra <tomas@vondra.me> writes:

Here's a patch trying to do it more like this - by manipulating the
lists describing the join problems, before it's passed the the actual
join search algorithm (which is where the PoC patch did this).
I wonder if this is roughly the place where you imagined this would be
done, or if you envision some other issue with this approach.

Cool. This is proof-of-concept that manipulating the joinlist can
do what we need done. So we can move on to what heuristics we need
to use.

I initially tried to manipulate the joinlist much earlier - pretty much
right at the end of deconstruct_jointree. But that turned out to be way
too early. To identify dimensions etc. we need to check stuff about
foreign keys, join clauses, ... and that's not available that early.

So I think this needs to happen much later in query_planner(), and the
patch does it right before the make_one_rel() call. Maybe that's too
late, but it needs to happen after match_foreign_keys_to_quals(), as it
relies on some of the FK info built by that call. Maybe we could call
match_foreign_keys_to_quals() earlier, but I don't quite see any
benefits of doing that ...

I don't have a problem with doing it where you did it, but the comment
should explain the placement. What you do have in the comment mostly
belongs with the code, too; it's not the business of the caller. So
in planmain.c something like

+	/*
+	 * Try to simplify the join search problem for starjoin-like joins.
+	 * This step relies on info about FK relationships, so we can't do it
+	 * till after match_foreign_keys_to_quals().
+	 */

would be more appropriate IMO. I'd be slightly inclined to put the
GUC test there, too:

+	if (enable_starjoin_join_search)
+		joinlist = starjoin_adjust_joins(root, joinlist);

I agree that you need to worry about join order restrictions,
and that it's not immediately clear how to do that. join_is_legal
would work if we could call it, but the problem is that at this
stage we'll only have RelOptInfos for base rels not join rels.
If we have a joinlist (A B C D) and we are considering treating
C as a dimension table, then the questions we have to ask are:
(a) is it okay to build the (A B D) join without C?
(b) is it okay to join (A B D) to C?

In this simple case, I think (b) must be true if (a) is, but
I'm not quite sure that that's so in more complex cases with
multiple candidates for dimension tables. In any case,
join_is_legal won't help us if we don't have join RelOptInfos.

I'm inclined to start by using has_join_restriction: if that
says "false" for a candidate dimension table, it should be safe
to postpone the join to the dimension table. We might be able
to refine that later.

The second example (create-2/select-2) is quite different, in that it's
nor a starjoin schema. It still joins one "main" table with multiple
"dimensions", but the FKs go in the other direction (to a single column
in the main table). But it has a very similar bottleneck - the order of
the joins is expensive, but it often does not matter very much, because
the query matches just one row anyway. And even if it returns more rows,
isn't the join order determined just by the selectivity of each join?
Maybe the starjoin optimization could be made to work for this type too?

Yeah, I'm slightly itchy about relying on FKs in this heuristic at
all; it doesn't seem like quite the right thing. I think we do want
one side of the join to be joining to a PK or at least a unique index,
but I'm not sure we need to insist on there being an FK relationship.

A couple of minor coding notes:

* There's no point in doing anything (except recursing) if the joinlist
contains fewer than 3 items, and maybe as a further heuristic
this shouldn't kick in till later yet, like 5 or so items.
When there are just a few items, the possibility of missing the
best plan seems to outweigh the minimal savings in plan time.

* Joinlists never contain anything but RangeTblRefs and sub-lists.
See make_rel_from_joinlist.

* Your reconstructed joinlist is overly complicated. Instead of

+ newlist = list_make2(newlist, list_make1(lfirst(lc)));

you could just do

+ newlist = list_make2(newlist, lfirst(lc));

because a single-element subproblem is useless.

I notice that the patch doesn't apply cleanly anymore because of
the introduction of guc_parameters.dat. So here's a v3 that
rebases over that, and I took the liberty of fixing the joinlist
construction as above, but I didn't do anything else.

regards, tom lane

Attachments:

v3-0001-Simplify-planning-of-starjoin-queries.patchtext/x-diff; charset=us-ascii; name=v3-0001-Simplify-planning-of-starjoin-queries.patchDownload
diff --git a/src/backend/optimizer/plan/analyzejoins.c b/src/backend/optimizer/plan/analyzejoins.c
index 2a3dea88a94..5417c10fbf8 100644
--- a/src/backend/optimizer/plan/analyzejoins.c
+++ b/src/backend/optimizer/plan/analyzejoins.c
@@ -51,6 +51,7 @@ typedef struct
 } SelfJoinCandidate;
 
 bool		enable_self_join_elimination;
+bool		enable_starjoin_join_search;
 
 /* local functions */
 static bool join_is_removable(PlannerInfo *root, SpecialJoinInfo *sjinfo);
@@ -2514,3 +2515,427 @@ remove_useless_self_joins(PlannerInfo *root, List *joinlist)
 
 	return joinlist;
 }
+
+/*
+ * starjoin_match_to_foreign_key
+ *		Try to match a join to a FK constraint.
+ *
+ * For a relation to be a dimension (for the starjoin heuristics), it needs
+ * to be joined through a FK constraint. The dimension is expected to be
+ * on the PK side of the join. The relation must not have any additional
+ * join clauses, beyond those matching the foreign key.
+ *
+ * We already have a list of relevant foreign keys, and we use that info
+ * for selectivity estimation in get_foreign_key_join_selectivity(). And
+ * we're actually doing something quite similar here.
+ *
+ * XXX Do we need to worry about the join type, e.g. inner/outer joins,
+ * semi/anti? get_foreign_key_join_selectivity() does care about it, and
+ * ignores some of those cases. Maybe we should too?
+ *
+ * XXX Check there are no other join clauses, beyond those matching the
+ * foreign key. But do we already have the joininfo at this point? Some
+ * of this stuff gets build only during the join order search later.
+ * The match_foreign_keys_to_quals() probably needs to be aware of all
+ * this, so how does it do that?
+ */
+static bool
+starjoin_match_to_foreign_key(PlannerInfo *root, RelOptInfo *rel)
+{
+	ListCell   *lc;
+
+	/* Consider each FK constraint that is known to match the query */
+	foreach(lc, root->fkey_list)
+	{
+		ForeignKeyOptInfo *fkinfo = (ForeignKeyOptInfo *) lfirst(lc);
+		int			nmatches = 0;
+
+		/* rel is not the referenced table of the FK */
+		if (fkinfo->ref_relid != rel->relid)
+			continue;
+
+		/*
+		 * Do we have a match for each key of the FK?
+		 *
+		 * XXX get_foreign_key_join_selectivity checks EquivalenceClasses,
+		 * we should probably (definitely) do that here too.
+		 *
+		 * XXX We should check that all the clauses have the same relation
+		 * on the other side (for multi-column keys). And that there are
+		 * no other join clauses other than those matching the FK.
+		 *
+		 * XXX Do we need to check that the FK side of the join (i.e. the fact
+		 * table) has the columns referenced as NOT NULL? Otherwise we could
+		 * have a FK join that reduces the cardinality, which is one of
+		 * the arguments why it's fine to move the join (that it doesn't
+		 * change the cardinality). But if the join is LEFT JOIN, this
+		 * should be fine too - but do we get here with LEFT JOINs?
+		 *
+		 * XXX Do we need to check if the other side of the FK is in the
+		 * current join list? Maybe it's in some later one?
+		 */
+		for (int i = 0; i < fkinfo->nkeys; i++)
+		{
+			bool		has_matching_clause = false;
+
+			/*
+			 * Is there a clause matching this FK key?
+			 *
+			 * XXX We need to make sure it's a valid match, e.g. that the
+			 * same referencing table matches all keys in a composite FK,
+			 * and so on.
+			 *
+			 * XXX Do we need to check some relationship to other rels in
+			 * the same jointree item? E.g. the referencing table should
+			 * not be a dimensions we already removed.
+			 */
+			if ((fkinfo->rinfos[i] != NULL) || (fkinfo->eclass[i] != NULL))
+			{
+				has_matching_clause = true;
+				nmatches++;
+				continue;
+			}
+
+			/* found a FK key without a matching join clause, ignore the FK */
+			if (has_matching_clause)
+				break;
+		}
+
+		/* matched all FK keys */
+		if (nmatches == fkinfo->nkeys)
+		{
+			return true;
+		}
+	}
+
+	return false;
+}
+
+
+/*
+ * starjoin_is_dimension
+ *		Determine if a range table entry is a dimension in a starjoin.
+ *
+ * To be considered a dimension for the simplified join order search, the
+ * join must not affect the cardinality of the join. We ensure that by
+ * requiring a couple things:
+ *
+ * 1) the join clause has to match a FK (that is, the fact does have at
+ *    most one matching row in the dimension)
+ *
+ * 2) the FK side (the fact table) should be marked as NOT NULL, so that
+ *    we know there's exactly one dimension row for each fact table row
+ *
+ * 3) there must be no additional restrictions on the relation (that
+ *    might eliminate some of the rows, reducing the cardinality)
+ *
+ * XXX The Implementation is incomplete. It probably needs more thought,
+ * considering some join types would allow relaxing some of the checks
+ * (e.g. outer joins may not require checking (2) or possibly even (3),
+ * depending on where the condition is, what varnullingrels it has).
+ *
+ * XXX I wonder if we could handle (3) by ordering the dimensions by the
+ * selectivity of the restriction. There are no join clauses between the
+ * dimensions (ignoring the snowflake joins, but even there the clauses
+ * don't go between branches), so the selectivity could be treated as
+ * a measure of how much it shrinks the join result. So we could just
+ * sort the dimensions by this, starting with the lowest selectivity
+ * (close to 0.0), and ending with dimensions without restrictions (in
+ * which case the selectivity is 1.0).
+ *
+ * XXX If the join in INNER, and the fact side has NULL values in the
+ * join key, we might consider nullfrac as restriction.
+ *
+ * XXX I'm not sure how careful this needs to be about join order
+ * restrictions. Maybe it should call have_relevant_joinclause and
+ * have_join_order_restriction, to ensure the join order is OK?
+ *
+ * The optimizer/README is not very clear about this, but maybe it's
+ * a too specific question. It seems to say the relations in those
+ * lists can be joined in any order (lines 94 and 106). Maybe that's
+ * not what it means, or I'm misunderstanding it.
+ *
+ * It however seems has_join_restrictions() in join_search_one_level()
+ * forces the code to look only at "earlier" rels in the list
+ *
+ *     first_rel = foreach_current_index(r) + 1
+ *
+ * So maybe we just need to stop once we find a rel with a restriction,
+ * as determined byhas_join_restrictions()?
+ *
+ * But there's also join_is_legal() to check legality of joins, with
+ * LEFT/RIGHT joins, and IN/EXISTS clauses. See README line 188. And it
+ * also looks-up the SpecialJoinInfo for the join. So maybe we should
+ * lookup RelOptInfo for both sides of the join, and call join_is_legal
+ * on that? Might be too expensive, though. Maybe do that only when
+ * has_join_restrictions already says yes?
+ *
+ * Maybe we should use has_join_restrictions(), but in a  different way.
+ * We could still treat rels with restrictions as dimensions, and move
+ * that to the separate list (that doesn't change the join order), but
+ * stop once we hit the first non-dimension with a restriction? Because
+ * if any relation after that was a dimention, we wouldn't be able to
+ * move it to the separate list. It'd change the join order in a way
+ * that might violate the restriction. I believe that's the idea behind
+ * first_rel in join_search_one_level(), but maybe not.
+ *
+ * Perhaps have_join_order_restriction and have_relevant_joinclause are
+ * useful for this, rather than has_join_restrictions? We might look at
+ * actual pairs of relations, and/or check there's no join order
+ * restriction with respect to the relations we skipped/moved to the
+ * list of dimension?
+ *
+ * AFAICS it's just the skipping that can break the order restrictions?
+ * Adding something to the list of dimensions keeps the order (at least
+ * with respect to the rels after it).
+ */
+static bool
+starjoin_is_dimension(PlannerInfo *root, RangeTblRef *rtr)
+{
+	Index			rti = rtr->rtindex;
+	RangeTblEntry  *rte = root->simple_rte_array[rti];
+	RelOptInfo	   *rel = root->simple_rel_array[rti];
+
+	/* only plain relations can be dimensions (we need FK/PK join) */
+	if ((rte->rtekind != RTE_RELATION) ||
+		(rel->reloptkind != RELOPT_BASEREL))
+		return false;
+
+	/*
+	 * Does it have any conditions/restrictions that may affect the number
+	 * of rows matched? If yes, don't treat as dimension.
+	 *
+	 * Dimensions in a starjoin may have restrictions, but that means it'll
+	 * change cardinality of the joins (reduce it), so it may be better to
+	 * join it early. We leave it to the regular join order planning. The
+	 * expectation is that most dimensions won't have extra restrictions.
+	 *
+	 * XXX Should we check some other fields, like lateral references, and
+	 * so on? Or is that unnecessary? What about eclasses?
+	 */
+	if (rel->baserestrictinfo != NIL)
+		return false;
+
+	/*
+	 * See if the join clause matches a foreign key. It should match a
+	 * single relation on the other side, and the dimension should be on
+	 * the PK side.
+	 *
+	 * XXX loosely inspired by get_foreign_key_join_selectivity()
+	 */
+	if (!starjoin_match_to_foreign_key(root, rel))
+		return false;
+
+	/*
+	 * XXX Maybe some additional checks here ...
+	 */
+
+	return true;
+}
+
+/*
+ * starjoin_adjust_joins
+ *		Adjust the jointree for starjoins, to simplify the join order search.
+ *
+ * The join search for starjoin queries is surprisingly expensive, because
+ * there are very few join order restrictions. Consider a starjoin query
+ *
+ *  SELECT * FROM f
+ *     JOIN d1 ON (f.id1 = d1.id)
+ *     JOIN d2 ON (f.id2 = d2.id)
+ *     ...
+ *     JOIN d9 ON (f.id9 = d9.id)
+ *
+ * There are no clauses between the dimension tables (d#), which means those
+ * tables can be joined in almost arbitrary order. This means the standard
+ * join_order_search() would explore a N! possible join orders. It is not
+ * that bad in practice, because we split the problem by from_collapse_limit
+ * into a sequence of smaller problems, but even for the default limit of
+ * 8 relations it's quite expensive. This can be easily demonstrated by
+ * setting from_collapse_limit=1 for example starjoin queries.
+ *
+ * The idea here is to apply a much simpler join order search for this type
+ * of queries, without too much risk of picking a much worse plans. It is
+ * however a trade off between how expensive we allow this to be, and how
+ * good the decisions will be. This can help only starjoins with multiple
+ * dimension tables, and we don't want to harm planning of other queries,
+ * so the basic "query shape" detection needs to be very cheap. And then
+ * it needs to be cheaper than the regular join order search.
+ *
+ * If a perfect check is impossible or too expensive, it's better to end
+ * up with a cheap false negative (i.e. and not use the optimization),
+ * rather than risk regressions in other cases.
+ *
+ * The simplified join order search relies on the fact that if the joins
+ * to dimensions do not alter the cardinality of the join relation, then
+ * the relative order of those joins does not matter. All the possible
+ * orders are guaranteed to perform the same. So we can simply pick one
+ * of those orders, and "hardcode" it in the join tree later passed to the
+ * join_order_search().
+ *
+ * The query may involve joins to additional (non-dimension) tables, and
+ * those may alter cardinality. Some joins may increase it, other joins
+ * may decrease it. In principle, it'd be best to first perform all the
+ * joins that reduce join size, then join all the dimensions, and finally
+ * perform joins that may increase the join size. But this is not done
+ * now, currently we simply apply all the dimensions at the end, hoping
+ * that the earlier joins did not inflate the join too much.
+ *
+ * The definition of a dimension is a bit vague. For our definition see
+ * the comment at starjoin_is_dimension().
+ *
+ * The optimization works by manipulating the joinlist (originally built
+ * by deconstruct_jointree), which decomposed the original jointree into
+ * smaller "problems" depending on join type and join_collapse_limit. We
+ * inspect those smaller lists, and selectively split them into smaller
+ * problems to force a join order. This may effectively undo some of the
+ * merging done by deconstruct_jointree(), which tries to build problems
+ * with up to join_collapse_limit relations.
+ *
+ * For example, imagine a join problem with 8 rels - one fact table and
+ * then 7 dimensions, which we can represent a joinlist with 8 elements.
+ *
+ * (D7, D6, D5, D4, D3, D2, D1, F)
+ *
+ * Assuming all those joins meet the requirements (have a matching FK,
+ * don't affect the join cardinality, ...), then we can split this into
+ *
+ * (D7, (D6, (D5, (D4, (D3, (D2, (D1, F)))))))
+ *
+ * which is a nested joinlist, with only two elements on each level. That
+ * means there's no need for expensive join order search, there's only
+ * one way to join the relations (two, if we consider the relations may
+ * switch sides).
+ *
+ * The joinlist may already be nested, with multiple smaller subproblems.
+ * We look at each individual join problem independently, i.e. we don't
+ * try to merge problems to build join_collapse_limit problems again.
+ * This is partially to keep it cheap/simple, but also so not change
+ * behavior for cases when people use join_collapse_limit to force some
+ * particular join shape.
+ *
+ * XXX A possible improvement is to allow handling snowflake joins, i.e.
+ * recursive dimensions. That would require a somewhat more complicated
+ * processing, because a dimension would be allowed other rels, as long
+ * as those are dimensions too. And we'd need to be more careful about
+ * the order in which join them to the top of the join.
+ *
+ * XXX One possible risk is that moving the dimension joins at the very
+ * end may move that after joins that increase the cardinality. Which
+ * may cause a regression. Such joins however don't seem very common, at
+ * least in regular starjoin queries. So maybe we could simply check if
+ * there are any such joins and disable this optimization. Is there a
+ * cheap way to identify that a join increases cardinality?
+ *
+ * XXX Ideally, we'd perform the dimension joins at the place with the
+ * lowest cardinality. Imagine a joinlist
+ *
+ * (D1, D2, A, B, F)
+ *
+ * Where A increases join cardinality, while B does not (possibly even
+ * reduces it). Ideally, we'd do the join like this
+ *
+ * (A, (D2, (D1, (B, F))))
+ *
+ * so D1/D2 get joined at the point of "lowest cardinality". We probably
+ * don't want to do all this cardinality estimation work here, it'd copy
+ * what we already do in the join_order_search(). Perhaps we could invent
+ * a "join item" representing a join to all those dimensions, and pass it
+ * to join_order_search()? And let it pick the right place for it? It'd
+ * always join them in the same order, it'd not reorder them. It would
+ * still do the regular cardinality estimations etc. It would be trivial
+ * to disable the optimization if needed - don't collapse the dimensions
+ * into the new type of join item.
+ */
+List *
+starjoin_adjust_joins(PlannerInfo *root, List *joinlist)
+{
+	ListCell *lc;
+	List *newlist = NIL;
+	List *dimensions = NIL;
+
+	/*
+	 * Do nothing if starjoin optimization not enabled / not applicable.
+	 *
+	 * XXX It might seems we can skip this for lists with <= 2 items, but
+	 * that does not work, the elements may be nested list, and we need to
+	 * descend into those. So do what remove_useless_self_joins() does, and
+	 * only bail out for the simplest single-relation case (i.e. no joins).
+	 */
+	if (!enable_starjoin_join_search || joinlist == NIL ||
+		(list_length(joinlist) == 1 && !IsA(linitial(joinlist), List)))
+		return joinlist;
+
+	/*
+	 * Process the current join problem - split the elements into dimensions
+	 * and non-dimensions. If there are dimensions, add them back at the end,
+	 * as small single-rel joins.
+	 *
+	 * The list may contain various types of elements. It may contain a list,
+	 * which means it's an independent join search problem and we need to
+	 * process it recursively. Or it may be RangeTblRef, in which case we
+	 * need to check if it's a dimension. Other types of elements are just
+	 * added back to the list as-is.
+	 *
+	 * XXX I think we need to be careful to keep the order of the list (for
+	 * the non-dimension entries). The join_search_one_level() relies on
+	 * that when handling join order restrictions.
+	 *
+	 * XXX It might be better to only create a new list if needed, i.e. once
+	 * we find the first dimension. So that non-starjoin queries don't pay
+	 * for something they don't need. A mutable iterator might be a way, but
+	 * I'm not sure how expensive this really is.
+	 */
+	foreach (lc, joinlist)
+	{
+		Node *item = (Node *) lfirst(lc);
+
+		/* a separate join search problem, handle it recursively */
+		if (IsA(item, List))
+		{
+			newlist = lappend(newlist,
+							  starjoin_adjust_joins(root, (List *) item));
+			continue;
+		}
+
+		/*
+		 * Non-RangeTblRef elements can't be considered a dimension (only
+		 * baserels can have FK, etc.), so just add those to the list.
+		 */
+		if (!IsA(item, RangeTblRef))
+		{
+			newlist = lappend(newlist, item);
+			continue;
+		}
+
+		/*
+		 * An entry representing a baserel. If it's a dimension, save it in
+		 * a separate list, and we'll add it at the "top" of the join at the
+		 * end. Otherwise add it to the list just like other elements.
+		 */
+		if (starjoin_is_dimension(root, (RangeTblRef *) item))
+		{
+			dimensions = lappend(dimensions, item);
+			continue;
+		}
+
+		/* not a dimension, add it to the list directly */
+		newlist = lappend(newlist, item);
+	}
+
+	/*
+	 * If we found some dimensions, add them to the join tree one by one.
+	 * The exact order does not matter, so we add them in the order we
+	 * found them in the original list.
+	 *
+	 * We need to add them by creating smaller 2-element lists, with the rest
+	 * of the list being a sub-problem and then adding the dimension
+	 * table. This is how we force the desired join order.
+	 */
+	foreach (lc, dimensions)
+	{
+		newlist = list_make2(newlist, lfirst(lc));
+	}
+
+	return newlist;
+}
diff --git a/src/backend/optimizer/plan/planmain.c b/src/backend/optimizer/plan/planmain.c
index 5467e094ca7..c75a5203aae 100644
--- a/src/backend/optimizer/plan/planmain.c
+++ b/src/backend/optimizer/plan/planmain.c
@@ -282,6 +282,16 @@ query_planner(PlannerInfo *root,
 	 */
 	distribute_row_identity_vars(root);
 
+	/*
+	 * Try to simplify the join search problem for starjoin-like joins, with
+	 * joins over FK relationships. The dimensions can be joined in almost
+	 * any order, so the join search can be close to factorial complexity.
+	 * But there's not much difference between such join orders, so we just
+	 * leave the dimensions at the end of each group (as determined by the
+	 * join_collapse_limit earlier).
+	 */
+	joinlist = starjoin_adjust_joins(root, joinlist);
+
 	/*
 	 * Ready to do the primary planning.
 	 */
diff --git a/src/backend/utils/misc/guc_parameters.dat b/src/backend/utils/misc/guc_parameters.dat
index 6bc6be13d2a..bde4378527e 100644
--- a/src/backend/utils/misc/guc_parameters.dat
+++ b/src/backend/utils/misc/guc_parameters.dat
@@ -203,6 +203,13 @@
   boot_val => 'true',
 },
 
+{ name => 'enable_starjoin_join_search', type => 'bool', context => 'PGC_USERSET', group => 'QUERY_TUNING_METHOD',
+  short_desc => 'Enables simplified join order planning for starjoins.',
+  flags => 'GUC_EXPLAIN',
+  variable => 'enable_starjoin_join_search',
+  boot_val => 'false',
+},
+
 { name => 'geqo', type => 'bool', context => 'PGC_USERSET', group => 'QUERY_TUNING_GEQO',
   short_desc => 'Enables genetic query optimization.',
   long_desc => 'This algorithm attempts to do planning without exhaustive searching.',
diff --git a/src/include/optimizer/planmain.h b/src/include/optimizer/planmain.h
index 9d3debcab28..fee6c695d03 100644
--- a/src/include/optimizer/planmain.h
+++ b/src/include/optimizer/planmain.h
@@ -21,6 +21,7 @@
 #define DEFAULT_CURSOR_TUPLE_FRACTION 0.1
 extern PGDLLIMPORT double cursor_tuple_fraction;
 extern PGDLLIMPORT bool enable_self_join_elimination;
+extern PGDLLIMPORT bool enable_starjoin_join_search;
 
 /* query_planner callback to compute query_pathkeys */
 typedef void (*query_pathkeys_callback) (PlannerInfo *root, void *extra);
@@ -119,6 +120,7 @@ extern bool innerrel_is_unique_ext(PlannerInfo *root, Relids joinrelids,
 								   JoinType jointype, List *restrictlist,
 								   bool force_cache, List **extra_clauses);
 extern List *remove_useless_self_joins(PlannerInfo *root, List *joinlist);
+extern List *starjoin_adjust_joins(PlannerInfo *root, List *joinlist);
 
 /*
  * prototypes for plan/setrefs.c
#30Tomas Vondra
tomas@vondra.me
In reply to: Tom Lane (#29)
1 attachment(s)
Re: should we have a fast-path planning for OLTP starjoins?

On 9/23/25 21:46, Tom Lane wrote:

[ sorry for ridiculously slow response to this ]

Tomas Vondra <tomas@vondra.me> writes:

Here's a patch trying to do it more like this - by manipulating the
lists describing the join problems, before it's passed the the actual
join search algorithm (which is where the PoC patch did this).
I wonder if this is roughly the place where you imagined this would be
done, or if you envision some other issue with this approach.

Cool. This is proof-of-concept that manipulating the joinlist can
do what we need done. So we can move on to what heuristics we need
to use.

Thanks. Good to hear this seems like a reasonable place.

I initially tried to manipulate the joinlist much earlier - pretty much
right at the end of deconstruct_jointree. But that turned out to be way
too early. To identify dimensions etc. we need to check stuff about
foreign keys, join clauses, ... and that's not available that early.

So I think this needs to happen much later in query_planner(), and the
patch does it right before the make_one_rel() call. Maybe that's too
late, but it needs to happen after match_foreign_keys_to_quals(), as it
relies on some of the FK info built by that call. Maybe we could call
match_foreign_keys_to_quals() earlier, but I don't quite see any
benefits of doing that ...

I don't have a problem with doing it where you did it, but the comment
should explain the placement. What you do have in the comment mostly
belongs with the code, too; it's not the business of the caller. So
in planmain.c something like

+	/*
+	 * Try to simplify the join search problem for starjoin-like joins.
+	 * This step relies on info about FK relationships, so we can't do it
+	 * till after match_foreign_keys_to_quals().
+	 */

would be more appropriate IMO.

I agree. I've adopted your wording, and moved the original comment to
starjoin_adjust_joins (with some changes).

I'd be slightly inclined to put the GUC test there, too:

+	if (enable_starjoin_join_search)
+		joinlist = starjoin_adjust_joins(root, joinlist);

I'm not sure I like this very mcuh. No other call in query_planner()
does it like that. Most don't have such GUC, but at least
remove_useless_self_joins does, and it still doesn't check it here.

I agree that you need to worry about join order restrictions,
and that it's not immediately clear how to do that. join_is_legal
would work if we could call it, but the problem is that at this
stage we'll only have RelOptInfos for base rels not join rels.
If we have a joinlist (A B C D) and we are considering treating
C as a dimension table, then the questions we have to ask are:
(a) is it okay to build the (A B D) join without C?
(b) is it okay to join (A B D) to C?

In this simple case, I think (b) must be true if (a) is, but
I'm not quite sure that that's so in more complex cases with
multiple candidates for dimension tables. In any case,
join_is_legal won't help us if we don't have join RelOptInfos.

I'm inclined to start by using has_join_restriction: if that
says "false" for a candidate dimension table, it should be safe
to postpone the join to the dimension table. We might be able
to refine that later.

Thanks. I agree has_join_restriction seems like a good start, I'll give
that a try in the next patch version.

When thinking about this, I realized the has_join_restriction() is only
ever used in join_search_one_level(), i.e. when dealing with each small
join order problem. Doesn't this mean the deconstructed jointree must
already consider the restrictions in some way? I don't see any explicit
mentions of such join order restrictions in deconstruct_recurse. It must
not violate any ordering restrictions by splitting the joins in a
"wrong" way, right? If I set join_collapse_limit=1 it still needs to
satisfy all the rules.

I was wondering if maybe we could piggy-back on that, somehow. But maybe
that's not very practical, and has_join_restriction() is the way to go.

It's been a while since I looked at this patch, so it's possible I
already concluded that wouldn't work, and forgot about it :-/

The second example (create-2/select-2) is quite different, in that it's
nor a starjoin schema. It still joins one "main" table with multiple
"dimensions", but the FKs go in the other direction (to a single column
in the main table). But it has a very similar bottleneck - the order of
the joins is expensive, but it often does not matter very much, because
the query matches just one row anyway. And even if it returns more rows,
isn't the join order determined just by the selectivity of each join?
Maybe the starjoin optimization could be made to work for this type too?

Yeah, I'm slightly itchy about relying on FKs in this heuristic at
all; it doesn't seem like quite the right thing. I think we do want
one side of the join to be joining to a PK or at least a unique index,
but I'm not sure we need to insist on there being an FK relationship.

True, requiring the FK may be unnecessary in this case. We do need to
guarantee the cardinality does not change, but a UNIQUE + LEFT JOIN
seems to be enough for that.

BTW the v3 lost the patch/ directory. I assume that wasn't intentional,
so I added it back into v4.

A couple of minor coding notes:

* There's no point in doing anything (except recursing) if the joinlist
contains fewer than 3 items, and maybe as a further heuristic
this shouldn't kick in till later yet, like 5 or so items.
When there are just a few items, the possibility of missing the
best plan seems to outweigh the minimal savings in plan time.

* Joinlists never contain anything but RangeTblRefs and sub-lists.
See make_rel_from_joinlist.

* Your reconstructed joinlist is overly complicated. Instead of

+ newlist = list_make2(newlist, list_make1(lfirst(lc)));

you could just do

+ newlist = list_make2(newlist, lfirst(lc));

because a single-element subproblem is useless.

I notice that the patch doesn't apply cleanly anymore because of
the introduction of guc_parameters.dat. So here's a v3 that
rebases over that, and I took the liberty of fixing the joinlist
construction as above, but I didn't do anything else.

Thanks. I agree with all of these comments, and updated v4 accordingly.
cfbot started complaining about guc_parameters.dat and a couple more
things, so v4 fixes that too.

regards

--
Tomas Vondra

Attachments:

v4-0001-Simplify-planning-of-starjoin-queries.patchtext/x-patch; charset=UTF-8; name=v4-0001-Simplify-planning-of-starjoin-queries.patchDownload
From b8473cd5c93bf594896d2be40a7f093e90aeca16 Mon Sep 17 00:00:00 2001
From: Tomas Vondra <tomas@vondra.me>
Date: Sat, 8 Nov 2025 18:16:30 +0100
Subject: [PATCH v4] Simplify planning of starjoin queries

---
 patch/create-1.sql                            |  18 +
 patch/create-2.sql                            |  11 +
 patch/select-1.sql                            |   9 +
 patch/select-2.sql                            |   9 +
 src/backend/optimizer/plan/analyzejoins.c     | 443 ++++++++++++++++++
 src/backend/optimizer/plan/planmain.c         |   7 +
 src/backend/utils/misc/guc_parameters.dat     |   7 +
 src/backend/utils/misc/postgresql.conf.sample |   1 +
 src/include/optimizer/planmain.h              |   2 +
 src/test/regress/expected/sysviews.out        |   3 +-
 10 files changed, 509 insertions(+), 1 deletion(-)
 create mode 100644 patch/create-1.sql
 create mode 100644 patch/create-2.sql
 create mode 100644 patch/select-1.sql
 create mode 100644 patch/select-2.sql

diff --git a/patch/create-1.sql b/patch/create-1.sql
new file mode 100644
index 00000000000..8df04fd0677
--- /dev/null
+++ b/patch/create-1.sql
@@ -0,0 +1,18 @@
+create table dim1 (id int primary key, val1 text);
+create table dim2 (id int primary key, val2 text);
+create table dim3 (id int primary key, val3 text);
+create table dim4 (id int primary key, val4 text);
+create table dim5 (id int primary key, val5 text);
+create table dim6 (id int primary key, val6 text);
+create table dim7 (id int primary key, val7 text);
+
+create table t (id serial primary key,
+                id1 int references dim1(id),
+                id2 int references dim2(id),
+                id3 int references dim3(id),
+                id4 int references dim4(id),
+                id5 int references dim5(id),
+                id6 int references dim6(id),
+                id7 int references dim7(id));
+
+vacuum analyze;
diff --git a/patch/create-2.sql b/patch/create-2.sql
new file mode 100644
index 00000000000..cdf612dde8f
--- /dev/null
+++ b/patch/create-2.sql
@@ -0,0 +1,11 @@
+create table t (id serial primary key, a text);
+
+create table dim1 (id1 int primary key references t(id), val1 text);
+create table dim2 (id2 int primary key references t(id), val2 text);
+create table dim3 (id3 int primary key references t(id), val3 text);
+create table dim4 (id4 int primary key references t(id), val4 text);
+create table dim5 (id5 int primary key references t(id), val5 text);
+create table dim6 (id6 int primary key references t(id), val6 text);
+create table dim7 (id7 int primary key references t(id), val7 text);
+
+vacuum analyze;
diff --git a/patch/select-1.sql b/patch/select-1.sql
new file mode 100644
index 00000000000..1535ddcdc8f
--- /dev/null
+++ b/patch/select-1.sql
@@ -0,0 +1,9 @@
+--set join_collapse_limit = 1;
+select * from t
+    join dim1 on (dim1.id = id1)
+    join dim2 on (dim2.id = id2)
+    join dim3 on (dim3.id = id3)
+    join dim4 on (dim4.id = id4)
+    join dim5 on (dim5.id = id5)
+    join dim6 on (dim6.id = id6)
+    join dim7 on (dim7.id = id7);
diff --git a/patch/select-2.sql b/patch/select-2.sql
new file mode 100644
index 00000000000..4e1d2a7b0e7
--- /dev/null
+++ b/patch/select-2.sql
@@ -0,0 +1,9 @@
+-- set join_collapse_limit = 1;
+select * from t
+    left join dim1 on (id = id1)
+    left join dim2 on (id = id2)
+    left join dim3 on (id = id3)
+    left join dim4 on (id = id4)
+    left join dim5 on (id = id5)
+    left join dim6 on (id = id6)
+    left join dim7 on (id = id7);
diff --git a/src/backend/optimizer/plan/analyzejoins.c b/src/backend/optimizer/plan/analyzejoins.c
index e592e1ac3d1..66b1c8c540c 100644
--- a/src/backend/optimizer/plan/analyzejoins.c
+++ b/src/backend/optimizer/plan/analyzejoins.c
@@ -51,6 +51,7 @@ typedef struct
 } SelfJoinCandidate;
 
 bool		enable_self_join_elimination;
+bool		enable_starjoin_join_search;
 
 /* local functions */
 static bool join_is_removable(PlannerInfo *root, SpecialJoinInfo *sjinfo);
@@ -2511,3 +2512,445 @@ remove_useless_self_joins(PlannerInfo *root, List *joinlist)
 
 	return joinlist;
 }
+
+/*
+ * starjoin_match_to_foreign_key
+ *		Try to match a join to a FK constraint.
+ *
+ * For a relation to be a dimension (for the starjoin heuristics), it needs
+ * to be joined through a FK constraint. The dimension is expected to be
+ * on the PK side of the join. The relation must not have any additional
+ * join clauses, beyond those matching the foreign key.
+ *
+ * We already have a list of relevant foreign keys, and we use that info
+ * for selectivity estimation in get_foreign_key_join_selectivity(). And
+ * we're actually doing something quite similar here.
+ *
+ * XXX Do we need to worry about the join type, e.g. inner/outer joins,
+ * semi/anti? get_foreign_key_join_selectivity() does care about it, and
+ * ignores some of those cases. Maybe we should too?
+ *
+ * XXX Check there are no other join clauses, beyond those matching the
+ * foreign key. But do we already have the joininfo at this point? Some
+ * of this stuff gets build only during the join order search later.
+ * The match_foreign_keys_to_quals() probably needs to be aware of all
+ * this, so how does it do that?
+ */
+static bool
+starjoin_match_to_foreign_key(PlannerInfo *root, RelOptInfo *rel)
+{
+	ListCell   *lc;
+
+	/* Consider each FK constraint that is known to match the query */
+	foreach(lc, root->fkey_list)
+	{
+		ForeignKeyOptInfo *fkinfo = (ForeignKeyOptInfo *) lfirst(lc);
+		int			nmatches = 0;
+
+		/* rel is not the referenced table of the FK */
+		if (fkinfo->ref_relid != rel->relid)
+			continue;
+
+		/*
+		 * Do we have a match for each key of the FK?
+		 *
+		 * XXX get_foreign_key_join_selectivity checks EquivalenceClasses,
+		 * we should probably (definitely) do that here too.
+		 *
+		 * XXX We should check that all the clauses have the same relation
+		 * on the other side (for multi-column keys). And that there are
+		 * no other join clauses other than those matching the FK.
+		 *
+		 * XXX Do we need to check that the FK side of the join (i.e. the fact
+		 * table) has the columns referenced as NOT NULL? Otherwise we could
+		 * have a FK join that reduces the cardinality, which is one of
+		 * the arguments why it's fine to move the join (that it doesn't
+		 * change the cardinality). But if the join is LEFT JOIN, this
+		 * should be fine too - but do we get here with LEFT JOINs?
+		 *
+		 * XXX Do we need to check if the other side of the FK is in the
+		 * current join list? Maybe it's in some later one?
+		 */
+		for (int i = 0; i < fkinfo->nkeys; i++)
+		{
+			bool		has_matching_clause = false;
+
+			/*
+			 * Is there a clause matching this FK key?
+			 *
+			 * XXX We need to make sure it's a valid match, e.g. that the
+			 * same referencing table matches all keys in a composite FK,
+			 * and so on.
+			 *
+			 * XXX Do we need to check some relationship to other rels in
+			 * the same jointree item? E.g. the referencing table should
+			 * not be a dimensions we already removed.
+			 */
+			if ((fkinfo->rinfos[i] != NULL) || (fkinfo->eclass[i] != NULL))
+			{
+				has_matching_clause = true;
+				nmatches++;
+				continue;
+			}
+
+			/* found a FK key without a matching join clause, ignore the FK */
+			if (has_matching_clause)
+				break;
+		}
+
+		/* matched all FK keys */
+		if (nmatches == fkinfo->nkeys)
+		{
+			return true;
+		}
+	}
+
+	return false;
+}
+
+
+/*
+ * starjoin_is_dimension
+ *		Determine if a range table entry is a dimension in a starjoin.
+ *
+ * To be considered a dimension for the simplified join order search, the
+ * join must not affect the cardinality of the join. We ensure that by
+ * requiring a couple things:
+ *
+ * 1) the join clause has to match a FK (that is, the fact does have at
+ *    most one matching row in the dimension)
+ *
+ * 2) the FK side (the fact table) should be marked as NOT NULL, so that
+ *    we know there's exactly one dimension row for each fact table row
+ *
+ * 3) there must be no additional restrictions on the relation (that
+ *    might eliminate some of the rows, reducing the cardinality)
+ *
+ * XXX The Implementation is incomplete. It probably needs more thought,
+ * considering some join types would allow relaxing some of the checks
+ * (e.g. outer joins may not require checking (2) or possibly even (3),
+ * depending on where the condition is, what varnullingrels it has).
+ *
+ * XXX I wonder if we could handle (3) by ordering the dimensions by the
+ * selectivity of the restriction. There are no join clauses between the
+ * dimensions (ignoring the snowflake joins, but even there the clauses
+ * don't go between branches), so the selectivity could be treated as
+ * a measure of how much it shrinks the join result. So we could just
+ * sort the dimensions by this, starting with the lowest selectivity
+ * (close to 0.0), and ending with dimensions without restrictions (in
+ * which case the selectivity is 1.0).
+ *
+ * XXX If the join in INNER, and the fact side has NULL values in the
+ * join key, we might consider nullfrac as restriction.
+ *
+ * XXX I'm not sure how careful this needs to be about join order
+ * restrictions. Maybe it should call have_relevant_joinclause and
+ * have_join_order_restriction, to ensure the join order is OK?
+ *
+ * The optimizer/README is not very clear about this, but maybe it's
+ * a too specific question. It seems to say the relations in those
+ * lists can be joined in any order (lines 94 and 106). Maybe that's
+ * not what it means, or I'm misunderstanding it.
+ *
+ * It however seems has_join_restrictions() in join_search_one_level()
+ * forces the code to look only at "earlier" rels in the list
+ *
+ *     first_rel = foreach_current_index(r) + 1
+ *
+ * So maybe we just need to stop once we find a rel with a restriction,
+ * as determined byhas_join_restrictions()?
+ *
+ * But there's also join_is_legal() to check legality of joins, with
+ * LEFT/RIGHT joins, and IN/EXISTS clauses. See README line 188. And it
+ * also looks-up the SpecialJoinInfo for the join. So maybe we should
+ * lookup RelOptInfo for both sides of the join, and call join_is_legal
+ * on that? Might be too expensive, though. Maybe do that only when
+ * has_join_restrictions already says yes?
+ *
+ * Maybe we should use has_join_restrictions(), but in a  different way.
+ * We could still treat rels with restrictions as dimensions, and move
+ * that to the separate list (that doesn't change the join order), but
+ * stop once we hit the first non-dimension with a restriction? Because
+ * if any relation after that was a dimention, we wouldn't be able to
+ * move it to the separate list. It'd change the join order in a way
+ * that might violate the restriction. I believe that's the idea behind
+ * first_rel in join_search_one_level(), but maybe not.
+ *
+ * Perhaps have_join_order_restriction and have_relevant_joinclause are
+ * useful for this, rather than has_join_restrictions? We might look at
+ * actual pairs of relations, and/or check there's no join order
+ * restriction with respect to the relations we skipped/moved to the
+ * list of dimension?
+ *
+ * AFAICS it's just the skipping that can break the order restrictions?
+ * Adding something to the list of dimensions keeps the order (at least
+ * with respect to the rels after it).
+ */
+static bool
+starjoin_is_dimension(PlannerInfo *root, RangeTblRef *rtr)
+{
+	Index			rti = rtr->rtindex;
+	RangeTblEntry  *rte = root->simple_rte_array[rti];
+	RelOptInfo	   *rel = root->simple_rel_array[rti];
+
+	/* only plain relations can be dimensions (we need FK/PK join) */
+	if ((rte->rtekind != RTE_RELATION) ||
+		(rel->reloptkind != RELOPT_BASEREL))
+		return false;
+
+	/*
+	 * Does it have any conditions/restrictions that may affect the number
+	 * of rows matched? If yes, don't treat as dimension.
+	 *
+	 * Dimensions in a starjoin may have restrictions, but that means it'll
+	 * change cardinality of the joins (reduce it), so it may be better to
+	 * join it early. We leave it to the regular join order planning. The
+	 * expectation is that most dimensions won't have extra restrictions.
+	 *
+	 * XXX Should we check some other fields, like lateral references, and
+	 * so on? Or is that unnecessary? What about eclasses?
+	 */
+	if (rel->baserestrictinfo != NIL)
+		return false;
+
+	/*
+	 * See if the join clause matches a foreign key. It should match a
+	 * single relation on the other side, and the dimension should be on
+	 * the PK side.
+	 *
+	 * XXX loosely inspired by get_foreign_key_join_selectivity()
+	 */
+	if (!starjoin_match_to_foreign_key(root, rel))
+		return false;
+
+	/*
+	 * XXX Maybe some additional checks here ...
+	 */
+
+	return true;
+}
+
+/*
+ * starjoin_adjust_joins
+ *		Adjust the jointree for starjoins, to simplify the join order search.
+ *
+ * Try to simplify the join search problem for starjoin-like joins, with
+ * joins over FK relationships. The dimensions can be joined in almost
+ * any order, which is about the worst case for the standard join order
+ * search, and can be close to factorial complexity. But there's not much
+ * difference between such join orders, so we just leave the dimensions at
+ * the end of each group (as determined by the join_collapse_limit earlier).
+ *
+ * The join search for starjoin queries is surprisingly expensive, because
+ * there are very few join order restrictions. Consider a starjoin query
+ *
+ *  SELECT * FROM f
+ *     JOIN d1 ON (f.id1 = d1.id)
+ *     JOIN d2 ON (f.id2 = d2.id)
+ *     ...
+ *     JOIN d9 ON (f.id9 = d9.id)
+ *
+ * There are no clauses between the dimension tables (d#), which means those
+ * tables can be joined in almost arbitrary order. This means the standard
+ * join_order_search() would explore a N! possible join orders. It is not
+ * that bad in practice, because we split the problem by from_collapse_limit
+ * into a sequence of smaller problems, but even for the default limit of
+ * 8 relations it's quite expensive. This can be easily demonstrated by
+ * setting from_collapse_limit=1 for example starjoin queries.
+ *
+ * The idea here is to apply a much simpler join order search for this type
+ * of queries, without too much risk of picking a much worse plans. It is
+ * however a trade off between how expensive we allow this to be, and how
+ * good the decisions will be. This can help only starjoins with multiple
+ * dimension tables, and we don't want to harm planning of other queries,
+ * so the basic "query shape" detection needs to be very cheap. And then
+ * it needs to be cheaper than the regular join order search.
+ *
+ * If a perfect check is impossible or too expensive, it's better to end
+ * up with a cheap false negative (i.e. and not use the optimization),
+ * rather than risk regressions in other cases.
+ *
+ * The simplified join order search relies on the fact that if the joins
+ * to dimensions do not alter the cardinality of the join relation, then
+ * the relative order of those joins does not matter. All the possible
+ * orders are guaranteed to perform the same. So we can simply pick one
+ * of those orders, and "hardcode" it in the join tree later passed to the
+ * join_order_search().
+ *
+ * The query may involve joins to additional (non-dimension) tables, and
+ * those may alter cardinality. Some joins may increase it, other joins
+ * may decrease it. In principle, it'd be best to first perform all the
+ * joins that reduce join size, then join all the dimensions, and finally
+ * perform joins that may increase the join size. But this is not done
+ * now, currently we simply apply all the dimensions at the end, hoping
+ * that the earlier joins did not inflate the join too much.
+ *
+ * The definition of a dimension is a bit vague. For our definition see
+ * the comment at starjoin_is_dimension().
+ *
+ * The optimization works by manipulating the joinlist (originally built
+ * by deconstruct_jointree), which decomposed the original jointree into
+ * smaller "problems" depending on join type and join_collapse_limit. We
+ * inspect those smaller lists, and selectively split them into smaller
+ * problems to force a join order. This may effectively undo some of the
+ * merging done by deconstruct_jointree(), which tries to build problems
+ * with up to join_collapse_limit relations.
+ *
+ * For example, imagine a join problem with 8 rels - one fact table and
+ * then 7 dimensions, which we can represent a joinlist with 8 elements.
+ *
+ * (D7, D6, D5, D4, D3, D2, D1, F)
+ *
+ * Assuming all those joins meet the requirements (have a matching FK,
+ * don't affect the join cardinality, ...), then we can split this into
+ *
+ * (D7, (D6, (D5, (D4, (D3, (D2, (D1, F)))))))
+ *
+ * which is a nested joinlist, with only two elements on each level. That
+ * means there's no need for expensive join order search, there's only
+ * one way to join the relations (two, if we consider the relations may
+ * switch sides).
+ *
+ * The joinlist may already be nested, with multiple smaller subproblems.
+ * We look at each individual join problem independently, i.e. we don't
+ * try to merge problems to build join_collapse_limit problems again.
+ * This is partially to keep it cheap/simple, but also so not change
+ * behavior for cases when people use join_collapse_limit to force some
+ * particular join shape.
+ *
+ * XXX A possible improvement is to allow handling snowflake joins, i.e.
+ * recursive dimensions. That would require a somewhat more complicated
+ * processing, because a dimension would be allowed other rels, as long
+ * as those are dimensions too. And we'd need to be more careful about
+ * the order in which join them to the top of the join.
+ *
+ * XXX One possible risk is that moving the dimension joins at the very
+ * end may move that after joins that increase the cardinality. Which
+ * may cause a regression. Such joins however don't seem very common, at
+ * least in regular starjoin queries. So maybe we could simply check if
+ * there are any such joins and disable this optimization. Is there a
+ * cheap way to identify that a join increases cardinality?
+ *
+ * XXX Ideally, we'd perform the dimension joins at the place with the
+ * lowest cardinality. Imagine a joinlist
+ *
+ * (D1, D2, A, B, F)
+ *
+ * Where A increases join cardinality, while B does not (possibly even
+ * reduces it). Ideally, we'd do the join like this
+ *
+ * (A, (D2, (D1, (B, F))))
+ *
+ * so D1/D2 get joined at the point of "lowest cardinality". We probably
+ * don't want to do all this cardinality estimation work here, it'd copy
+ * what we already do in the join_order_search(). Perhaps we could invent
+ * a "join item" representing a join to all those dimensions, and pass it
+ * to join_order_search()? And let it pick the right place for it? It'd
+ * always join them in the same order, it'd not reorder them. It would
+ * still do the regular cardinality estimations etc. It would be trivial
+ * to disable the optimization if needed - don't collapse the dimensions
+ * into the new type of join item.
+ */
+List *
+starjoin_adjust_joins(PlannerInfo *root, List *joinlist)
+{
+	ListCell *lc;
+	List *newlist = NIL;
+	List *dimensions = NIL;
+	int		nlist = list_length(joinlist);
+
+	/* Do nothing if starjoin optimization not enabled. */
+	if (!enable_starjoin_join_search)
+		return joinlist;
+
+	/*
+	 * Do nothing if starjoin optimization not applicable.
+	 *
+	 * XXX It might seems we can skip this for lists with <= 2 items, but
+	 * that does not work, the elements may be nested list, and we need to
+	 * descend into those. So do what remove_useless_self_joins() does, and
+	 * only bail out for the simplest single-relation case (i.e. no joins).
+	 */
+	if (joinlist == NIL ||
+		(nlist == 1 && !IsA(linitial(joinlist), List)))
+		return joinlist;
+
+	/*
+	 * Process the current join problem - split the elements into dimensions
+	 * and non-dimensions. If there are dimensions, add them back at the end,
+	 * as small single-rel joins.
+	 *
+	 * The list may contain various types of elements. It may contain a list,
+	 * which means it's an independent join search problem and we need to
+	 * process it recursively. Or it may be RangeTblRef, in which case we
+	 * need to check if it's a dimension. Other types of elements are just
+	 * added back to the list as-is.
+	 *
+	 * XXX I think we need to be careful to keep the order of the list (for
+	 * the non-dimension entries). The join_search_one_level() relies on
+	 * that when handling join order restrictions.
+	 *
+	 * XXX It might be better to only create a new list if needed, i.e. once
+	 * we find the first dimension. So that non-starjoin queries don't pay
+	 * for something they don't need. A mutable iterator might be a way, but
+	 * I'm not sure how expensive this really is.
+	 */
+	foreach (lc, joinlist)
+	{
+		Node *item = (Node *) lfirst(lc);
+
+		/* a separate join search problem, handle it recursively */
+		if (IsA(item, List))
+		{
+			newlist = lappend(newlist,
+							  starjoin_adjust_joins(root, (List *) item));
+			continue;
+		}
+
+		/*
+		 * If it's not a List, it has to be a RangeTblRef - jinlists can't
+		 * contain any other elements (see make_rel_from_joinlist).
+		 */
+		Assert(IsA(item, RangeTblRef));
+
+		/*
+		 * An entry representing a baserel. If it's a dimension, save it in
+		 * a separate list, and we'll add it at the "top" of the join at the
+		 * end. Otherwise add it to the list just like other elements.
+		 *
+		 * We do this only when the joinlist has at least 3 items. For fewer
+		 * rels the optimization does not matter, there's only a single join
+		 * order anyway. That only skips the optimization on this level - we
+		 * still do the recursion, and that might hit a larger join problem.
+		 *
+		 * XXX We might have a new GUC to customize the cutoff limit, but for
+		 * now it seems good enough to do it whenever applicable. If we find
+		 * it's not worth it for less than N rels, we can add it later.
+		 */
+		if ((nlist >= 3) &&
+			starjoin_is_dimension(root, (RangeTblRef *) item))
+		{
+			dimensions = lappend(dimensions, item);
+			continue;
+		}
+
+		/* not a dimension, add it to the list directly */
+		newlist = lappend(newlist, item);
+	}
+
+	/*
+	 * If we found some dimensions, add them to the join tree one by one.
+	 * The exact order does not matter, so we add them in the order we
+	 * found them in the original list.
+	 *
+	 * We need to add them by creating smaller 2-element lists, with the rest
+	 * of the list being a sub-problem and then adding the dimension
+	 * table. This is how we force the desired join order.
+	 */
+	foreach (lc, dimensions)
+	{
+		newlist = list_make2(newlist, lfirst(lc));
+	}
+
+	return newlist;
+}
diff --git a/src/backend/optimizer/plan/planmain.c b/src/backend/optimizer/plan/planmain.c
index eefc486a566..14abbbbd361 100644
--- a/src/backend/optimizer/plan/planmain.c
+++ b/src/backend/optimizer/plan/planmain.c
@@ -291,6 +291,13 @@ query_planner(PlannerInfo *root,
 	 */
 	distribute_row_identity_vars(root);
 
+	/*
+	 * Try to simplify the join search problem for starjoin-like joins.
+	 * This step relies on info about FK relationships, so we can't do it
+	 * till after match_foreign_keys_to_quals().
+	 */
+	joinlist = starjoin_adjust_joins(root, joinlist);
+
 	/*
 	 * Ready to do the primary planning.
 	 */
diff --git a/src/backend/utils/misc/guc_parameters.dat b/src/backend/utils/misc/guc_parameters.dat
index 1128167c025..510241e75be 100644
--- a/src/backend/utils/misc/guc_parameters.dat
+++ b/src/backend/utils/misc/guc_parameters.dat
@@ -968,6 +968,13 @@
   boot_val => 'true',
 },
 
+{ name => 'enable_starjoin_join_search', type => 'bool', context => 'PGC_USERSET', group => 'QUERY_TUNING_METHOD',
+  short_desc => 'Enables simplified join order planning for starjoins.',
+  flags => 'GUC_EXPLAIN',
+  variable => 'enable_starjoin_join_search',
+  boot_val => 'false',
+},
+
 { name => 'enable_tidscan', type => 'bool', context => 'PGC_USERSET', group => 'QUERY_TUNING_METHOD',
   short_desc => 'Enables the planner\'s use of TID scan plans.',
   flags => 'GUC_EXPLAIN',
diff --git a/src/backend/utils/misc/postgresql.conf.sample b/src/backend/utils/misc/postgresql.conf.sample
index f62b61967ef..4e5542f690c 100644
--- a/src/backend/utils/misc/postgresql.conf.sample
+++ b/src/backend/utils/misc/postgresql.conf.sample
@@ -424,6 +424,7 @@
 #enable_presorted_aggregate = on
 #enable_seqscan = on
 #enable_sort = on
+enable_starjoin_join_search = off
 #enable_tidscan = on
 #enable_group_by_reordering = on
 #enable_distinct_reordering = on
diff --git a/src/include/optimizer/planmain.h b/src/include/optimizer/planmain.h
index 00addf15992..c30ac3a5754 100644
--- a/src/include/optimizer/planmain.h
+++ b/src/include/optimizer/planmain.h
@@ -21,6 +21,7 @@
 #define DEFAULT_CURSOR_TUPLE_FRACTION 0.1
 extern PGDLLIMPORT double cursor_tuple_fraction;
 extern PGDLLIMPORT bool enable_self_join_elimination;
+extern PGDLLIMPORT bool enable_starjoin_join_search;
 
 /* query_planner callback to compute query_pathkeys */
 typedef void (*query_pathkeys_callback) (PlannerInfo *root, void *extra);
@@ -120,6 +121,7 @@ extern bool innerrel_is_unique_ext(PlannerInfo *root, Relids joinrelids,
 								   JoinType jointype, List *restrictlist,
 								   bool force_cache, List **extra_clauses);
 extern List *remove_useless_self_joins(PlannerInfo *root, List *joinlist);
+extern List *starjoin_adjust_joins(PlannerInfo *root, List *joinlist);
 
 /*
  * prototypes for plan/setrefs.c
diff --git a/src/test/regress/expected/sysviews.out b/src/test/regress/expected/sysviews.out
index 3b37fafa65b..0c3b1eeaba7 100644
--- a/src/test/regress/expected/sysviews.out
+++ b/src/test/regress/expected/sysviews.out
@@ -172,8 +172,9 @@ select name, setting from pg_settings where name like 'enable%';
  enable_self_join_elimination   | on
  enable_seqscan                 | on
  enable_sort                    | on
+ enable_starjoin_join_search    | off
  enable_tidscan                 | on
-(25 rows)
+(26 rows)
 
 -- There are always wait event descriptions for various types.  InjectionPoint
 -- may be present or absent, depending on history since last postmaster start.
-- 
2.51.1

#31Tom Lane
tgl@sss.pgh.pa.us
In reply to: Tomas Vondra (#30)
Re: should we have a fast-path planning for OLTP starjoins?

[ Don't have time to read the v4 patch right now, but a couple
of quick responses: ]

Tomas Vondra <tomas@vondra.me> writes:

On 9/23/25 21:46, Tom Lane wrote:

I'd be slightly inclined to put the GUC test there, too:

+	if (enable_starjoin_join_search)
+		joinlist = starjoin_adjust_joins(root, joinlist);

I'm not sure I like this very mcuh. No other call in query_planner()
does it like that. Most don't have such GUC, but at least
remove_useless_self_joins does, and it still doesn't check it here.

Fair enough, it was just a suggestion.

When thinking about this, I realized the has_join_restriction() is only
ever used in join_search_one_level(), i.e. when dealing with each small
join order problem. Doesn't this mean the deconstructed jointree must
already consider the restrictions in some way? I don't see any explicit
mentions of such join order restrictions in deconstruct_recurse. It must
not violate any ordering restrictions by splitting the joins in a
"wrong" way, right? If I set join_collapse_limit=1 it still needs to
satisfy all the rules.

Performing outer joins in syntactic order is always OK by definition,
and setting join_collapse_limit to 1 just forces that to happen.
So I guess you could say that the original jointree "considers the
restrictions", and it's only after we flatten an outer join's two
sides into a joinlist (along with other rels) that we have to worry.
Or is that not what you meant?

regards, tom lane

#32Tomas Vondra
tomas@vondra.me
In reply to: Tom Lane (#31)
Re: should we have a fast-path planning for OLTP starjoins?

On 11/8/25 21:36, Tom Lane wrote:

[ Don't have time to read the v4 patch right now, but a couple
of quick responses: ]

Tomas Vondra <tomas@vondra.me> writes:

On 9/23/25 21:46, Tom Lane wrote:

I'd be slightly inclined to put the GUC test there, too:

+	if (enable_starjoin_join_search)
+		joinlist = starjoin_adjust_joins(root, joinlist);

I'm not sure I like this very mcuh. No other call in query_planner()
does it like that. Most don't have such GUC, but at least
remove_useless_self_joins does, and it still doesn't check it here.

Fair enough, it was just a suggestion.

When thinking about this, I realized the has_join_restriction() is only
ever used in join_search_one_level(), i.e. when dealing with each small
join order problem. Doesn't this mean the deconstructed jointree must
already consider the restrictions in some way? I don't see any explicit
mentions of such join order restrictions in deconstruct_recurse. It must
not violate any ordering restrictions by splitting the joins in a
"wrong" way, right? If I set join_collapse_limit=1 it still needs to
satisfy all the rules.

Performing outer joins in syntactic order is always OK by definition,
and setting join_collapse_limit to 1 just forces that to happen.
So I guess you could say that the original jointree "considers the
restrictions", and it's only after we flatten an outer join's two
sides into a joinlist (along with other rels) that we have to worry.
Or is that not what you meant?

I'm not sure, but I wasn't talking just about outer joins.

AFAICS even queries with inner joins will get the jointree deconstructed
like this. Consider the query from select-1.sql:

select * from t
join dim1 on (dim1.id = id1)
join dim2 on (dim2.id = id2)
join dim3 on (dim3.id = id3)
join dim4 on (dim4.id = id4)
join dim5 on (dim5.id = id5)
join dim6 on (dim6.id = id6)
join dim7 on (dim7.id = id7);

If I set join_collapse_limit=1, then standard_join_search() only sees
problems of size 2, i.e. (list_length(initial_rels) == 2). And we only
look at has_join_restriction() *inside* these small problems, i.e. the
jointree must not be deconstructed in a way that would violate this.

Doesn't that mean deconstruct_jointree() has to somehow "consider" the
join restrictions (even if not explicitly). It that's the case, could we
maybe leverage that, eliminating the need to call has_join_restriction?

It's just a hunch, though. Maybe splitting the jointree like this is
always legal, because deconstruct_jointree() does not try to "reorder"
the elements.

regards

--
Tomas Vondra

#33Tom Lane
tgl@sss.pgh.pa.us
In reply to: Tomas Vondra (#32)
Re: should we have a fast-path planning for OLTP starjoins?

Tomas Vondra <tomas@vondra.me> writes:

If I set join_collapse_limit=1, then standard_join_search() only sees
problems of size 2, i.e. (list_length(initial_rels) == 2). And we only
look at has_join_restriction() *inside* these small problems, i.e. the
jointree must not be deconstructed in a way that would violate this.

Doesn't that mean deconstruct_jointree() has to somehow "consider" the
join restrictions (even if not explicitly).

It mustn't build subproblems that don't have any legal solutions, sure.
But that is automatic given that it only folds up within the syntactic
structure --- it doesn't go combining rels from random places within
the jointree.

It that's the case, could we
maybe leverage that, eliminating the need to call has_join_restriction?

Don't see how. Once we've folded an outer join into an upper
subproblem, some but (usually) not all of the join orders within that
subproblem will be legal.

It might be that we could make has_join_restriction and friends
faster/simpler with some other representation of the join tree.
I've not really thought hard about alternatives.

regards, tom lane

#34Tomas Vondra
tomas@vondra.me
In reply to: Tom Lane (#33)
Re: should we have a fast-path planning for OLTP starjoins?

On 11/9/25 19:42, Tom Lane wrote:

Tomas Vondra <tomas@vondra.me> writes:

If I set join_collapse_limit=1, then standard_join_search() only sees
problems of size 2, i.e. (list_length(initial_rels) == 2). And we only
look at has_join_restriction() *inside* these small problems, i.e. the
jointree must not be deconstructed in a way that would violate this.

Doesn't that mean deconstruct_jointree() has to somehow "consider" the
join restrictions (even if not explicitly).

It mustn't build subproblems that don't have any legal solutions, sure.
But that is automatic given that it only folds up within the syntactic
structure --- it doesn't go combining rels from random places within
the jointree.

Ah, I see. I didn't realize it's driven purely by the syntactic
structure, I got convinced it's aware of more stuff. But yeah, this
means it can't help the patch.

It that's the case, could we
maybe leverage that, eliminating the need to call has_join_restriction?

Don't see how. Once we've folded an outer join into an upper
subproblem, some but (usually) not all of the join orders within that
subproblem will be legal.

It might be that we could make has_join_restriction and friends
faster/simpler with some other representation of the join tree.
I've not really thought hard about alternatives.

No idea. I'm not familiar enough with this to have good ideas on how to
rework it, and I assume has_join_restriction will be cheap enough for
this patch.

regards

--
Tomas Vondra

#35Tomas Vondra
tomas@vondra.me
In reply to: Tomas Vondra (#34)
2 attachment(s)
Re: should we have a fast-path planning for OLTP starjoins?

Hi,

Here's a v5, addressing some (but not all) of the things discussed
earlier in this thread.

This does nothing about the "opposite" type of join, with many small
tables linking to a single "central" table. I'm not convinced it makes
sense to handle that together with starjoins. But I haven't tried yet.

The main improvements/changes in v5 are:

1) comment cleanup / clarification
----------------------------------
A lot of comments was stale, or open questions answered since the
comment was written. So clean that up. Rewording and clarification of
various comments - a lot of places talking about the same thing, so I
de-duplicated that (I hope).

2) starjoin_match_to_foreign_key: improved matching FK to join clauses
----------------------------------------------------------------------
The check is split into starjoin_foreign_key_matched_by_clauses and
starjoin_clauses_matched_by_foreign_key, each doing the check in one
direction. It might be possible to do both in a single function, but I
don't think it'd be more efficient and this seemed simpler.

I was a bit surprised it doesn't need to inspect the EC members, it's
enough to check if the FK matches the EC. At least I don't think it's
needed, and it seems to be working without it. Maybe there's some more
complex case where we actually need to look at the members?

The one remaining XXX is about ensuring the referencing table has the FK
columns marked as NOT NULL, to guarantee the join does not reduce
cardinality. But it's related to the question of OUTER joins, which is
discussed later.

3) has_join_restriction(), but allowing some join order restrictions
--------------------------------------------------------------------
starjoin_is_dimension() now calls has_join_restriction(), and for inner
joins this works fine. But as soon as there's an outer join (say, left
join), it disabled the simplified planning. I find that unfortunate, but
I think we can actually do better - IIUC it's OK to treat a relation
with join restrictions as a dimension, as long as we don't reorder
relations with restrictions (the sublist).

Consider a join list with 8 baserels, and an empty list of dimensions.

[F, E1, D2, E3, D4, E5, D6, E7] []

The "F" is the fact, "D" are dimensions, "E" are non-dimension tables.
We can simply move the "D" rels to the dimension list:

[F, E1, E3, E5, E7] [D2, D4, D6]

The v4 patch would have stopped here, but I think we can do better - we
can move the "E" rels to the dimension list, as long as the only reason
preventing that was "has_join_restriction". We move the rels to the
beginning of the dimensions list, to keep the syntactic join order. And
we stop once we find the first rel that can't be moved (due to not
having a matching FK or has WHERE filter).

starjoin_adjust_joins does that by walking the filter repeatedly, and
stopping when it finds no dimension. I now realize it won't actually
need more than two loops (and one to find nothing) but that's a detail.

This is related to the NOT NULL vs. outer join check mentioned in (2),
because the restrictions are usually due to outer joins, and outer joins
don't need the check (and probably even can't have that). But I'm not
sure what's the best way to check if the order restriction is due to
some kind of outer join, or something else. Not sure.

I kept this separated in 0002, for easier review.

snowflake joins
---------------
There's another possible improvement that I'd like to address in the
next version of the patch - handling snowflake schemas. Right now the
leaf dimensions will be handled fine, but the "inner" dimensions won't
because they reference other tables (the leafs). Which gets rejected by
starjoin_clauses_matched_by_foreign_key, because those join clauses are
not matched by the incoming FK.

I plan to modify starjoin_is_dimension() to allow join clauses pointing
to "known" dimensions, so that the next loop can add the "inner" ones.

some experiments
----------------
To verify if this is effective, I ran the two starjoin and snowflake
selects (select-1 and select-3) with inner/outer joins, on master and
with 0001 and 0002. There's a "run.sh" script in "patch/" directory.

The results look like this:

| master | 0001/off 0001/on | 0002/off 0002/on
------------------|---------|-------------------|------------------
starjoin inner | 2299 | 2295 15325 | 2299 15131
starjoin outer | 2270 | 2272 2257 | 2249 14312
snowflake inner | 2718 | 2667 7223 | 2654 7106
snowflake outer | 2282 | 2264 2254 | 2273 6210

This is throughput (tps) from a single pgbench run with a single client.
It's quite stable, but there's a bit of noise.

The master and "off" results are virtually the same (and it gives you a
good idea of how much noise is there). 0001 helps with inner joins, but
not the outer joins (because of the restrictions). 0002 fixes that.

The improvement for snowflake joins is smaller because of the "inner"
dimensions. The current patches identify only the leaf ones.

regards

--
Tomas Vondra

Attachments:

v5-0002-Allow-dimensions-with-some-join-restrictions.patchtext/x-patch; charset=UTF-8; name=v5-0002-Allow-dimensions-with-some-join-restrictions.patchDownload
From 41273bc5db9785ba88038c15b762a1ffd367b762 Mon Sep 17 00:00:00 2001
From: Tomas Vondra <tomas@vondra.me>
Date: Tue, 11 Nov 2025 23:12:39 +0100
Subject: [PATCH v5 2/2] Allow dimensions with some join restrictions

---
 src/backend/optimizer/plan/analyzejoins.c | 154 +++++++++++++++++-----
 1 file changed, 119 insertions(+), 35 deletions(-)

diff --git a/src/backend/optimizer/plan/analyzejoins.c b/src/backend/optimizer/plan/analyzejoins.c
index 79a7f0c8608..bc19c2b537c 100644
--- a/src/backend/optimizer/plan/analyzejoins.c
+++ b/src/backend/optimizer/plan/analyzejoins.c
@@ -2782,7 +2782,8 @@ starjoin_match_to_foreign_key(PlannerInfo *root, RelOptInfo *rel)
  * with respect to the rels after it).
  */
 static bool
-starjoin_is_dimension(PlannerInfo *root, RangeTblRef *rtr)
+starjoin_is_dimension(PlannerInfo *root, RangeTblRef *rtr,
+					  bool allow_restrictions)
 {
 	Index		rti = rtr->rtindex;
 	RangeTblEntry *rte = root->simple_rte_array[rti];
@@ -2815,7 +2816,7 @@ starjoin_is_dimension(PlannerInfo *root, RangeTblRef *rtr)
 	 * XXX This blocks the simplified planning for LEFT (or OUTER) joins,
 	 * because outer joins imply restrictions.
 	 */
-	if (has_join_restriction(root, rel))
+	if (!allow_restrictions && has_join_restriction(root, rel))
 		return false;
 
 	/*
@@ -2953,6 +2954,28 @@ starjoin_is_dimension(PlannerInfo *root, RangeTblRef *rtr)
  * to disable the optimization if needed, I think - don't collapse the
  * dimensions into the "group" join item. It would require changes to
  * the generic join search, to be aware of the new item type.
+ *
+ * The search for dimensions may perform multiple passes over the list, to
+ * allow treating some rels with restrictions as dimensions. Relations
+ * without restrictions can be moved to an arbitrary place in the join
+ * tree. We leverage that by moving it to the list of dimensions, which
+ * may skip over various other relations.
+ *
+ * Relations with join order do not allow these arbitrary moves. But we can
+ * allow treating them dimensions in some cases. A join restriction does not
+ * imply we can't move the relation at all, otherwise we wouldn't be allowed
+ * to move any relations when there's a single relation with a restriction.
+ * It means we can't change the relative order of restricted relations.
+ *
+ * This means we can treat a relation with a restriction as a dimension,
+ * as long as it's the last in the current joinlist (after some relations
+ * were already moved to list of dimensions).
+ *
+ * To do this we walk the joinlist multiple times, and in each iteration
+ * we try to identify as many dimensions as possible. We walk the list in
+ * reverse, and we add dimensions to the beginning of the list. This way
+ * we preserve the original syntactic join order. If we find no dimensions
+ * in a loop, we're done.
  */
 List *
 starjoin_adjust_joins(PlannerInfo *root, List *joinlist)
@@ -2961,6 +2984,8 @@ starjoin_adjust_joins(PlannerInfo *root, List *joinlist)
 	List	   *newlist = NIL;
 	List	   *dimensions = NIL;
 	int			nlist = list_length(joinlist);
+	int			nitems;
+	Node	  **items;
 
 	/* Do nothing if starjoin optimization not enabled. */
 	if (!enable_starjoin_join_search)
@@ -2978,6 +3003,15 @@ starjoin_adjust_joins(PlannerInfo *root, List *joinlist)
 		(nlist == 1 && !IsA(linitial(joinlist), List)))
 		return joinlist;
 
+	/* expand the list into an array, to make backwards processing easier */
+	items = palloc_array(Node *, nlist);
+
+	nitems = 0;
+	foreach(lc, joinlist)
+	{
+		items[nitems++] = (Node *) lfirst(lc);
+	}
+
 	/*
 	 * Process the current join problem - split the elements into dimensions
 	 * and non-dimensions. If there are dimensions, add them back at the end,
@@ -2989,6 +3023,9 @@ starjoin_adjust_joins(PlannerInfo *root, List *joinlist)
 	 * to check if it's a dimension. Other types of elements are just added
 	 * back to the list as-is.
 	 *
+	 * Walk the list backwards, to preserve syntactic join order. This allows
+	 * tracking "last" relation. If we find no dimension, we're done.
+	 *
 	 * XXX I think we need to be careful to keep the order of the list (for
 	 * the non-dimension entries). The join_search_one_level() relies on that
 	 * when handling join order restrictions.
@@ -2998,47 +3035,94 @@ starjoin_adjust_joins(PlannerInfo *root, List *joinlist)
 	 * something they don't need. A mutable iterator might be a way, but I'm
 	 * not sure how expensive this really is.
 	 */
-	foreach(lc, joinlist)
+	for (;;)
 	{
-		Node	   *item = (Node *) lfirst(lc);
+		bool		found = false;	/* found at least one dimension */
+		bool		last = true;	/* is this the current last rel */
 
-		/* a separate join search problem, handle it recursively */
-		if (IsA(item, List))
+		for (int i = (nitems - 1); i >= 0; i--)
 		{
-			newlist = lappend(newlist,
-							  starjoin_adjust_joins(root, (List *) item));
-			continue;
+			Node	   *item = items[i];
+
+			/* skip empty items (already moved to dimensions) */
+			if (item == NULL)
+				continue;
+
+			/* do nothing about join subproblems, leave them in place */
+			if (IsA(item, List))
+			{
+				/* XXX do we need to disable "false" for join subtree? */
+				last = false;
+				continue;
+			}
+
+			/*
+			 * If it's not a List, it has to be a RangeTblRef - jinlists can't
+			 * contain any other elements (see make_rel_from_joinlist).
+			 */
+			Assert(IsA(item, RangeTblRef));
+
+			/*
+			 * Is it a dimension?
+			 *
+			 * An entry representing a baserel. If it's a dimension, save it
+			 * in a separate list, and we'll add it at the "top" of the join
+			 * at the end. Otherwise add it to the list just like other
+			 * elements.
+			 *
+			 * We do this only when the joinlist has at least 3 items. For
+			 * fewer rels the optimization does not matter, there's only a
+			 * single join order anyway. That only skips the optimization on
+			 * this level - we still do the recursion, and that might hit a
+			 * larger join problem.
+			 *
+			 * XXX If we decide to treat the rel as a dimension, don't update
+			 * the "last" flag. The next relation will be the last one.
+			 *
+			 * XXX We might have a new GUC to customize the cutoff limit, but
+			 * for now it seems good enough to do it whenever applicable. If
+			 * we find it's not worth it for less than N rels, we can add it
+			 * later.
+			 */
+			if ((nlist >= 3) &&
+				starjoin_is_dimension(root, (RangeTblRef *) item, last))
+			{
+				/* add it to the beginning of the list */
+				dimensions = lcons(item, dimensions);
+				items[i] = NULL;
+				found = true;
+				continue;
+			}
+
+			/*
+			 * Not a dimension. Leave it in the array, but remember the next
+			 * item (backwards) is no longer the last one.
+			 *
+			 * XXX Maybe we don't need to reset "last" if the item does not
+			 * have join restrictions?
+			 */
+			last = false;
 		}
 
-		/*
-		 * If it's not a List, it has to be a RangeTblRef - jinlists can't
-		 * contain any other elements (see make_rel_from_joinlist).
-		 */
-		Assert(IsA(item, RangeTblRef));
+		/* terminate when a loop finds no dimension */
+		if (!found)
+			break;
+	}
 
-		/*
-		 * An entry representing a baserel. If it's a dimension, save it in a
-		 * separate list, and we'll add it at the "top" of the join at the
-		 * end. Otherwise add it to the list just like other elements.
-		 *
-		 * We do this only when the joinlist has at least 3 items. For fewer
-		 * rels the optimization does not matter, there's only a single join
-		 * order anyway. That only skips the optimization on this level - we
-		 * still do the recursion, and that might hit a larger join problem.
-		 *
-		 * XXX We might have a new GUC to customize the cutoff limit, but for
-		 * now it seems good enough to do it whenever applicable. If we find
-		 * it's not worth it for less than N rels, we can add it later.
-		 */
-		if ((nlist >= 3) &&
-			starjoin_is_dimension(root, (RangeTblRef *) item))
-		{
-			dimensions = lappend(dimensions, item);
+	/*
+	 * Add items remaining in the input array to the newlist. We need to do
+	 * this every time, even without dimensions, because we need to recurse to
+	 * the nested join problems.
+	 */
+	for (int i = 0; i < nitems; i++)
+	{
+		if (items[i] == NULL)
 			continue;
-		}
 
-		/* not a dimension, add it to the list directly */
-		newlist = lappend(newlist, item);
+		if (IsA(items[i], List))
+			items[i] = (Node *) starjoin_adjust_joins(root, (List *) items[i]);
+
+		newlist = lappend(newlist, items[i]);
 	}
 
 	/*
-- 
2.51.1

v5-0001-Simplify-planning-of-starjoin-queries.patchtext/x-patch; charset=UTF-8; name=v5-0001-Simplify-planning-of-starjoin-queries.patchDownload
From 162d2e9d876304e9cffa9a0fd73cfea33ca74819 Mon Sep 17 00:00:00 2001
From: Tomas Vondra <tomas@vondra.me>
Date: Sat, 8 Nov 2025 18:16:30 +0100
Subject: [PATCH v5 1/2] Simplify planning of starjoin queries

---
 patch/create-1.sql                            |  18 +
 patch/create-2.sql                            |  11 +
 patch/create-3.sql                            |  32 +
 patch/run.sh                                  |  23 +
 patch/select-1-inner.sql                      |  10 +
 patch/select-1-outer.sql                      |  10 +
 patch/select-2.sql                            |   9 +
 patch/select-3-inner.sql                      |  15 +
 patch/select-3-outer.sql                      |  15 +
 src/backend/optimizer/path/joinrels.c         |   3 +-
 src/backend/optimizer/plan/analyzejoins.c     | 546 ++++++++++++++++++
 src/backend/optimizer/plan/planmain.c         |   7 +
 src/backend/utils/misc/guc_parameters.dat     |   7 +
 src/backend/utils/misc/postgresql.conf.sample |   1 +
 src/include/optimizer/paths.h                 |   1 +
 src/include/optimizer/planmain.h              |   2 +
 src/test/regress/expected/sysviews.out        |   3 +-
 17 files changed, 710 insertions(+), 3 deletions(-)
 create mode 100644 patch/create-1.sql
 create mode 100644 patch/create-2.sql
 create mode 100644 patch/create-3.sql
 create mode 100644 patch/run.sh
 create mode 100644 patch/select-1-inner.sql
 create mode 100644 patch/select-1-outer.sql
 create mode 100644 patch/select-2.sql
 create mode 100644 patch/select-3-inner.sql
 create mode 100644 patch/select-3-outer.sql

diff --git a/patch/create-1.sql b/patch/create-1.sql
new file mode 100644
index 00000000000..8df04fd0677
--- /dev/null
+++ b/patch/create-1.sql
@@ -0,0 +1,18 @@
+create table dim1 (id int primary key, val1 text);
+create table dim2 (id int primary key, val2 text);
+create table dim3 (id int primary key, val3 text);
+create table dim4 (id int primary key, val4 text);
+create table dim5 (id int primary key, val5 text);
+create table dim6 (id int primary key, val6 text);
+create table dim7 (id int primary key, val7 text);
+
+create table t (id serial primary key,
+                id1 int references dim1(id),
+                id2 int references dim2(id),
+                id3 int references dim3(id),
+                id4 int references dim4(id),
+                id5 int references dim5(id),
+                id6 int references dim6(id),
+                id7 int references dim7(id));
+
+vacuum analyze;
diff --git a/patch/create-2.sql b/patch/create-2.sql
new file mode 100644
index 00000000000..cdf612dde8f
--- /dev/null
+++ b/patch/create-2.sql
@@ -0,0 +1,11 @@
+create table t (id serial primary key, a text);
+
+create table dim1 (id1 int primary key references t(id), val1 text);
+create table dim2 (id2 int primary key references t(id), val2 text);
+create table dim3 (id3 int primary key references t(id), val3 text);
+create table dim4 (id4 int primary key references t(id), val4 text);
+create table dim5 (id5 int primary key references t(id), val5 text);
+create table dim6 (id6 int primary key references t(id), val6 text);
+create table dim7 (id7 int primary key references t(id), val7 text);
+
+vacuum analyze;
diff --git a/patch/create-3.sql b/patch/create-3.sql
new file mode 100644
index 00000000000..bd086c137ce
--- /dev/null
+++ b/patch/create-3.sql
@@ -0,0 +1,32 @@
+create table dim1_1 (id int primary key, val2 text);
+create table dim1_2 (id int primary key, val3 text);
+create table dim1 (id int primary key,
+                   id1_1 int references dim1_1(id),
+                   id1_2 int references dim1_2(id),
+                   val1 text);
+create table dim2_1 (id int primary key, val5 text);
+create table dim2_2 (id int primary key, val6 text);
+create table dim2 (id int primary key,
+                   id2_1 int references dim2_1(id),
+                   id2_2 int references dim2_2(id),
+                   val4 text);
+create table dim3_1 (id int primary key, val5 text);
+create table dim3_2 (id int primary key, val6 text);
+create table dim3 (id int primary key,
+                   id3_1 int references dim3_1(id),
+                   id3_2 int references dim3_2(id),
+                   val4 text);
+create table dim4_1 (id int primary key, val5 text);
+create table dim4_2 (id int primary key, val6 text);
+create table dim4 (id int primary key,
+                   id4_1 int references dim4_1(id),
+                   id4_2 int references dim4_2(id),
+                   val4 text);
+
+create table t (id serial primary key,
+                id1 int references dim1(id),
+                id2 int references dim2(id),
+                id3 int references dim3(id),
+                id4 int references dim4(id));
+
+vacuum analyze;
diff --git a/patch/run.sh b/patch/run.sh
new file mode 100644
index 00000000000..c67cd848a4a
--- /dev/null
+++ b/patch/run.sh
@@ -0,0 +1,23 @@
+#!/usr/bin/env bash
+
+for t in 1 3; do
+
+	dropdb --if-exists test
+	createdb test
+	psql test < create-$t.sql > /dev/null 2>&1
+
+	for m in inner outer; do
+
+		for o in off on; do
+
+			sed "s/OPT/$o/" select-$t$m.sql > script.sql
+
+			tps=$(pgbench -n -f script.sql -T 10 test | grep 'tps = ' | awk '{print $3}')
+
+			echo $t $m $o $tps
+
+		done
+
+	done
+
+done
diff --git a/patch/select-1-inner.sql b/patch/select-1-inner.sql
new file mode 100644
index 00000000000..d3bd477eea3
--- /dev/null
+++ b/patch/select-1-inner.sql
@@ -0,0 +1,10 @@
+--set join_collapse_limit = 1;
+set enable_starjoin_join_search = OPT;
+select * from t
+    join dim1 on (dim1.id = id1)
+    join dim2 on (dim2.id = id2)
+    join dim3 on (dim3.id = id3)
+    join dim4 on (dim4.id = id4)
+    join dim5 on (dim5.id = id5)
+    join dim6 on (dim6.id = id6)
+    join dim7 on (dim7.id = id7);
diff --git a/patch/select-1-outer.sql b/patch/select-1-outer.sql
new file mode 100644
index 00000000000..249cde4b768
--- /dev/null
+++ b/patch/select-1-outer.sql
@@ -0,0 +1,10 @@
+--set join_collapse_limit = 1;
+set enable_starjoin_join_search = OPT;
+select * from t
+    left join dim1 on (dim1.id = id1)
+    left join dim2 on (dim2.id = id2)
+    left join dim3 on (dim3.id = id3)
+    left join dim4 on (dim4.id = id4)
+    left join dim5 on (dim5.id = id5)
+    left join dim6 on (dim6.id = id6)
+    left join dim7 on (dim7.id = id7);
diff --git a/patch/select-2.sql b/patch/select-2.sql
new file mode 100644
index 00000000000..4e1d2a7b0e7
--- /dev/null
+++ b/patch/select-2.sql
@@ -0,0 +1,9 @@
+-- set join_collapse_limit = 1;
+select * from t
+    left join dim1 on (id = id1)
+    left join dim2 on (id = id2)
+    left join dim3 on (id = id3)
+    left join dim4 on (id = id4)
+    left join dim5 on (id = id5)
+    left join dim6 on (id = id6)
+    left join dim7 on (id = id7);
diff --git a/patch/select-3-inner.sql b/patch/select-3-inner.sql
new file mode 100644
index 00000000000..f661c0c2fb5
--- /dev/null
+++ b/patch/select-3-inner.sql
@@ -0,0 +1,15 @@
+--set join_collapse_limit = 1;
+set enable_starjoin_join_search = OPT;
+select * from t
+    join dim1 on (dim1.id = id1)
+    join dim2 on (dim2.id = id2)
+    join dim3 on (dim3.id = id3)
+    join dim4 on (dim4.id = id4)
+    join dim1_1 on (id1_1 = dim1_1.id)
+    join dim1_2 on (id1_2 = dim1_2.id)
+    join dim2_1 on (id2_1 = dim2_1.id)
+    join dim2_2 on (id2_2 = dim2_2.id)
+    join dim3_1 on (id3_1 = dim3_1.id)
+    join dim3_2 on (id3_2 = dim3_2.id)
+    join dim4_1 on (id4_1 = dim4_1.id)
+    join dim4_2 on (id4_2 = dim4_2.id);
diff --git a/patch/select-3-outer.sql b/patch/select-3-outer.sql
new file mode 100644
index 00000000000..5ca549f02ac
--- /dev/null
+++ b/patch/select-3-outer.sql
@@ -0,0 +1,15 @@
+--set join_collapse_limit = 1;
+set enable_starjoin_join_search = OPT;
+select * from t
+    left join dim1 on (dim1.id = id1)
+    left join dim2 on (dim2.id = id2)
+    left join dim3 on (dim3.id = id3)
+    left join dim4 on (dim4.id = id4)
+    left join dim1_1 on (id1_1 = dim1_1.id)
+    left join dim1_2 on (id1_2 = dim1_2.id)
+    left join dim2_1 on (id2_1 = dim2_1.id)
+    left join dim2_2 on (id2_2 = dim2_2.id)
+    left join dim3_1 on (id3_1 = dim3_1.id)
+    left join dim3_2 on (id3_2 = dim3_2.id)
+    left join dim4_1 on (id4_1 = dim4_1.id)
+    left join dim4_2 on (id4_2 = dim4_2.id);
diff --git a/src/backend/optimizer/path/joinrels.c b/src/backend/optimizer/path/joinrels.c
index 5d1fc3899da..17332350da5 100644
--- a/src/backend/optimizer/path/joinrels.c
+++ b/src/backend/optimizer/path/joinrels.c
@@ -32,7 +32,6 @@ static void make_rels_by_clause_joins(PlannerInfo *root,
 static void make_rels_by_clauseless_joins(PlannerInfo *root,
 										  RelOptInfo *old_rel,
 										  List *other_rels);
-static bool has_join_restriction(PlannerInfo *root, RelOptInfo *rel);
 static bool has_legal_joinclause(PlannerInfo *root, RelOptInfo *rel);
 static bool restriction_is_constant_false(List *restrictlist,
 										  RelOptInfo *joinrel,
@@ -1363,7 +1362,7 @@ have_join_order_restriction(PlannerInfo *root,
  * say "true" incorrectly.  (Therefore, we don't bother with the relatively
  * expensive has_legal_joinclause test.)
  */
-static bool
+bool
 has_join_restriction(PlannerInfo *root, RelOptInfo *rel)
 {
 	ListCell   *l;
diff --git a/src/backend/optimizer/plan/analyzejoins.c b/src/backend/optimizer/plan/analyzejoins.c
index e592e1ac3d1..79a7f0c8608 100644
--- a/src/backend/optimizer/plan/analyzejoins.c
+++ b/src/backend/optimizer/plan/analyzejoins.c
@@ -51,6 +51,7 @@ typedef struct
 } SelfJoinCandidate;
 
 bool		enable_self_join_elimination;
+bool		enable_starjoin_join_search;
 
 /* local functions */
 static bool join_is_removable(PlannerInfo *root, SpecialJoinInfo *sjinfo);
@@ -2511,3 +2512,548 @@ remove_useless_self_joins(PlannerInfo *root, List *joinlist)
 
 	return joinlist;
 }
+
+/*
+ * starjoin_foreign_key_matched_by_clauses
+ *		Determines if the foreign key is matched by join clauses.
+ *
+ * Each foreign key attribute must be matched by a join clause. Either by
+ * a simple RestrictInfo, or by an equivalence class (if the relation has
+ * eclass joins).
+ *
+ * Returns true if the foreign key is matched, false otherwise.
+ *
+ * XXX Do we need to check that the FK side of the join (i.e. the fact table)
+ * has the columns referenced as NOT NULL? Otherwise we could have a FK join
+ * that reduces the cardinality, which is one of the arguments why it's fine
+ * to move the join (that it doesn't change the cardinality). But if the join
+ * is LEFT JOIN, this should be fine too - but do we get here with LEFT JOINs?
+ */
+static bool
+starjoin_foreign_key_matched_by_clauses(PlannerInfo *root, RelOptInfo *rel,
+										ForeignKeyOptInfo *fkinfo)
+{
+	/* make sure each FK attribute has at least one matching clause */
+	for (int i = 0; i < fkinfo->nkeys; i++)
+	{
+		/* matching rinfo clause or equivalance class */
+		if ((fkinfo->rinfos[i] != NULL) || (fkinfo->eclass[i] != NULL))
+		{
+			/*
+			 * XXX Do we need to inspect the rinfo/eclass further? I don't
+			 * think that's really necessary, we've already inspected it when
+			 * building ForeignKeyOptInfo. So existence should be enough.
+			 */
+			continue;
+		}
+
+		/* found an attribute without a join clause, ignore this FK */
+		return false;
+	}
+
+	/* all FK attributes had a matching join clause */
+	return true;
+}
+
+/*
+ * starjoin_clauses_matched_by_foreign_key
+ *		Are all join clauses (rinfo or eclass) matched by the foreign key?
+ *
+ * Check if all join clauses for the current relation match the foreign key.
+ * Returns true if that's the case, false otherwise.
+ *
+ * XXX Could we do the check in both directions at once? Essentially, merge
+ * this with starjoin_foreign_key_matched_by_clauses, in a way that would
+ * make it cheaper than two separate functions? I don't think so.
+ */
+static bool
+starjoin_clauses_matched_by_foreign_key(PlannerInfo *root, RelOptInfo *rel,
+										ForeignKeyOptInfo *fkinfo)
+{
+	ListCell   *lc;
+	int			j;
+
+	/* Inspect all simple (RestrictInfo) clauses. */
+	foreach(lc, rel->joininfo)
+	{
+		RestrictInfo *rinfo = (RestrictInfo *) lfirst(lc);
+		bool		matched = false;	/* matched to the foreign key */
+
+		/* Is there a FK attribute referencing this rinfo? */
+		for (int i = 0; i < fkinfo->nkeys; i++)
+		{
+			if (list_member_ptr(fkinfo->rinfos[i], rinfo))
+			{
+				matched = true;
+				break;
+			}
+		}
+
+		/* found a clause not matched for FK */
+		if (!matched)
+			return false;
+	}
+
+	/* If the rel does not have eclass joins, we're done. */
+	if (!rel->has_eclass_joins)
+		return true;
+
+	/*
+	 * There should be joins with clauses in equivalence classes. Walk all the
+	 * eclasses, and try to match them to the foreign key.
+	 */
+	j = -1;
+	while ((j = bms_next_member(rel->eclass_indexes, j)) >= 0)
+	{
+		EquivalenceClass *ec = (EquivalenceClass *) list_nth(root->eq_classes, j);
+		bool		matched = false;	/* matched to the foreign key */
+
+		/*
+		 * We're interested in joins, and const or single-member EC won't
+		 * generate join clauses. So skip them now, before walking the FK.
+		 * (The latter test covers the volatile case too.)
+		 *
+		 * XXX Taken from generate_implied_equalities_for_column().
+		 */
+		if (ec->ec_has_const || list_length(ec->ec_members) <= 1)
+			continue;
+
+		/*
+		 * A join EC needs to have multiple relids, so ignore cases with only
+		 * a single relid.
+		 *
+		 * XXX Could there be 0 relids? I don't think so. Or do we need to
+		 * check if (num != 2) instead?
+		 *
+		 * XXX If this simple check is not enough and we need to inspect ut we
+		 * need to inspect the members, we should probably leave this after
+		 * matching to FK attributes, if it doesn't match. The FK check is
+		 * likely cheaper
+		 */
+		if (bms_num_members(ec->ec_relids) == 1)
+			continue;
+
+		/* Is there a FK attribute referencing this EC? */
+		for (int i = 0; i < fkinfo->nkeys; i++)
+		{
+			if (fkinfo->eclass[i] == ec)
+			{
+				matched = true;
+				break;
+			}
+		}
+
+		/* found a join eclass not matched by the FK */
+		if (!matched)
+			return false;
+	}
+
+	/* all the join clauses seem to match (both rinfo and eclass) */
+	return true;
+}
+
+/*
+ * starjoin_match_to_foreign_key
+ *		Determine if the relation is joined through a FK constraint.
+ *
+ * The relation needs to be joined through a FK constraint, with it being on
+ * the PK side of the join. The FK must be matched completely (no columns
+ * missing in join clauses), and there must be no other join clauses.
+ *
+ * We already have a list of relevant foreign keys, and we use that info
+ * for selectivity estimation in get_foreign_key_join_selectivity(). And
+ * we're actually doing something quite similar here.
+ *
+ * XXX Do we need to worry about the join type, e.g. inner/outer joins,
+ * semi/anti? get_foreign_key_join_selectivity() does care about it, and
+ * ignores some of those cases. Maybe we should too?
+ */
+static bool
+starjoin_match_to_foreign_key(PlannerInfo *root, RelOptInfo *rel)
+{
+	ListCell   *lc;
+
+	/*
+	 * Check if there's a FK matching the join clauses.
+	 *
+	 * The match needs to be perfect from both sides. All join clauses need to
+	 * match the foreign key, and the whole foreign key needs to have a
+	 * matching clause. There must not be any extra join clauses.
+	 */
+	foreach(lc, root->fkey_list)
+	{
+		ForeignKeyOptInfo *fkinfo = (ForeignKeyOptInfo *) lfirst(lc);
+
+		/*
+		 * The foreign key is not relevant unless it references the rel on the
+		 * PK side.
+		 *
+		 * XXX If we want to support the "inverse" join (with smaller tables
+		 * referencing the main table) in the future, we'll probably need to
+		 * allow con_relid too.
+		 */
+		if (fkinfo->ref_relid != rel->relid)
+			continue;
+
+		/*
+		 * First, check that each FK attribute has a matching join clause.
+		 */
+		if (!starjoin_foreign_key_matched_by_clauses(root, rel, fkinfo))
+			continue;
+
+		/*
+		 * Each FK attribute has a join clause matching it. What about the
+		 * opposite direction? Do all join clauses match this FK? We need to
+		 * check both joininfo and equivalence classes (if the rel has
+		 * has_eclass_joins=true).
+		 */
+		if (!starjoin_clauses_matched_by_foreign_key(root, rel, fkinfo))
+			continue;
+
+		/* matched in both directions */
+		return true;
+	}
+
+	return false;
+}
+
+/*
+ * starjoin_is_dimension
+ *		Determine if a range table entry is a dimension in a starjoin.
+ *
+ * To be considered a dimension for the simplified join order search, the
+ * relation must be joined in a way that does not affect the cardinality
+ * of the join. And must be possible to postpone the join.
+ *
+ * We ensure that by checking a couple things:
+ *
+ * 1) The join clause(s) match a single FK. There has to be a single FK,
+ *    with each key covered by a join clause. There must be no extra join
+ *    clauses (which means the rel can be joined to a single other rel).
+ *
+ * 2) The FK side (in the fact table) should be marked as NOT NULL.
+ *
+ * 3) There must be no additional restrictions (WHERE conditions etc.).
+ *
+ * 4) The relation must not have a join order restriction, i.e. it has to
+ *    be possible to "postpone" the join.
+ *
+ * These three rules guarantee the join does not alter the cardinality, as
+ * each row in the fact table has exactly one match in the dimension.
+ *
+ * XXX For inner joins this works fine. For outer we may need to be smarter
+ * as outer joins imply ordering restrictions, violating (4) and so don't
+ * allow the simplified planning. I believe it should be possible to still
+ * postpone the join, if we're dealing with the last relation in the list
+ * (because then we're not really changing the order). Or maybe it needs
+ * to check varnullingrels? In any case, we need to keep this cheap,
+ * cheaper than the "full" join planning.
+ *
+ * XXX Could we relax (3) in some way, to allow filters on dimensions? The
+ * joins are independent (there are no clauses between dimensions), so the
+ * per-dimension selectivity could measures how much it "shrinks" the join.
+ * We could order the dimensions so that the most selective (close to 0.0)
+ * are joined first, to reduce the join cardinality soon. This could be
+ * extended with the "cost" of evaluating the join clause, to make the cost
+ * model more correct.
+ *
+ * In snowflake joins this would be more complicated, because dimensions
+ * can join to other (child) dimensions, but even there the clauses don't
+ * go between branches. So even there it should be possible.
+ *
+ * XXX With LEFT joins we could even allow baserestrictinfo on the rel, as
+ * that won't affect the cardinality (if the filter happens before the
+ * join, of course). But such queries are likely rather rare, because why
+ * would you filter before LEFT join?
+ *
+ * XXX Right now this uses has_join_restriction(), but maybe that's a bit
+ * too heavy-handed and have_join_order_restriction would be better? But
+ * that might be too early? Also, have_join_order_restriction is already
+ * exposed in paths.h, not static. Could have_relevant_joinclause help?
+ *
+ * XXX There's also join_is_legal() to check legality of joins, with
+ * LEFT/RIGHT joins, and IN/EXISTS clauses (see "Join Tree Construction"
+ * in README, circa line 188). It also looks-up the SpecialJoinInfo for
+ * the join. But it's probably too early for join_is_legal(), we don't
+ * have RelOptInfos for joins yet, just base relations.
+ *
+ * XXX Is it just the "skipping" that can break the order restrictions?
+ * Adding something to the list of dimensions keeps the order (at least
+ * with respect to the rels after it).
+ */
+static bool
+starjoin_is_dimension(PlannerInfo *root, RangeTblRef *rtr)
+{
+	Index		rti = rtr->rtindex;
+	RangeTblEntry *rte = root->simple_rte_array[rti];
+	RelOptInfo *rel = root->simple_rel_array[rti];
+
+	/* only plain relations can be dimensions (we need FK/PK join) */
+	if ((rte->rtekind != RTE_RELATION) ||
+		(rel->reloptkind != RELOPT_BASEREL))
+		return false;
+
+	/*
+	 * Does it have any conditions/restrictions that may affect the number of
+	 * rows matched? If yes, don't treat as dimension.
+	 *
+	 * Dimensions in a starjoin may have restrictions, but that means it'll
+	 * change cardinality of the joins (reduce it), so it may be better to
+	 * join it early. We leave it to the regular join order planning. The
+	 * expectation is that most dimensions won't have extra restrictions.
+	 *
+	 * XXX Should we check some other fields, like lateral references, and so
+	 * on? Or is that unnecessary? What about eclasses?
+	 */
+	if (rel->baserestrictinfo != NIL)
+		return false;
+
+	/*
+	 * Ignore relations with join restrictions. This requires the complete
+	 * join order search, this cheap heuristics is not enough.
+	 *
+	 * XXX This blocks the simplified planning for LEFT (or OUTER) joins,
+	 * because outer joins imply restrictions.
+	 */
+	if (has_join_restriction(root, rel))
+		return false;
+
+	/*
+	 * See if the join clause matches a foreign key. It should match a single
+	 * relation on the other side, and the dimension should be on the PK side.
+	 */
+	if (!starjoin_match_to_foreign_key(root, rel))
+		return false;
+
+	/*
+	 * XXX Maybe some additional checks here ...
+	 */
+
+	return true;
+}
+
+/*
+ * starjoin_adjust_joins
+ *		Adjust the jointree for starjoins, to simplify the join order search.
+ *
+ * Try to simplify the join search problem for starjoin-like joins, with
+ * joins over FK relationships. The dimensions can be joined in almost any
+ * order, which is about the worst case for the standard join order search,
+ * and can be close to factorial complexity. But all the different orders
+ * are equivalent, so all this work is wasted. So the simplified planning
+ * identifies dimensions, and joins them all at the end of each group (as
+ * determined by the join_collapse_limit earlier).
+ *
+ * Note: The definition of a dimension is a bit vague. See the comment at
+ * starjoin_is_dimension() for our definition.
+ *
+ * The join search for starjoin queries is surprisingly expensive, because
+ * there are very few join order restrictions. Consider a starjoin query
+ *
+ *  SELECT * FROM f
+ *     JOIN d1 ON (f.id1 = d1.id)
+ *     JOIN d2 ON (f.id2 = d2.id)
+ *     ...
+ *     JOIN d9 ON (f.id9 = d9.id)
+ *
+ * There are no clauses between the dimension tables (d#), which means those
+ * tables can be joined in almost arbitrary order. This means the standard
+ * join_order_search() would explore a N! possible join orders. It is not
+ * that bad in practice, as we split the problem by from_collapse_limit into
+ * a sequence of smaller problems, but even for the default of 8 relations
+ * it's quite expensive. This can be easily demonstrated by setting
+ * join_collapse_limit=1 for starjoin queries.
+ *
+ * We can significantly simplify the join order search for this type of
+ * queries, without too much risk of picking a much worse plans. It is
+ * however a trade off between how expensive we allow this to be, and how
+ * good the decisions will be. This can help only starjoins with multiple
+ * dimension tables, and we don't want to harm planning of other queries,
+ * so the basic "query shape" detection needs to be very cheap.
+ *
+ * If a perfect check is impossible or too expensive, it's better to end
+ * up with a cheap false negative (i.e. and not use the optimization),
+ * rather than risk regressions in other cases. Otherwise we might just
+ * as well use the regular join order search.
+ *
+ * The simplified join order search relies leverages the fact that joins
+ * of dimensions do not change the cardinality of the join, which means
+ * the relative order of those joins does not matter. All orders perform
+ * the same - we can pick an arbitrary of those orders, and "hardcode"
+ * it in the join tree before passing it to join_order_search().
+ *
+ * The join order is "hardcoded" by modifying the jointree, undoing some
+ * of the work performed by deconstruct_jointree earlier. That decomposed
+ * the original jointree into smaller "problems" depending on join type,
+ * join_collapse_limit and other details. We inspect those smaller lists,
+ * and selectively split them into smaller problems to force a join order.
+ * This may effectively undo some of the merging, which tries to construct
+ * problems with up to join_collapse_limit relations.
+ *
+ * For example, imagine a join problem with 8 rels - one fact table and
+ * then 7 dimensions, which we can represent a joinlist with 8 elements.
+ *
+ * (D7, D6, D5, D4, D3, D2, D1, F)
+ *
+ * Assuming all those joins meet the requirements (have a matching FK,
+ * don't affect the join cardinality, ...), then we can split this into
+ *
+ * (D7, (D6, (D5, (D4, (D3, (D2, (D1, F)))))))
+ *
+ * which is a nested joinlist, with only two elements on each level. That
+ * means there's no need for expensive join order search, there's only
+ * one way to join the relations (two, if we consider the relations may
+ * switch sides).
+ *
+ * The joinlist may already be nested, with multiple smaller join problems,
+ * similar to the example. Those are processed independently. We don't try
+ * to merge problems to build join_collapse_limit problems again. This is
+ * partially to keep it cheap/simple, but also so not change behavior for
+ * cases when people use join_collapse_limit to force a particular shape.
+ *
+ * Note: Ne never move relations between the "smaller problems", so this
+ * restricts what fraction of the join space we explore. So reducing the
+ * join_collapse_limit would improve the starjoin planning, but it may
+ * produce worse plans for other queries.
+ *
+ * The query may involve joins to additional (non-dimension) tables, and
+ * those may alter cardinality in either direction. In principle, it'd be
+ * best to first perform all the joins that reduce join size, then join all
+ * the dimensions, and finally perform joins that may increase the join
+ * size. Imagine a joinlist:
+ *
+ * (D1, D2, A, B, F)
+ *
+ * with fact F, dimensions D1 and D2, and non-dimensions A and B. If A
+ * increases cardinality, and B does not (or even reduces it), we could
+ * use this join tree:
+ *
+ * (A, (D2, (D1, (B, F))))
+ *
+ * For now we simply leave the dimension joins at the end, assuming
+ * that the earlier joins did not inflate the join too much.
+ *
+ * XXX Joins with cardinality increase don't seem very common, at least in
+ * regular starjoin queries. But maybe we could simply check if there are
+ * any such joins and disable this optimization? Is there a cheap way to
+ * identify when a join increases cardinality? I suppose we would need to
+ * calculate selectivity for join clauses? That might be too expensive,
+ * which goes against keeping this join search optimization very cheap.
+ *
+ * XXX A possible improvement would be to allow snowflake joins, i.e.
+ * queries with "recursive" dimensions. That would require a more complex
+ * logic, as a dimension would be allowed to join to other rels, as long
+ * as those are dimensions too. We'd need to be careful about preventing
+ * cycles, and about the order in which we join them.
+ *
+ * XXX Maybe we could invent a "join item" representing the dimensions,
+ * and pass it to join_order_search()? It'd expand the item into individual
+ * joins, and do the regular cardinality estimations etc. But it would
+ * only consider a single join order of the dimension. It would be trivial
+ * to disable the optimization if needed, I think - don't collapse the
+ * dimensions into the "group" join item. It would require changes to
+ * the generic join search, to be aware of the new item type.
+ */
+List *
+starjoin_adjust_joins(PlannerInfo *root, List *joinlist)
+{
+	ListCell   *lc;
+	List	   *newlist = NIL;
+	List	   *dimensions = NIL;
+	int			nlist = list_length(joinlist);
+
+	/* Do nothing if starjoin optimization not enabled. */
+	if (!enable_starjoin_join_search)
+		return joinlist;
+
+	/*
+	 * Do nothing if starjoin optimization not applicable.
+	 *
+	 * XXX It might seems we can skip this for lists with <= 2 items, but that
+	 * does not work, the elements may be nested list, and we need to descend
+	 * into those. So do what remove_useless_self_joins() does, and only bail
+	 * out for the simplest single-relation case (i.e. no joins).
+	 */
+	if (joinlist == NIL ||
+		(nlist == 1 && !IsA(linitial(joinlist), List)))
+		return joinlist;
+
+	/*
+	 * Process the current join problem - split the elements into dimensions
+	 * and non-dimensions. If there are dimensions, add them back at the end,
+	 * as small single-rel joins.
+	 *
+	 * The list may contain various types of elements. It may contain a list,
+	 * which means it's an independent join search problem and we need to
+	 * process it recursively. Or it may be RangeTblRef, in which case we need
+	 * to check if it's a dimension. Other types of elements are just added
+	 * back to the list as-is.
+	 *
+	 * XXX I think we need to be careful to keep the order of the list (for
+	 * the non-dimension entries). The join_search_one_level() relies on that
+	 * when handling join order restrictions.
+	 *
+	 * XXX It might be better to only create a new list if needed, i.e. once
+	 * we find the first dimension. So that non-starjoin queries don't pay for
+	 * something they don't need. A mutable iterator might be a way, but I'm
+	 * not sure how expensive this really is.
+	 */
+	foreach(lc, joinlist)
+	{
+		Node	   *item = (Node *) lfirst(lc);
+
+		/* a separate join search problem, handle it recursively */
+		if (IsA(item, List))
+		{
+			newlist = lappend(newlist,
+							  starjoin_adjust_joins(root, (List *) item));
+			continue;
+		}
+
+		/*
+		 * If it's not a List, it has to be a RangeTblRef - jinlists can't
+		 * contain any other elements (see make_rel_from_joinlist).
+		 */
+		Assert(IsA(item, RangeTblRef));
+
+		/*
+		 * An entry representing a baserel. If it's a dimension, save it in a
+		 * separate list, and we'll add it at the "top" of the join at the
+		 * end. Otherwise add it to the list just like other elements.
+		 *
+		 * We do this only when the joinlist has at least 3 items. For fewer
+		 * rels the optimization does not matter, there's only a single join
+		 * order anyway. That only skips the optimization on this level - we
+		 * still do the recursion, and that might hit a larger join problem.
+		 *
+		 * XXX We might have a new GUC to customize the cutoff limit, but for
+		 * now it seems good enough to do it whenever applicable. If we find
+		 * it's not worth it for less than N rels, we can add it later.
+		 */
+		if ((nlist >= 3) &&
+			starjoin_is_dimension(root, (RangeTblRef *) item))
+		{
+			dimensions = lappend(dimensions, item);
+			continue;
+		}
+
+		/* not a dimension, add it to the list directly */
+		newlist = lappend(newlist, item);
+	}
+
+	/*
+	 * If we found some dimensions, add them to the join tree one by one. The
+	 * exact order does not matter, so we add them in the order we found them
+	 * in the original list.
+	 *
+	 * We need to add them by creating smaller 2-element lists, with the rest
+	 * of the list being a sub-problem and then adding the dimension table.
+	 * This is how we force the desired join order.
+	 */
+	foreach(lc, dimensions)
+	{
+		newlist = list_make2(newlist, lfirst(lc));
+	}
+
+	return newlist;
+}
diff --git a/src/backend/optimizer/plan/planmain.c b/src/backend/optimizer/plan/planmain.c
index eefc486a566..58278dbc94f 100644
--- a/src/backend/optimizer/plan/planmain.c
+++ b/src/backend/optimizer/plan/planmain.c
@@ -291,6 +291,13 @@ query_planner(PlannerInfo *root,
 	 */
 	distribute_row_identity_vars(root);
 
+	/*
+	 * Try to simplify the join search problem for starjoin-like joins. This
+	 * step relies on info about FK relationships, so we can't do it till
+	 * after match_foreign_keys_to_quals().
+	 */
+	joinlist = starjoin_adjust_joins(root, joinlist);
+
 	/*
 	 * Ready to do the primary planning.
 	 */
diff --git a/src/backend/utils/misc/guc_parameters.dat b/src/backend/utils/misc/guc_parameters.dat
index 1128167c025..d5b976b2e39 100644
--- a/src/backend/utils/misc/guc_parameters.dat
+++ b/src/backend/utils/misc/guc_parameters.dat
@@ -968,6 +968,13 @@
   boot_val => 'true',
 },
 
+{ name => 'enable_starjoin_join_search', type => 'bool', context => 'PGC_USERSET', group => 'QUERY_TUNING_METHOD',
+  short_desc => 'Enables simplified join order planning for starjoins.',
+  flags => 'GUC_EXPLAIN',
+  variable => 'enable_starjoin_join_search',
+  boot_val => 'true',
+},
+
 { name => 'enable_tidscan', type => 'bool', context => 'PGC_USERSET', group => 'QUERY_TUNING_METHOD',
   short_desc => 'Enables the planner\'s use of TID scan plans.',
   flags => 'GUC_EXPLAIN',
diff --git a/src/backend/utils/misc/postgresql.conf.sample b/src/backend/utils/misc/postgresql.conf.sample
index f62b61967ef..458cd74c262 100644
--- a/src/backend/utils/misc/postgresql.conf.sample
+++ b/src/backend/utils/misc/postgresql.conf.sample
@@ -424,6 +424,7 @@
 #enable_presorted_aggregate = on
 #enable_seqscan = on
 #enable_sort = on
+#enable_starjoin_join_search = on
 #enable_tidscan = on
 #enable_group_by_reordering = on
 #enable_distinct_reordering = on
diff --git a/src/include/optimizer/paths.h b/src/include/optimizer/paths.h
index f6a62df0b43..8d3c44854cd 100644
--- a/src/include/optimizer/paths.h
+++ b/src/include/optimizer/paths.h
@@ -108,6 +108,7 @@ extern RelOptInfo *make_join_rel(PlannerInfo *root,
 extern Relids add_outer_joins_to_relids(PlannerInfo *root, Relids input_relids,
 										SpecialJoinInfo *sjinfo,
 										List **pushed_down_joins);
+extern bool has_join_restriction(PlannerInfo *root, RelOptInfo *rel);
 extern bool have_join_order_restriction(PlannerInfo *root,
 										RelOptInfo *rel1, RelOptInfo *rel2);
 extern void mark_dummy_rel(RelOptInfo *rel);
diff --git a/src/include/optimizer/planmain.h b/src/include/optimizer/planmain.h
index 00addf15992..c30ac3a5754 100644
--- a/src/include/optimizer/planmain.h
+++ b/src/include/optimizer/planmain.h
@@ -21,6 +21,7 @@
 #define DEFAULT_CURSOR_TUPLE_FRACTION 0.1
 extern PGDLLIMPORT double cursor_tuple_fraction;
 extern PGDLLIMPORT bool enable_self_join_elimination;
+extern PGDLLIMPORT bool enable_starjoin_join_search;
 
 /* query_planner callback to compute query_pathkeys */
 typedef void (*query_pathkeys_callback) (PlannerInfo *root, void *extra);
@@ -120,6 +121,7 @@ extern bool innerrel_is_unique_ext(PlannerInfo *root, Relids joinrelids,
 								   JoinType jointype, List *restrictlist,
 								   bool force_cache, List **extra_clauses);
 extern List *remove_useless_self_joins(PlannerInfo *root, List *joinlist);
+extern List *starjoin_adjust_joins(PlannerInfo *root, List *joinlist);
 
 /*
  * prototypes for plan/setrefs.c
diff --git a/src/test/regress/expected/sysviews.out b/src/test/regress/expected/sysviews.out
index 3b37fafa65b..e9762da9937 100644
--- a/src/test/regress/expected/sysviews.out
+++ b/src/test/regress/expected/sysviews.out
@@ -172,8 +172,9 @@ select name, setting from pg_settings where name like 'enable%';
  enable_self_join_elimination   | on
  enable_seqscan                 | on
  enable_sort                    | on
+ enable_starjoin_join_search    | on
  enable_tidscan                 | on
-(25 rows)
+(26 rows)
 
 -- There are always wait event descriptions for various types.  InjectionPoint
 -- may be present or absent, depending on history since last postmaster start.
-- 
2.51.1

#36Bruce Momjian
bruce@momjian.us
In reply to: Tomas Vondra (#35)
Re: should we have a fast-path planning for OLTP starjoins?

On Wed, Nov 12, 2025 at 04:39:50PM +0100, Tomas Vondra wrote:

Hi,

Here's a v5, addressing some (but not all) of the things discussed
earlier in this thread.

This does nothing about the "opposite" type of join, with many small
tables linking to a single "central" table. I'm not convinced it makes
sense to handle that together with starjoins. But I haven't tried yet.

I read this thread and the patch. I have a few questions which might
have already been answered but they used terminology I might not have
understood. I want to explain what I think is happening and perhaps
someone can tell me if these ideas are new or are already covered.

So, assume a fact table with a primary-key first column, and ten more
columns, each with its own dimension table.

So, a star join would query the fact table with some filter, and then
join each of the ten columns to its own dimension table, e.g.,

fact.col2 joins to dim2.primary_key
fact.col3 joins to dim3.primary_key
...

and the problem is that the dimension tables don't join to each other,
but only to the fact table, and our existing optimizer considers join
orders of:

F to D2
F to D3
...

and then

F to D3
F to D4
...

and there are 10! possible combinations, and Tomas is saying that the
dimension tables are almost all the same in their affect on the row
count, so why bother to consider all 10! join orders. Also, some joins
might increase the row count, so a foreign key guarantees only one row
will be matched in the dimension.

I found this code comment in the recent patch which is helpful:

+ * The query may involve joins to additional (non-dimension) tables, and
+ * those may alter cardinality in either direction. In principle, it'd be
+ * best to first perform all the joins that reduce join size, then join all
+ * the dimensions, and finally perform joins that may increase the join
+ * size. Imagine a joinlist:
+ *
+ * (D1, D2, A, B, F)
+ *
+ * with fact F, dimensions D1 and D2, and non-dimensions A and B. If A
+ * increases cardinality, and B does not (or even reduces it), we could
+ * use this join tree:
+ *
+ * (A, (D2, (D1, (B, F))))
+ *
+ * For now we simply leave the dimension joins at the end, assuming
+ * that the earlier joins did not inflate the join too much.

And then there is the problem of detecting when this happens.

I think my big question is, when we join A->B->C->D, we do a lot of work
in the optimizer to figure out what order to use, but when we do A->B,
A->C, A->D, why are we spending the same amount of optimizer effort?

Could we just order B, C, D in order of which have restrictions, or
based on size? I assume we can't because we don't know if A->C or
another join would increase the number of rows, and this patch is saying
if there is a foreign key relationship, they can't increase the rows so
just short-circuit and order them simply. Is that accurate?

Crazy question, if we have A->B, A->C, and A->D, why can't we just sort
B,C,D based in increasing order of adding rows to the result, and just
use that ordering, without requiring foreign keys?

I am very glad someone is working on this problem.

--
Bruce Momjian <bruce@momjian.us> https://momjian.us
EDB https://enterprisedb.com

Do not let urgent matters crowd out time for investment in the future.

#37Tomas Vondra
tomas@vondra.me
In reply to: Bruce Momjian (#36)
Re: should we have a fast-path planning for OLTP starjoins?

On 11/14/25 22:07, Bruce Momjian wrote:

On Wed, Nov 12, 2025 at 04:39:50PM +0100, Tomas Vondra wrote:

Hi,

Here's a v5, addressing some (but not all) of the things discussed
earlier in this thread.

This does nothing about the "opposite" type of join, with many small
tables linking to a single "central" table. I'm not convinced it makes
sense to handle that together with starjoins. But I haven't tried yet.

I read this thread and the patch. I have a few questions which might
have already been answered but they used terminology I might not have
understood. I want to explain what I think is happening and perhaps
someone can tell me if these ideas are new or are already covered.

So, assume a fact table with a primary-key first column, and ten more
columns, each with its own dimension table.

So, a star join would query the fact table with some filter, and then
join each of the ten columns to its own dimension table, e.g.,

fact.col2 joins to dim2.primary_key
fact.col3 joins to dim3.primary_key
...

and the problem is that the dimension tables don't join to each other,
but only to the fact table, and our existing optimizer considers join
orders of:

F to D2
F to D3
...

and then

F to D3
F to D4
...

and there are 10! possible combinations, and Tomas is saying that the
dimension tables are almost all the same in their affect on the row
count, so why bother to consider all 10! join orders. Also, some joins
might increase the row count, so a foreign key guarantees only one row
will be matched in the dimension.

Right. A join between F and a "dimension" has the same cardinality as F,
i.e. each row in F has one matching row in the dimension. It's entirely
irrelevant in which order we actually join the dimensions.

And then there may be some other joins that affect the cardinality, and
the question is what to do about these ...

I found this code comment in the recent patch which is helpful:

+ * The query may involve joins to additional (non-dimension) tables, and
+ * those may alter cardinality in either direction. In principle, it'd be
+ * best to first perform all the joins that reduce join size, then join all
+ * the dimensions, and finally perform joins that may increase the join
+ * size. Imagine a joinlist:
+ *
+ * (D1, D2, A, B, F)
+ *
+ * with fact F, dimensions D1 and D2, and non-dimensions A and B. If A
+ * increases cardinality, and B does not (or even reduces it), we could
+ * use this join tree:
+ *
+ * (A, (D2, (D1, (B, F))))
+ *
+ * For now we simply leave the dimension joins at the end, assuming
+ * that the earlier joins did not inflate the join too much.

And then there is the problem of detecting when this happens.

I think my big question is, when we join A->B->C->D, we do a lot of work
in the optimizer to figure out what order to use, but when we do A->B,
A->C, A->D, why are we spending the same amount of optimizer effort?

I'm sorry, I don't quite understand what's the question here. What does
A->B->C->D mean, exactly?

The standard join algorithm is (intentionally) generic, it handles all
kinds of joins, and it simply doesn't have any special cases for joins
with a particular structure (like a starjoin).

Could we just order B, C, D in order of which have restrictions, or
based on size? I assume we can't because we don't know if A->C or
another join would increase the number of rows, and this patch is saying
if there is a foreign key relationship, they can't increase the rows so
just short-circuit and order them simply. Is that accurate?

Crazy question, if we have A->B, A->C, and A->D, why can't we just sort
B,C,D based in increasing order of adding rows to the result, and just
use that ordering, without requiring foreign keys?

Yeah, that's mostly the idea one of the comments in the patch suggests.
To do the joins that reduce the cardinality first, then the dimensions,
and finally the joins that increase the cardinality.

However, the examples make it look like we're joining pairs of tables,
but that's not necessarily true. The join may be between F and relation
that is really a join itself. And now you need to know how this join
changes the cardinality, which is more expensive than when only looking
at joins of pairs of tables.

So I think we'd need to first identify these "independent join groups"
first. But that seems non-trivial, because we don't know which table to
start from (we don't know what's the "F" table).

I'm sure there's an algorithm to decompose the join tree like this, but
I'm not sure how expensive / invasive it'd be. The premise of this patch
is that it's a cheap optimization, that doesn't need to do this.

It simply "peels off" the dimensions from the join, based on things it
can prove locally, without having to decompose the whole jointree.

In any case, this is my current understanding of the problem. It's
entirely possible I'm missing some obvious solution, described in a
paper somewhere.

regards

--
Tomas Vondra

#38Bruce Momjian
bruce@momjian.us
In reply to: Tomas Vondra (#37)
Re: should we have a fast-path planning for OLTP starjoins?

On Sat, Nov 15, 2025 at 01:41:04AM +0100, Tomas Vondra wrote:

And then there is the problem of detecting when this happens.

I think my big question is, when we join A->B->C->D, we do a lot of work
in the optimizer to figure out what order to use, but when we do A->B,
A->C, A->D, why are we spending the same amount of optimizer effort?

I'm sorry, I don't quite understand what's the question here. What does
A->B->C->D mean, exactly?

It means table A joins B, and B joins C, and C joins D. I can see that
as a much harder problem, and one we have code for in the optimizer,
than A joining to B, C, and D.

Could we just order B, C, D in order of which have restrictions, or
based on size? I assume we can't because we don't know if A->C or
another join would increase the number of rows, and this patch is saying
if there is a foreign key relationship, they can't increase the rows so
just short-circuit and order them simply. Is that accurate?

Crazy question, if we have A->B, A->C, and A->D, why can't we just sort
B,C,D based in increasing order of adding rows to the result, and just
use that ordering, without requiring foreign keys?

Yeah, that's mostly the idea one of the comments in the patch suggests.
To do the joins that reduce the cardinality first, then the dimensions,
and finally the joins that increase the cardinality.

Yes, I saw that.

However, the examples make it look like we're joining pairs of tables,
but that's not necessarily true. The join may be between F and relation
that is really a join itself. And now you need to know how this join
changes the cardinality, which is more expensive than when only looking
at joins of pairs of tables.

Yes, if the join is from F to D, and D joins to something else,
especially if it is not a foreign key where we know there is only one
match, I think we have to give up and go back to the normal optimizer
process.

So I think we'd need to first identify these "independent join groups"
first. But that seems non-trivial, because we don't know which table to
start from (we don't know what's the "F" table).

Do we easily know how many relations each relation joins to? Does that
help us?

I'm sure there's an algorithm to decompose the join tree like this, but
I'm not sure how expensive / invasive it'd be. The premise of this patch
is that it's a cheap optimization, that doesn't need to do this.

Yeah, I can see expense being an issue, which explains, as you said, why
many other databases have star join "flags", which ideally we can avoid
since very few people are going to use the flag.

It simply "peels off" the dimensions from the join, based on things it
can prove locally, without having to decompose the whole jointree.

I see, and I think understand better now. Thanks.

--
Bruce Momjian <bruce@momjian.us> https://momjian.us
EDB https://enterprisedb.com

Do not let urgent matters crowd out time for investment in the future.

#39Nico Williams
nico@cryptonector.com
In reply to: Tomas Vondra (#1)
Re: should we have a fast-path planning for OLTP starjoins?

On Tue, Feb 04, 2025 at 03:00:49PM +0100, Tomas Vondra wrote:

I'm late to this party. I have apps that do start queries like this a
lot. These apps fall into this type:

Or maybe the fact table is "users" and the dimensions have all kinds of
info about the user (address, primary e-mail address, balance, ...).

In my case the schema is an EAV schema, but essentially it stores users,
groups, and many other such things -- the sorts you expect to find in a
directory service.

Some unsolicited advice:

- the table source with the longest index key prefix (or full key)
determined by WHERE clause terms is the table that should lead the
query plan

This is really important for the case where the query is a VIEW and
the WHERE clause terms can get pushed into it, then:

SELECT ...
FROM t0
JOIN t1 ON ...
JOIN t2 ON ...
..
JOIN tN ON ...
-- tX's PK is (a, b, c), or maybe (a, b, c, d), but (a, b, c) is a
-- very selective prefix of that PK index, so the query plan should
-- start with tX
WHERE tX.a = ... AND tX.b = ... AND tX.c = ...

- if there is no such table source then we're asking for "all the
data", and we might as well start with a full table scan of some
table source, but, which? my answer: the lexically first one in the
query! (why? because it gives the query author the power to pick
which table goes first in this case)

SELECT ...
FROM t0
JOIN ...
...; -- no WHERE clause or no terms that provide values for prefixes
-- of indices that we could use to find a good choice of
-- starting table, so start with t0

Anyway, this pattern is quite common, yet it performs quite poorly.

Yes.

But for starjoins, a lot of this is not really needed. In the simplest
case (no conditions on dimensions etc) it does not really matter in what
order we join those, and filters on dimensions make it only a little bit

But here you can just use the order that the SQL uses. It gives the
author some power.

more complicated (join the most selective first).

Yes.

So I've been wondering how difficult would it be to have a special
fast-path mode for starjoins, completely skipping most of this. I
cobbled together a WIP/PoC patch (attached) on the way from FOSDEM, and
it seems to help quite a bit.

Yay! _Thank you_!

So that about triples the throughput. If you bump join_collapse_limit to
12, it gets even clearer

build 1 16
--------------------------------------
master 200 2000
patched 4500 48000

That's a 20x improvement - not bad. Sure, this is on a tiny dataset, and
with larger data sets it might need to do I/O, diminishing the benefits.
It's just an example to demonstrate the benefits.

Fantastic! I can't wait to use this in prod.

But the bigger question is whether it makes sense to have such fast-path
modes for certain query shapes. The patch "hard-codes" the planning for
starjoin queries, but we clearly can't do that for every possible join
shape (because then why have dynamic join search at all?).

IMO: Yes for starjoins. The reason is:

I do think starjoins might be sufficiently unique / special to justify
this, but maybe it would be possible to instead improve the regular join
order search to handle this case better? I don't have a very clear idea
what would that look like, though :-(

If you're not pessimizing other cases and you're getting a 4x to 20x
improvement then the uniqueness of the starjoin case and the frequent
use of starjoin queries makes this fast-path worthwhile.

Moreover, I think in general if you can cheaply determine a "kind" of
query and then apply query plan searches / optimizations that are most
relevant to the query's "kind" then I think that's a good way to unlock
more useful optimizations.

I did check what do some other databases do, and they often have some
sort of "hint" to nudge the let the optimizer know this is a starjoin.

I don't think a hint is needed here.

BTW, I like hints, but only out-of-band, not embedded in the SQL.
Unfortunately out-of-band hinting is not really viable because to
introduce it one would need new APIs (and possibly protocol work).

Nico
--

#40Tom Lane
tgl@sss.pgh.pa.us
In reply to: Nico Williams (#39)
Re: should we have a fast-path planning for OLTP starjoins?

Nico Williams <nico@cryptonector.com> writes:

Some unsolicited advice:
...
But here you can just use the order that the SQL uses. It gives the
author some power.

If that's the approach you want, it's been possible for decades:
"set join_collapse_limit = 1" and away you go. I don't feel a
need to invent a different version of that for star schemas.

I do not think this patch should have ambitions beyond the stated
one of avoiding useless join-order search effort. If you try to
load more than that onto the plate you'll probably end in failure.

regards, tom lane

#41Bruce Momjian
bruce@momjian.us
In reply to: Bruce Momjian (#38)
Re: should we have a fast-path planning for OLTP starjoins?

On Fri, Nov 14, 2025 at 09:52:41PM -0500, Bruce Momjian wrote:

On Sat, Nov 15, 2025 at 01:41:04AM +0100, Tomas Vondra wrote:

And then there is the problem of detecting when this happens.

I think my big question is, when we join A->B->C->D, we do a lot of work
in the optimizer to figure out what order to use, but when we do A->B,
A->C, A->D, why are we spending the same amount of optimizer effort?

I'm sorry, I don't quite understand what's the question here. What does
A->B->C->D mean, exactly?

It means table A joins B, and B joins C, and C joins D. I can see that
as a much harder problem, and one we have code for in the optimizer,
than A joining to B, C, and D.

I guess fundamentally it is the case of splitting a big problem into
smaller ones, e.g., 2 + 3 + 3 = 8, but 2! * 3! * 3! = 72 and 8! = 40320.

--
Bruce Momjian <bruce@momjian.us> https://momjian.us
EDB https://enterprisedb.com

Do not let urgent matters crowd out time for investment in the future.

#42Tomas Vondra
tomas@vondra.me
In reply to: Tom Lane (#40)
Re: should we have a fast-path planning for OLTP starjoins?

On 11/15/25 16:57, Tom Lane wrote:

Nico Williams <nico@cryptonector.com> writes:

Some unsolicited advice:
...
But here you can just use the order that the SQL uses. It gives the
author some power.

If that's the approach you want, it's been possible for decades:
"set join_collapse_limit = 1" and away you go. I don't feel a
need to invent a different version of that for star schemas.

I do not think this patch should have ambitions beyond the stated
one of avoiding useless join-order search effort. If you try to
load more than that onto the plate you'll probably end in failure.

FWIW I certainly agree with this. The motivation is to speed up planning
with starjoin-like queries, and that's still the primary goal. If it
could handle more complex cases (snowflake, inverse starjoin), great.
But I have no ambition to make it somehow generic and much more complex.

The main thing I'm really unsure about is what to do about joins that
increase the cardinality. AFAICS that's the only possible regression if
we simply move joins with dimensions at the end. Not sure what to do
about that before the actual join search ...

regards

--
Tomas Vondra

#43Tom Lane
tgl@sss.pgh.pa.us
In reply to: Tomas Vondra (#42)
Re: should we have a fast-path planning for OLTP starjoins?

I spent a little time staring at the v5 patches. Obviously there
are a bunch of minor details to be verified, which you've carefully
provided XXX comments about, and I didn't really go through those
yet. There are two big-picture questions that are bothering me:

1. I do not think I believe the premise that the dimension tables
typically won't have restriction clauses. ISTM that a typical
query might be like

select sum(o.total_price) from
orders o
join customers c on c.id = o.c_id
join products p on p.id = o.p_id
where c.customer_name = 'Wile E Coyote'
and p.product_name = 'Rocket Skates';

The only reason to join a dimension table that lacks a restriction
clause is if you need some of its fields in the output, which you
might but I'm not sure that's such a common case. (Have you got
evidence to the contrary?) So I feel like we're not going to be
getting all that much win if we are not willing to treat such tables
as dimension tables. We could do something simplistic like order
those dimensions by the selectivity of their baserestrict clauses,
joining the most-restricted ones first and any restriction-free ones
last.

2. I'm pretty un-excited about the 0002 patch altogether. I'm having
a hard time visualizing cases where it helps, other than left joins
to dimension tables which I don't really think are common either.
I did a bit of poking around on the net and found that it seems to
be common to restrict star-join optimizations to equijoins (e.g.
SAP says explicitly that they only handle that case). I think we'd
be better off to focus on the allow-baserestrict-clauses extension
than the allow-join-order-restrictions extension.

regards, tom lane

#44Bruce Momjian
bruce@momjian.us
In reply to: Tom Lane (#43)
Re: should we have a fast-path planning for OLTP starjoins?

On Fri, Nov 21, 2025 at 03:14:15PM -0500, Tom Lane wrote:

I spent a little time staring at the v5 patches. Obviously there
are a bunch of minor details to be verified, which you've carefully
provided XXX comments about, and I didn't really go through those
yet. There are two big-picture questions that are bothering me:

1. I do not think I believe the premise that the dimension tables
typically won't have restriction clauses. ISTM that a typical
query might be like

select sum(o.total_price) from
orders o
join customers c on c.id = o.c_id
join products p on p.id = o.p_id
where c.customer_name = 'Wile E Coyote'
and p.product_name = 'Rocket Skates';

Yes, I am sure it is typical because I have seen cartoons use exactly
those products. ;-)

The only reason to join a dimension table that lacks a restriction
clause is if you need some of its fields in the output, which you
might but I'm not sure that's such a common case. (Have you got
evidence to the contrary?) So I feel like we're not going to be
getting all that much win if we are not willing to treat such tables
as dimension tables. We could do something simplistic like order
those dimensions by the selectivity of their baserestrict clauses,
joining the most-restricted ones first and any restriction-free ones
last.

Oh, I thought the patch already did this, e.g., the patch was going to
make groups, e.g., foreign keys with restrictions, foreign keys without
restrictions, and no foreign key (might add rows). The first group was
going to be sorted by their selectivity, and the last group was going to
be sorted by how much they add rows, if that is possible.

--
Bruce Momjian <bruce@momjian.us> https://momjian.us
EDB https://enterprisedb.com

Do not let urgent matters crowd out time for investment in the future.

#45Tomas Vondra
tomas@vondra.me
In reply to: Tom Lane (#43)
Re: should we have a fast-path planning for OLTP starjoins?

On 11/21/25 21:14, Tom Lane wrote:

I spent a little time staring at the v5 patches. Obviously there
are a bunch of minor details to be verified, which you've carefully
provided XXX comments about, and I didn't really go through those
yet. There are two big-picture questions that are bothering me:

1. I do not think I believe the premise that the dimension tables
typically won't have restriction clauses. ISTM that a typical
query might be like

select sum(o.total_price) from
orders o
join customers c on c.id = o.c_id
join products p on p.id = o.p_id
where c.customer_name = 'Wile E Coyote'
and p.product_name = 'Rocket Skates';

The only reason to join a dimension table that lacks a restriction
clause is if you need some of its fields in the output, which you
might but I'm not sure that's such a common case. (Have you got
evidence to the contrary?) So I feel like we're not going to be
getting all that much win if we are not willing to treat such tables
as dimension tables. We could do something simplistic like order
those dimensions by the selectivity of their baserestrict clauses,
joining the most-restricted ones first and any restriction-free ones
last.

Good question. I don't have a great evidence such joins to dimensions
(without additional restrictions) are a common case. It's partially a
guess and partially based on my past experience.

I have seen a lot of such joins in analytical workloads, where the join
is followed by an aggregation, with GROUP BY referencing attributes from
the dimensions. Of course, that may be an argument against worrying
about the planning too much, because with enough data the timing is
going to be dominated by the join/aggregation execution. However, it's
surprising how little data many analytical workloads actually access, so
it's not that clear.

The other use case I've been thinking about is poorly written queries,
joining more tables than needed. A traditional example is an ORM loading
more data than needed, to load the whole "object". I don't know how
prevalent this is today - it used to be a pretty common issue, and I
doubt it improved. I think it's not that different from the self-join
removal (the tradeoffs may be different, of course). I realize we try
not to add complexity for such cases, especially if it might hurt well
written queries.

Actually, I initially investigated at the opposite example, i.e. all
dimensions joining to the fact.id, see create-2/select-2 scripts. And
then I realized starjoins have mostly the same issue. But it's true the
v5 patch does not actually help this original query.

2. I'm pretty un-excited about the 0002 patch altogether. I'm having
a hard time visualizing cases where it helps, other than left joins
to dimension tables which I don't really think are common either.
I did a bit of poking around on the net and found that it seems to
be common to restrict star-join optimizations to equijoins (e.g.
SAP says explicitly that they only handle that case). I think we'd
be better off to focus on the allow-baserestrict-clauses extension
than the allow-join-order-restrictions extension.

I recall seen such queries (with LEFT joins) in analytics workloads, but
it's definitely less common than inner starjoins. So I agree focusing on
allowing baserestrict clauses is probably more useful/important.

FWIW I tried searching for more info too, but all the SAP pages
suggested by google return 404 to me :-(

regards

--
Tomas Vondra

#46Tomas Vondra
tomas@vondra.me
In reply to: Bruce Momjian (#44)
Re: should we have a fast-path planning for OLTP starjoins?

On 11/21/25 21:47, Bruce Momjian wrote:

On Fri, Nov 21, 2025 at 03:14:15PM -0500, Tom Lane wrote:

I spent a little time staring at the v5 patches. Obviously there
are a bunch of minor details to be verified, which you've carefully
provided XXX comments about, and I didn't really go through those
yet. There are two big-picture questions that are bothering me:

1. I do not think I believe the premise that the dimension tables
typically won't have restriction clauses. ISTM that a typical
query might be like

select sum(o.total_price) from
orders o
join customers c on c.id = o.c_id
join products p on p.id = o.p_id
where c.customer_name = 'Wile E Coyote'
and p.product_name = 'Rocket Skates';

Yes, I am sure it is typical because I have seen cartoons use exactly
those products. ;-)

;-)

The only reason to join a dimension table that lacks a restriction
clause is if you need some of its fields in the output, which you
might but I'm not sure that's such a common case. (Have you got
evidence to the contrary?) So I feel like we're not going to be
getting all that much win if we are not willing to treat such tables
as dimension tables. We could do something simplistic like order
those dimensions by the selectivity of their baserestrict clauses,
joining the most-restricted ones first and any restriction-free ones
last.

Oh, I thought the patch already did this, e.g., the patch was going to
make groups, e.g., foreign keys with restrictions, foreign keys without
restrictions, and no foreign key (might add rows). The first group was
going to be sorted by their selectivity, and the last group was going to
be sorted by how much they add rows, if that is possible.

No, the patch never did that. The various XXX comments discuss that as a
future optimization. Aren't the comments clear enough?

I think it'd work about the way you described, except that joins without
foreign keys can both increase and decrease the cardinality, and those
that reduce cardinality would need to be moved to the first group.

Another question is what to do about snowflake joins, as a common
extension/generalization of starjoins. I think we'd need to identify the
groups of dimensions (for the branches), and treat those as a single
logical dimension.

regards

--
Tomas Vondra

#47Bruce Momjian
bruce@momjian.us
In reply to: Tomas Vondra (#46)
Re: should we have a fast-path planning for OLTP starjoins?

On Sun, Nov 23, 2025 at 03:53:17PM +0100, Tomas Vondra wrote:

The only reason to join a dimension table that lacks a restriction
clause is if you need some of its fields in the output, which you
might but I'm not sure that's such a common case. (Have you got
evidence to the contrary?) So I feel like we're not going to be
getting all that much win if we are not willing to treat such tables
as dimension tables. We could do something simplistic like order
those dimensions by the selectivity of their baserestrict clauses,
joining the most-restricted ones first and any restriction-free ones
last.

Oh, I thought the patch already did this, e.g., the patch was going to
make groups, e.g., foreign keys with restrictions, foreign keys without
restrictions, and no foreign key (might add rows). The first group was
going to be sorted by their selectivity, and the last group was going to
be sorted by how much they add rows, if that is possible.

No, the patch never did that. The various XXX comments discuss that as a
future optimization. Aren't the comments clear enough?

I think my brain got lost in the patch --- I was happy I got as far as I
did in understanding it. :-)

I think it'd work about the way you described, except that joins without
foreign keys can both increase and decrease the cardinality, and those
that reduce cardinality would need to be moved to the first group.

I see, makes sense.

--
Bruce Momjian <bruce@momjian.us> https://momjian.us
EDB https://enterprisedb.com

Do not let urgent matters crowd out time for investment in the future.

#48Robert Haas
robertmhaas@gmail.com
In reply to: Tomas Vondra (#45)
Re: should we have a fast-path planning for OLTP starjoins?

On Sun, Nov 23, 2025 at 9:39 AM Tomas Vondra <tomas@vondra.me> wrote:

1. I do not think I believe the premise that the dimension tables
typically won't have restriction clauses. ISTM that a typical
query might be like

select sum(o.total_price) from
orders o
join customers c on c.id = o.c_id
join products p on p.id = o.p_id
where c.customer_name = 'Wile E Coyote'
and p.product_name = 'Rocket Skates';

Good question. I don't have a great evidence such joins to dimensions
(without additional restrictions) are a common case. It's partially a
guess and partially based on my past experience.

In my experience, restriction clauses on dimension tables are very common.

--
Robert Haas
EDB: http://www.enterprisedb.com

#49Tomas Vondra
tomas@vondra.me
In reply to: Robert Haas (#48)
Re: should we have a fast-path planning for OLTP starjoins?

On 11/24/25 21:55, Robert Haas wrote:

On Sun, Nov 23, 2025 at 9:39 AM Tomas Vondra <tomas@vondra.me> wrote:

1. I do not think I believe the premise that the dimension tables
typically won't have restriction clauses. ISTM that a typical
query might be like

select sum(o.total_price) from
orders o
join customers c on c.id = o.c_id
join products p on p.id = o.p_id
where c.customer_name = 'Wile E Coyote'
and p.product_name = 'Rocket Skates';

Good question. I don't have a great evidence such joins to dimensions
(without additional restrictions) are a common case. It's partially a
guess and partially based on my past experience.

In my experience, restriction clauses on dimension tables are very common.

Sure, but does that imply the inverse case (dimensions without non-join
restrictions) are not? I'm not sure.

regards

--
Tomas Vondra

#50Robert Haas
robertmhaas@gmail.com
In reply to: Tomas Vondra (#49)
Re: should we have a fast-path planning for OLTP starjoins?

On Wed, Nov 26, 2025 at 1:30 PM Tomas Vondra <tomas@vondra.me> wrote:

In my experience, restriction clauses on dimension tables are very common.

Sure, but does that imply the inverse case (dimensions without non-join
restrictions) are not? I'm not sure.

Obviously that depends on a lot of things, and I don't completely
understand what the patch does and doesn't do. But, I think it would
be sad to implement an optimization that falls over catastrophically
when such restriction clauses are present. For example, a long time
ago, I used to build web applications. Twenty, even thirty table joins
were common. There certainly wouldn't be a restriction clause on every
dimension table, but it would be an unusual situation if there were NO
restriction clauses on ANY dimension table. It's maybe also worth
mentioning that in those applications, it wasn't always a pure star
join: one central fact table would join to a bunch of codes tables,
but also very often to some other fact tables that had their own codes
tables. Point being that optimizations like this can be shown to have
a LOT of value in individual test cases even if the circumstances in
which they can be applied are very restricted, but lifting some of
those restrictions can enormously expand the number of real-world
cases to which they apply. My intuition is that a smaller gain on a
larger class of queries will win us more praise than the reverse.

--
Robert Haas
EDB: http://www.enterprisedb.com

#51Tomas Vondra
tomas@vondra.me
In reply to: Robert Haas (#50)
Re: should we have a fast-path planning for OLTP starjoins?

On 11/28/25 19:57, Robert Haas wrote:

On Wed, Nov 26, 2025 at 1:30 PM Tomas Vondra <tomas@vondra.me> wrote:

In my experience, restriction clauses on dimension tables are very common.

Sure, but does that imply the inverse case (dimensions without non-join
restrictions) are not? I'm not sure.

Obviously that depends on a lot of things, and I don't completely
understand what the patch does and doesn't do. But, I think it would
be sad to implement an optimization that falls over catastrophically
when such restriction clauses are present. For example, a long time
ago, I used to build web applications. Twenty, even thirty table joins
were common. There certainly wouldn't be a restriction clause on every
dimension table, but it would be an unusual situation if there were NO
restriction clauses on ANY dimension table.

I think it depends on what you mean by "falls over catastrophically".

The patch identifies dimensions without restrictions, moves them aside,
and does regular join search on the rest of the relations (some of which
may be dimensions with restrictions).

So the presence of dimensions with restrictions does not disable the
optimization entirely, it just means the dimensions with restrictions
won't benefit from it. So in the worst case, it'll perform just like
before (assuming the optimization is kept cheap enough).

I'd love if the optimization worked for all dimensions, even for those
with restrictions. But I don't know about such optimization.

It's maybe also worth
mentioning that in those applications, it wasn't always a pure star
join: one central fact table would join to a bunch of codes tables,
but also very often to some other fact tables that had their own codes
tables.

I certainly don't claim this optimization works for all queries, but
it's also not restricted to "pure" starjoins. It simply finds which
relations can be considered dimensions (i.e. joined through a FK). It
does not match the whole plan shape, or anything like that.

Yes, that may reduce the possible benefit of this optimization, because
the patch works within the "groups" generated by join_collapse_limit (so
within 8 relations by default). If those groups have few dimensions, the
patch may not help all that much.

Point being that optimizations like this can be shown to have
a LOT of value in individual test cases even if the circumstances in
which they can be applied are very restricted, but lifting some of
those restrictions can enormously expand the number of real-world
cases to which they apply. My intuition is that a smaller gain on a
larger class of queries will win us more praise than the reverse.

I don't disagree, but isn't this mostly what we're discussing now? I'm
trying to figure out if enough queries would benefit from this
optimization, which only applies to dimensions without restrictions.

regards

--
Tomas Vondra

#52Robert Haas
robertmhaas@gmail.com
In reply to: Tomas Vondra (#51)
Re: should we have a fast-path planning for OLTP starjoins?

On Fri, Nov 28, 2025 at 2:21 PM Tomas Vondra <tomas@vondra.me> wrote:=

The patch identifies dimensions without restrictions, moves them aside,
and does regular join search on the rest of the relations (some of which
may be dimensions with restrictions).

So the presence of dimensions with restrictions does not disable the
optimization entirely, it just means the dimensions with restrictions
won't benefit from it. So in the worst case, it'll perform just like
before (assuming the optimization is kept cheap enough).

I'm guessing that the reason you're limiting this to relations without
restrictions is so that you don't have to reason about the join
causing cardinality changes. But I don't quite understand how you
avoid having that problem anyway. For example, suppose that we have a
fact table F which is joined to relations S1, S2, D1, D2, I1, and I2.
The joins to S1 and S2 are joins on FKs to unconstrained dimension
tables; i.e. cardinality stays the same. The joins to D1 and D2 are
joins on FKs to constrained dimension tables, i.e. cardinality
decreases. The joins to I1 and I2 on average match more than once,
i.e. cardinality increases. The optimal join order is presumably
something like F-D1-D2-S1-S2-I1-I2, so that the number of rows flowing
through each level of the join tree is kept as small as possible, but
how do you achieve this if the joins to S1 and S2 are set aside? In
the presence of row-count-inflating joins, it's wrong to suppose that
S1 and S2 should be joined at the end.

What seems more likely to be true is that we should perform the join
to S1 and the join to S2 consecutively. It's very common in my
experience for complex reporting queries to have a bunch of joins the
results of which matter very little: each one changes the cardinality
very little or not at all, and so any ordering of those joins produces
essentially the same result, and probably it's best to do them all at
whatever point in the join sequence the cardinality of the other input
is at lowest. However, I'm not sure that even this is guaranteed. For
instance, suppose that in the above example there's no index on the
column of F that joins to S2. Could it be that the only reasonable way
to join to S2 is a merge join? If so, it might be best to start by
join F to S2 using an index scan on each, and then continue by joining
to D1, D2, S1, I1, I2 in that order.

Every time I start to think about this kind of optimization, I find
myself getting hung up on corner cases like these which are, maybe,
not all that probable, but which I think people almost certainly do
rely on the planner to get right. I don't know what to do about that.
I certainly agree with the idea that we waste a lot of energy
searching through functionally identical join orders and that we
should find a way to avoid that, but I'm a little suspicious that
avoiding regressions, or even finding out whether we've introduced
any, will prove difficult.

--
Robert Haas
EDB: http://www.enterprisedb.com

#53Tomas Vondra
tomas@vondra.me
In reply to: Robert Haas (#52)
Re: should we have a fast-path planning for OLTP starjoins?

On 11/28/25 23:50, Robert Haas wrote:

On Fri, Nov 28, 2025 at 2:21 PM Tomas Vondra <tomas@vondra.me> wrote:=

The patch identifies dimensions without restrictions, moves them aside,
and does regular join search on the rest of the relations (some of which
may be dimensions with restrictions).

So the presence of dimensions with restrictions does not disable the
optimization entirely, it just means the dimensions with restrictions
won't benefit from it. So in the worst case, it'll perform just like
before (assuming the optimization is kept cheap enough).

I'm guessing that the reason you're limiting this to relations without
restrictions is so that you don't have to reason about the join
causing cardinality changes. But I don't quite understand how you
avoid having that problem anyway. For example, suppose that we have a
fact table F which is joined to relations S1, S2, D1, D2, I1, and I2.
The joins to S1 and S2 are joins on FKs to unconstrained dimension
tables; i.e. cardinality stays the same. The joins to D1 and D2 are
joins on FKs to constrained dimension tables, i.e. cardinality
decreases. The joins to I1 and I2 on average match more than once,
i.e. cardinality increases. The optimal join order is presumably
something like F-D1-D2-S1-S2-I1-I2, so that the number of rows flowing
through each level of the join tree is kept as small as possible, but
how do you achieve this if the joins to S1 and S2 are set aside? In
the presence of row-count-inflating joins, it's wrong to suppose that
S1 and S2 should be joined at the end.

Yes, that's certainly possible. It was discussed at the very beginning
of this thread, and at that point there was a suggestion to keep it
simple and just push the joins to the end:

/messages/by-id/1751009.1738974197@sss.pgh.pa.us

I'm not claiming that's good enough, though. Maybe we should reconsider
and it needs a better solution.

What seems more likely to be true is that we should perform the join
to S1 and the join to S2 consecutively. It's very common in my
experience for complex reporting queries to have a bunch of joins the
results of which matter very little: each one changes the cardinality
very little or not at all, and so any ordering of those joins produces
essentially the same result, and probably it's best to do them all at
whatever point in the join sequence the cardinality of the other input
is at lowest. However, I'm not sure that even this is guaranteed. For
instance, suppose that in the above example there's no index on the
column of F that joins to S2. Could it be that the only reasonable way
to join to S2 is a merge join? If so, it might be best to start by
join F to S2 using an index scan on each, and then continue by joining
to D1, D2, S1, I1, I2 in that order.

Good points.

The first part reminds me the approach I mentioned a couple messages
back, We might preprocess the join lists, but instead of "removing the
dimensions" from the search, we'd group them together, and treat each
group as a single item in join_search_one_level. Then, whenever
join_search_one_level hits the group, it'd expand it into a sequence of
joins. I have not tried that yet, but it seems doable ...

However, I'm not sure about your second point - what if the join order
matters after all, e.g. because some join order can leverage ordering
(pathkeys) of the inputs, or produces ordering better for the later joins?

Every time I start to think about this kind of optimization, I find
myself getting hung up on corner cases like these which are, maybe,
not all that probable, but which I think people almost certainly do
rely on the planner to get right. I don't know what to do about that.
I certainly agree with the idea that we waste a lot of energy
searching through functionally identical join orders and that we
should find a way to avoid that, but I'm a little suspicious that
avoiding regressions, or even finding out whether we've introduced
any, will prove difficult.

True. I started working on this with two assumptions: (a) we can detect
cases when this is guaranteed to be the optimal join order, and (b) it
would be cheap to do so. Maybe one of those assumptions is not correct.

thanks

--
Tomas Vondra

#54Robert Haas
robertmhaas@gmail.com
In reply to: Tomas Vondra (#53)
Re: should we have a fast-path planning for OLTP starjoins?

On Fri, Nov 28, 2025 at 6:34 PM Tomas Vondra <tomas@vondra.me> wrote:

True. I started working on this with two assumptions: (a) we can detect
cases when this is guaranteed to be the optimal join order, and (b) it
would be cheap to do so. Maybe one of those assumptions is not correct.

Probably needs testing, at least.

I wonder if there's any way that we could rule out the presence of
row-count-inflating joins, or at least identify the joins that are
definitely not row-count-inflating. I have a general feeling that we
postpone some of the estimation work that the planner does for too
long, and that moving some of it earlier would allow better
decision-making. It's very common for a query to involve a driving
table and then a bunch of joins to side tables that are all
essentially independent of each other. That is, each of those joins
will multiply the row count from the other side of the join by a
constant that does not depend very much on the join order. I don't
really know exactly what we could do that would enable us to notice
that pattern and do something about it, but it feels like we're
duplicating a lot of work

For instance, consider a 4-way join between A, B, C, and D, where A is
connected to the other three tables by join clauses, and those are the
only join clauses. Let's say that the join to B is going to multiply
the row count by 2, the join to C is going to multiply it by 1 (i.e.
no change), and the join to D is going to multiply it by 0.1 (i.e.
eliminate 90% of rows). Well, we're going to consider the A-B join and
discover that it has 2 times the cardinality of A, and then later
we'll consider the (A-C)-B join and discover that it has 2 times the
cardinality of A-C, and then later we'll consider the (A-D)-B join and
discover that it has two times the cardinality of A-D, and then later
we'll consider the (A-B-C)-D join and discover that it has two times
the cardinality of A-B-C. As the number of tables grows, the number of
times we rediscover the effect of joining to a certain table grows, I
believe, exponentially.

Of course, in theory, there's no reason why the idea that any
particular join multiplies the row count by a constant that is
independent of the join order has to be correct. For instance, if the
A-B join multiplies the same rows that the A-D join eliminates, then
you can't set a fixed multiplier for either one. But in practice, even
when that's the case, we're not aware of it: when evaluating a join
column from, say, the output of the A-B join, we use the statistics
for the underlying column of A or B, without any modification
reflecting what the A-B join did to the distribution. So I think that
our estimates will behave like join-order-independent multipliers even
when the reality is otherwise. I'm not at all sure that I'm totally
right about this, and I sort of expect you or Tom to point out why I'm
totally weak in the head for thinking that it's the case, but I feel
like there might be the kernel of an idea here even if the details are
wrong.

Because, like, I think the general complexity of determining the
optimal join order is known to be some horrifically non-polynomial
time thing, but there are lots of real-world problems where I think a
human being would try to do it in linear time, by initially choosing
the driving table, and then what to join to first, second, third, etc.
And I think that's the kind of case that you're trying to pursue with
this optimization, so it feels intuitively logical that something
should be possible. That said, I don't know whether from a theoretical
perspective it really is possible to do something like this in a
reliable way, making it a pure optimization, or whether you would be
doomed to always get some cases wrong, making it more like an optional
planner mode or something. Either way, I can't shake the feeling that
determining essentially every important fact about every join only
when we perform the main join search makes it a lot harder to imagine
ever avoiding the main join search.

--
Robert Haas
EDB: http://www.enterprisedb.com

#55Bruce Momjian
bruce@momjian.us
In reply to: Robert Haas (#52)
Re: should we have a fast-path planning for OLTP starjoins?

On Fri, Nov 28, 2025 at 05:50:34PM -0500, Robert Haas wrote:

I'm guessing that the reason you're limiting this to relations without
restrictions is so that you don't have to reason about the join
causing cardinality changes. But I don't quite understand how you
avoid having that problem anyway. For example, suppose that we have a
fact table F which is joined to relations S1, S2, D1, D2, I1, and I2.
The joins to S1 and S2 are joins on FKs to unconstrained dimension
tables; i.e. cardinality stays the same. The joins to D1 and D2 are
joins on FKs to constrained dimension tables, i.e. cardinality
decreases. The joins to I1 and I2 on average match more than once,
i.e. cardinality increases. The optimal join order is presumably
something like F-D1-D2-S1-S2-I1-I2, so that the number of rows flowing
through each level of the join tree is kept as small as possible, but
how do you achieve this if the joins to S1 and S2 are set aside? In
the presence of row-count-inflating joins, it's wrong to suppose that
S1 and S2 should be joined at the end.

I spend some time thinking about this email. I have a few questions.
As I see it, we are regrouping joins of a single table into three
groups:

1. restriction joins
2. neutral joins
3. expansion joins

It seems we have to identify these joins _before_ we actually start the
main optimizer. We can identify restriction joins since we see the
restriction in the query, and we can identify neutral joins because of
foreign keys. How do we identify expansion joins? Is it all the joins
which are not the previous types?

What seems more likely to be true is that we should perform the join
to S1 and the join to S2 consecutively. It's very common in my
experience for complex reporting queries to have a bunch of joins the
results of which matter very little: each one changes the cardinality
very little or not at all, and so any ordering of those joins produces
essentially the same result, and probably it's best to do them all at
whatever point in the join sequence the cardinality of the other input
is at lowest. However, I'm not sure that even this is guaranteed. For
instance, suppose that in the above example there's no index on the
column of F that joins to S2. Could it be that the only reasonable way
to join to S2 is a merge join? If so, it might be best to start by
join F to S2 using an index scan on each, and then continue by joining
to D1, D2, S1, I1, I2 in that order.

So, this got me thinking. As the optimizer runs, it doesn't choose just
the cheapest path for each stage, but retains paths with higher costs if
they have sort orders (pathkeys) that might be useful in later stages.

In the group execution order we are considering:

1. restriction joins
2. neutral joins
3. expansion joins

do we generate only the cheapest path for each group or return multiple
paths that can be considered by later group executions? If not, if we
join the same column in stages 1 & 2, would it make sense to move the
stage 2 join into stage 1 so we can potentially use sort order
(pathkeys) for both joins? Similarly if we join the same column in
stage 2 & 3 can we move the stage 2 join to stage 3? I don't think it
is worth moving stage 1 to 3 or 3 to 1 since it seems too risky.

I am sorry if this was already discussed in the patch comments.

What Robert is saying in the above paragraph is even more complex ---
that we might want to use an index on the fact table for a merge join of
a stage 2 or 3 join, and then do the other joins. How would we detect
this? Could we run each join on its own and see which ones choose merge
join, and move them to stage 1?

--
Bruce Momjian <bruce@momjian.us> https://momjian.us
EDB https://enterprisedb.com

Do not let urgent matters crowd out time for investment in the future.

#56Bruce Momjian
bruce@momjian.us
In reply to: Bruce Momjian (#55)
Re: should we have a fast-path planning for OLTP starjoins?

On Sat, Dec 20, 2025 at 05:49:24PM -0500, Bruce Momjian wrote:

What Robert is saying in the above paragraph is even more complex ---
that we might want to use an index on the fact table for a merge join of
a stage 2 or 3 join, and then do the other joins. How would we detect
this? Could we run each join on its own and see which ones choose merge
join, and move them to stage 1?

Thinking some more, how likely would we do a merge join before applying
a restrictive join?

--
Bruce Momjian <bruce@momjian.us> https://momjian.us
EDB https://enterprisedb.com

Do not let urgent matters crowd out time for investment in the future.

#57Robert Haas
robertmhaas@gmail.com
In reply to: Bruce Momjian (#55)
Re: should we have a fast-path planning for OLTP starjoins?

On Sat, Dec 20, 2025 at 5:49 PM Bruce Momjian <bruce@momjian.us> wrote:

It seems we have to identify these joins _before_ we actually start the
main optimizer. We can identify restriction joins since we see the
restriction in the query, and we can identify neutral joins because of
foreign keys. How do we identify expansion joins? Is it all the joins
which are not the previous types?

We unfortunately have no way to identify these joins before we
actually start the main optimizer; that's not how the code works. I'm
not sure if there's a reasonable way to do better, because whether the
join inflates or reduces the row count can't be known independently of
the join order in general, even though in practice it often can.

In the group execution order we are considering:

1. restriction joins
2. neutral joins
3. expansion joins

do we generate only the cheapest path for each group or return multiple
paths that can be considered by later group executions? If not, if we
join the same column in stages 1 & 2, would it make sense to move the
stage 2 join into stage 1 so we can potentially use sort order
(pathkeys) for both joins? Similarly if we join the same column in
stage 2 & 3 can we move the stage 2 join to stage 3? I don't think it
is worth moving stage 1 to 3 or 3 to 1 since it seems too risky.

I'm not sure this is what the patch is actually doing -- it's
definitely not what the current code is doing.

--
Robert Haas
EDB: http://www.enterprisedb.com

#58Bruce Momjian
bruce@momjian.us
In reply to: Robert Haas (#57)
Re: should we have a fast-path planning for OLTP starjoins?

On Wed, Dec 24, 2025 at 08:32:42AM -0500, Robert Haas wrote:

On Sat, Dec 20, 2025 at 5:49 PM Bruce Momjian <bruce@momjian.us> wrote:

It seems we have to identify these joins _before_ we actually start the
main optimizer. We can identify restriction joins since we see the
restriction in the query, and we can identify neutral joins because of
foreign keys. How do we identify expansion joins? Is it all the joins
which are not the previous types?

We unfortunately have no way to identify these joins before we
actually start the main optimizer; that's not how the code works. I'm
not sure if there's a reasonable way to do better, because whether the
join inflates or reduces the row count can't be known independently of
the join order in general, even though in practice it often can.

Okay, makes sense. Are we moving forward with this patch, or are we
considering the greedy join search algorithm as a possible better
solution to this problem?

/messages/by-id/3FF63E99-AB4F-41A9-BC78-AAB28823FBD0@Outlook.com

In the group execution order we are considering:

1. restriction joins
2. neutral joins
3. expansion joins

do we generate only the cheapest path for each group or return multiple
paths that can be considered by later group executions? If not, if we
join the same column in stages 1 & 2, would it make sense to move the
stage 2 join into stage 1 so we can potentially use sort order
(pathkeys) for both joins? Similarly if we join the same column in
stage 2 & 3 can we move the stage 2 join to stage 3? I don't think it
is worth moving stage 1 to 3 or 3 to 1 since it seems too risky.

I'm not sure this is what the patch is actually doing -- it's
definitely not what the current code is doing.

I think we have general consensus that short-circuiting queries that do
many joins to a single table, like star joins, is a valid optimization.
I guess we have to continue considering the best solution.

--
Bruce Momjian <bruce@momjian.us> https://momjian.us
EDB https://enterprisedb.com

Do not let urgent matters crowd out time for investment in the future.

#59Tom Lane
tgl@sss.pgh.pa.us
In reply to: Robert Haas (#57)
Re: should we have a fast-path planning for OLTP starjoins?

Robert Haas <robertmhaas@gmail.com> writes:

On Sat, Dec 20, 2025 at 5:49 PM Bruce Momjian <bruce@momjian.us> wrote:

It seems we have to identify these joins _before_ we actually start the
main optimizer. We can identify restriction joins since we see the
restriction in the query, and we can identify neutral joins because of
foreign keys. How do we identify expansion joins? Is it all the joins
which are not the previous types?

We unfortunately have no way to identify these joins before we
actually start the main optimizer; that's not how the code works. I'm
not sure if there's a reasonable way to do better, because whether the
join inflates or reduces the row count can't be known independently of
the join order in general, even though in practice it often can.

I think the core idea of this proposal is to improve cases where
we *can* know that; where we can't, just do what we've always done.
Not handling every case isn't a fatal objection, as long as the
patch doesn't spend much time to discover that it can't help.

Having said that, I'm starting to wonder whether "do this stuff in a
separate pass before the main optimizer" is the wrong structural
decision. Should we be injecting the logic at some later point
where we've gathered more information? At least in principle,
we should be able to build all base-relation Paths before we start
to think about join order; would having those help?

regards, tom lane

#60Tomas Vondra
tomas@vondra.me
In reply to: Tom Lane (#59)
Re: should we have a fast-path planning for OLTP starjoins?

On 12/24/25 19:16, Tom Lane wrote:

Robert Haas <robertmhaas@gmail.com> writes:

On Sat, Dec 20, 2025 at 5:49 PM Bruce Momjian <bruce@momjian.us> wrote:

It seems we have to identify these joins _before_ we actually start the
main optimizer. We can identify restriction joins since we see the
restriction in the query, and we can identify neutral joins because of
foreign keys. How do we identify expansion joins? Is it all the joins
which are not the previous types?

We unfortunately have no way to identify these joins before we
actually start the main optimizer; that's not how the code works. I'm
not sure if there's a reasonable way to do better, because whether the
join inflates or reduces the row count can't be known independently of
the join order in general, even though in practice it often can.

I think the core idea of this proposal is to improve cases where
we *can* know that; where we can't, just do what we've always done.
Not handling every case isn't a fatal objection, as long as the
patch doesn't spend much time to discover that it can't help.

Right. This was conceived as a cheap opportunistic optimization. It has
to be cheap enough to not hurt queries that don't benefit it (which may
be most queries).

Having said that, I'm starting to wonder whether "do this stuff in a
separate pass before the main optimizer" is the wrong structural
decision. Should we be injecting the logic at some later point
where we've gathered more information? At least in principle,
we should be able to build all base-relation Paths before we start
to think about join order; would having those help?

It's entirely possible doing it in a separate pass before the "regular"
join order search is the wrong approach. But if wanted to do that later,
when would that be?

I don't think doing that after building baserels would be enough. What
additional information would that give us? AFAICS we already have
RelOptInfos for baserels with all the necessary info about foreign keys,
join clauses etc. The thing we don't have is RelOptInfos for the joins,
which means we can't use join_is_legal() etc.

An idea I floated some time back is "grouping" the dimension joins into
a single "group entry", and teach join_search_one_level() to expand it
into a sequence of joins whenever it hits it. It'd still consider all
join orders of the "other" joins (some of which may increase or decrease
the join cardinality).

Would this be a better structure? It'd be later than what we do now, and
we can't really do it any later, I think.

regards

--
Tomas Vondra

#61Robert Haas
robertmhaas@gmail.com
In reply to: Tom Lane (#59)
Re: should we have a fast-path planning for OLTP starjoins?

On Wed, Dec 24, 2025 at 1:16 PM Tom Lane <tgl@sss.pgh.pa.us> wrote:

Having said that, I'm starting to wonder whether "do this stuff in a
separate pass before the main optimizer" is the wrong structural
decision. Should we be injecting the logic at some later point
where we've gathered more information? At least in principle,
we should be able to build all base-relation Paths before we start
to think about join order; would having those help?

I've been wondering for a while about making cardinality estimation a
separate pass from path construction. One reason is that we currently
come up with different row count estimates for partitionwise and
non-partitionwise paths for the same rel, which doesn't really make
sense. We could do partitionwise estimates for joins that could be
done partitionwise even if partitionwise join is not selected or even
if it is entirely disabled, and I think we'd get more accurate
estimates (as we should for baserels also). But I wonder if it might
help with this problem, too. Like, suppose we try to construct a
star-join path using some fast-path, and as we go we compute
cardinality estimates for the joinrels we consider building. At any
point, we can decide to give up, e.g. because we find a row-count
inflating join, or something that otherwise doesn't meet the criteria
for the fast path. At that point, we can fall back and do the standard
join search, and all the cardinality estimates we used are still
available and don't need to be recomputed, so the only effort we've
wasted is the effort of constructing paths for some rels. Those paths
probably do need to be discarded, unless our fast-path always computes
the full path set for each rel it considers. But being able to reuse
the cardinality estimates would limit the wasted work.

Your idea of building base-relation paths early, thus also getting
base-relation cardinality estimates, has some of the same advantages
and might be easier to implement. It would mean that we lose any join
cardinality estimates that the fast-path algorithm computes, so I
think it's probably at least modestly worse if you ignore
implementation complexity, but I can almost hear you telling me that
we cannot and should not ignore implementation complexity, which is
fair enough as far as it goes.

--
Robert Haas
EDB: http://www.enterprisedb.com