Very slow queries w/ NOT IN preparation (seems like a bug, test case)

Sergey Konoplev wrote:

I've faced strange parser (or may be planner) behaviour. When I do
"EXPLAIN SELECT 1 FROM table1 WHERE table1_id IN (...~2000 ids
here...);" it works as fast as I expect (50 ms). But when I rewrite it
using NOT IN "EXPLAIN SELECT 1 FROM table1 WHERE table1_id NOT IN
(...~2000 ids here...);" it gets much more slower (34537 ms).

Can you post the EXPLAIN ANALYSE output from your NOT IN query?

--
Richard Huxton
Archonet Ltd

Can you post the EXPLAIN ANALYSE output from your NOT IN query?

Seq Scan on table1 (cost=0.00..12648.25 rows=3351 width=0) (actual
time=0.054..140.596 rows=5000 loops=1)
Filter: (table1_id <> ALL ('{123456789000, ... plus 1999 ids'::bigint[]))
Total runtime: 142.303 ms
(3 rows)

But actual (real) time of running "EXPLAIN SELECT 1 FROM table1 WHERE
table1_id NOT IN > (...~2000 ids here...);" is

2000 ids: 34102 ms

--
Regards,
Sergey Konoplev
--
PostgreSQL articles in english & russian
http://gray-hemp.blogspot.com/search/label/postgresql/

Sergey Konoplev wrote:

Can you post the EXPLAIN ANALYSE output from your NOT IN query?

Seq Scan on table1 (cost=0.00..12648.25 rows=3351 width=0) (actual
time=0.054..140.596 rows=5000 loops=1)
Filter: (table1_id <> ALL ('{123456789000, ... plus 1999 ids'::bigint[]))
Total runtime: 142.303 ms
(3 rows)

But actual (real) time of running "EXPLAIN SELECT 1 FROM table1 WHERE
table1_id NOT IN > (...~2000 ids here...);" is

2000 ids: 34102 ms

I've never heard of EXPLAIN ANALYSE being *faster* than the actual
query, it's usually slower due to all the timing calls. The only thing
it doesn't do is actually send the results over the connection to the
client. In your case, you're not actually selecting any columns, so that
can't be it.

Are you sure there's nothing subtly different about the slow query when
compared with the explain analyse?

--
Richard Huxton
Archonet Ltd

Richard Huxton <dev@archonet.com> writes:

I've never heard of EXPLAIN ANALYSE being *faster* than the actual
query, it's usually slower due to all the timing calls. The only thing
it doesn't do is actually send the results over the connection to the
client. In your case, you're not actually selecting any columns, so that
can't be it.

If I'm reading it right the query returns 5000 instances of "1". So
there's definitely scope for the client side to pose a performance
issue.

regards, tom lane

Tom Lane wrote:

Richard Huxton <dev@archonet.com> writes:

I've never heard of EXPLAIN ANALYSE being *faster* than the actual
query, it's usually slower due to all the timing calls. The only thing
it doesn't do is actually send the results over the connection to the
client. In your case, you're not actually selecting any columns, so that
can't be it.

If I'm reading it right the query returns 5000 instances of "1". So
there's definitely scope for the client side to pose a performance
issue.

But 34s for 5000 single values? Surely you'd loads of queries slow, not
just this "not in" query.

--
Richard Huxton
Archonet Ltd

I've never heard of EXPLAIN ANALYSE being *faster* than the actual
query, it's usually slower due to all the timing calls. The only thing
it doesn't do is actually send the results over the connection to the
client. In your case, you're not actually selecting any columns, so that
can't be it.

Are you sure there's nothing subtly different about the slow query when
compared with the explain analyse?

Sorry, but it seems like you didn't understand the problem.

The thing is that

EXPLAIN (without ANALYZE) ... NOT IN (a lot of values)

works very slow but

EXPLAIN (without ANALYZE) ... IN (a lot of values)

works fast.

Just run the test script I attached.

--
Regards,
Sergey Konoplev
--
PostgreSQL articles in english & russian
http://gray-hemp.blogspot.com/search/label/postgresql/

"Sergey Konoplev" <gray.ru@gmail.com> writes:

I've faced strange parser (or may be planner) behaviour. When I do
"EXPLAIN SELECT 1 FROM table1 WHERE table1_id IN (...~2000 ids
here...);" it works as fast as I expect (50 ms). But when I rewrite it
using NOT IN "EXPLAIN SELECT 1 FROM table1 WHERE table1_id NOT IN
(...~2000 ids here...);" it gets much more slower (34537 ms).

FWIW, I can't reproduce your problem here. The output from your
script looks like this:

------------------------------------------
Testing EXPLAIN w/ NOT IN...
------------------------------------------
100 ids: 16 ms
200 ids: 17 ms
300 ids: 17 ms
400 ids: 18 ms
500 ids: 19 ms
600 ids: 20 ms
700 ids: 21 ms
800 ids: 22 ms
900 ids: 23 ms
1000 ids: 24 ms
1100 ids: 25 ms
1200 ids: 25 ms
1300 ids: 26 ms
1400 ids: 28 ms
1500 ids: 28 ms
1600 ids: 29 ms
1700 ids: 30 ms
1800 ids: 31 ms
1900 ids: 32 ms
2000 ids: 33 ms

------------------------------------------
Testing EXPLAIN w/ IN...
------------------------------------------
100 ids: 16 ms
200 ids: 17 ms
300 ids: 18 ms
400 ids: 19 ms
500 ids: 20 ms
600 ids: 21 ms
700 ids: 22 ms
800 ids: 23 ms
900 ids: 24 ms
1000 ids: 25 ms
1100 ids: 26 ms
1200 ids: 27 ms
1300 ids: 29 ms
1400 ids: 29 ms
1500 ids: 31 ms
1600 ids: 32 ms
1700 ids: 32 ms
1800 ids: 34 ms
1900 ids: 35 ms
2000 ids: 36 ms

regards, tom lane

I've never heard of EXPLAIN ANALYSE being *faster* than the actual
query, it's usually slower due to all the timing calls. The only thing
it doesn't do is actually send the results over the connection to the
client. In your case, you're not actually selecting any columns, so that
can't be it.

If I'm reading it right the query returns 5000 instances of "1". So
there's definitely scope for the client side to pose a performance
issue.

Query doesn't return 5000 instances of "1".

It returns just few rows of EXPLAIN output cos I do

EXPLAIN (without ANALYZE) ... NOT IN (a lot of values)

(pay attention to NOT IN)

And it works extremly slow oposite to

EXPLAIN (without ANALYZE) ... IN (a lot of values)

which works fast.

That is the main problem.

Another thing is that even I set statement_timeout to 20s the query
with NOT IN finishes working after 30+ seconds without "canceled by
statement timeout" error.

--
Regards,
Sergey Konoplev
--
PostgreSQL articles in english & russian
http://gray-hemp.blogspot.com/search/label/postgresql/

Sergey Konoplev wrote:

I've never heard of EXPLAIN ANALYSE being *faster* than the actual
query, it's usually slower due to all the timing calls. The only thing
it doesn't do is actually send the results over the connection to the
client. In your case, you're not actually selecting any columns, so that
can't be it.

Are you sure there's nothing subtly different about the slow query when
compared with the explain analyse?

Sorry, but it seems like you didn't understand the problem.

The thing is that

EXPLAIN (without ANALYZE) ... NOT IN (a lot of values)

works very slow but

EXPLAIN (without ANALYZE) ... IN (a lot of values)

works fast.

It's the EXPLAIN that you're finding slow? Hold on... not seeing it here.

------------------------------------------
Testing EXPLAIN w/ NOT IN...
------------------------------------------
100 ids: 95 ms
200 ids: 15 ms
300 ids: 17 ms
400 ids: 19 ms
500 ids: 20 ms
600 ids: 21 ms
700 ids: 23 ms
800 ids: 27 ms
900 ids: 26 ms
1000 ids: 27 ms
1100 ids: 29 ms
1200 ids: 30 ms
1300 ids: 33 ms
1400 ids: 45 ms
1500 ids: 35 ms
1600 ids: 37 ms
1700 ids: 39 ms
1800 ids: 40 ms
1900 ids: 42 ms
2000 ids: 44 ms

------------------------------------------
Testing EXPLAIN w/ IN...
------------------------------------------
100 ids: 15 ms
200 ids: 16 ms
300 ids: 17 ms
400 ids: 20 ms
500 ids: 21 ms
600 ids: 23 ms
700 ids: 25 ms
800 ids: 27 ms
900 ids: 28 ms
1000 ids: 33 ms
1100 ids: 32 ms
1200 ids: 34 ms
1300 ids: 35 ms
1400 ids: 38 ms
1500 ids: 39 ms
1600 ids: 41 ms
1700 ids: 43 ms
1800 ids: 48 ms
1900 ids: 47 ms
2000 ids: 48 ms

--
Richard Huxton
Archonet Ltd

Sergey Konoplev wrote:

Another thing is that even I set statement_timeout to 20s the query
with NOT IN finishes working after 30+ seconds without "canceled by
statement timeout" error.

Maybe it's not taking that long to execute the query then.

Maybe something to do with process startup is delaying things - could
you tweak the test script to send the outputs of the explain somewhere
other than /dev/null? That way we'd know if there was a big difference
between query-execution-time and process-execution-time.

--
Richard Huxton
Archonet Ltd

Hi Sergey,

- It's just guess but it could be the range of a SERIAL TYPE that is
generating this behavior.
An example is:
Knowing that "table1_id" is primary a key ( the table will be ordered
by it ) and that a serial range is 2147483647 long.

(a) you use 2000 different numbers of this range the planner will search for
the 2000 numbers in yours 5000 rows in an ordered way and it will stop when
the searched number can't be found any more. It will make, in the worst
case, 2000*log(5000) tests ( aprox: 24.575 ).
(b) If you use "~2000" different numbers and the system understands that you
want that the rest of the range ( 2147481647 numbers ) have to be searched
and it will cost 263.876.368.186 tests.

On Tue, Nov 11, 2008 at 12:20 PM, Richard Huxton <dev@archonet.com> wrote:

Sergey Konoplev wrote:

Another thing is that even I set statement_timeout to 20s the query
with NOT IN finishes working after 30+ seconds without "canceled by
statement timeout" error.

Maybe it's not taking that long to execute the query then.

Maybe something to do with process startup is delaying things - could
you tweak the test script to send the outputs of the explain somewhere
other than /dev/null? That way we'd know if there was a big difference
between query-execution-time and process-execution-time.

--
Richard Huxton
Archonet Ltd

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--
Helio Campos Mello de Andrade

Sergey Konoplev wrote:

Maybe something to do with process startup is delaying things - could
you tweak the test script to send the outputs of the explain somewhere
other than /dev/null? That way we'd know if there was a big difference
between query-execution-time and process-execution-time.

I did \timing and run my query in console. You can find the result in
attachement. Will it be enough?

Very strange.

The explain runtime is 3.1 seconds, but \timing shows 37.8 seconds
before it returns.

And it only does this for the NOT IN version of the query, but the IN
version seems OK.

The two together make no sense to me.

If you do the same again but "\o /dev/null" before the /timing, is it
still slow?
If not, what about "\o /tmp/results.txt"?

That should rule out something strange with displaying a very long line
(and I admit I'm reduced to wild guesses now).

If you run it over the network, can you try running it directly on the
server?

Finally - did you compile this from source yourself, or is it installed
via apt? I'm wondering whether you have an unusual version of a library
linked in, and it's taking a long time to parse the query.

Actually, we can test that. If you run the same query against an empty
table, does it take more than a few milliseconds?

--
Richard Huxton
Archonet Ltd

I did \timing and run my query in console. You can find the result in
attachement. Will it be enough?

Very strange.

The explain runtime is 3.1 seconds, but \timing shows 37.8 seconds
before it returns.

And it only does this for the NOT IN version of the query, but the IN
version seems OK.

Exactly.

The two together make no sense to me.

If you do the same again but "\o /dev/null" before the /timing, is it
still slow?

Unfortunaly it is.
\o /dev/null
Time: 38337,644 ms

If not, what about "\o /tmp/results.txt"?

The same.
Time: 37631,055 ms

That should rule out something strange with displaying a very long line
(and I admit I'm reduced to wild guesses now).

I had that wild guess too and tested it after separating ID's list to
10 per line but result is the same.

If you run it over the network, can you try running it directly on the
server?

I'm running it directly on my machine. But I tested it remotely too.

Finally - did you compile this from source yourself, or is it installed
via apt? I'm wondering whether you have an unusual version of a library
linked in, and it's taking a long time to parse the query.

I've compiled it from sources. BTW, I tested it on both 8.3.3 and 8.3.4.

Actually, we can test that. If you run the same query against an empty
table, does it take more than a few milliseconds?

Yes it does. Nothing has changed.

--
Regards,
Sergey Konoplev
--
PostgreSQL articles in english & russian
http://gray-hemp.blogspot.com/search/label/postgresql/

Sergey Konoplev wrote:

Finally - did you compile this from source yourself, or is it installed
via apt? I'm wondering whether you have an unusual version of a library
linked in, and it's taking a long time to parse the query.

I've compiled it from sources. BTW, I tested it on both 8.3.3 and 8.3.4.

Hmm - nothing unusual about your setup, I suppose?

Actually, we can test that. If you run the same query against an empty
table, does it take more than a few milliseconds?

Yes it does. Nothing has changed.

So it *must* be something in the planner/parser/explain code, and
something specific to your setup.

If you connect via psql and then (as root, in another terminal) do:
ps auxw | grep postgres
you should see the backend that corresponds to your psql connection.
strace -p <pid>
should then show system calls as they are executed (assuming you have it
installed). Execute the explain, and see what is output.

Mine flies past, but is composed almost entirely of "gettimeofday" calls
(10,000 of them) apart from at the very end where we get some write and
send/recv calls (to print the explain results). I've heard of some
people having slow "gettimeofday" calls, but not on linux. On the other
hand, that seems to be the main difference between strace output with
"not in" compared to "in".

--
Richard Huxton
Archonet Ltd

Por favor, no quiero seguir recibiendo mensajes

Tom Lane escribió:

Richard Huxton <dev@archonet.com> writes:

If you connect via psql and then (as root, in another terminal) do:
ps auxw | grep postgres
you should see the backend that corresponds to your psql connection.
strace -p <pid>
should then show system calls as they are executed (assuming you have it
installed). Execute the explain, and see what is output.

Mine flies past, but is composed almost entirely of "gettimeofday" calls
(10,000 of them) apart from at the very end where we get some write and
send/recv calls (to print the explain results). I've heard of some
people having slow "gettimeofday" calls, but not on linux. On the other
hand, that seems to be the main difference between strace output with
"not in" compared to "in".

AFAICT Sergey is complaining about the speed of EXPLAIN, *not* EXPLAIN
ANALYZE. There'd only be a lot of gettimeofday calls in an EXPLAIN
ANALYZE test.

The whole thing doesn't make a lot of sense to me either. All the
slowdown explanations I can think of would apply as much or more to the
IN case...

regards, tom lane

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"Sergey Konoplev" <gray.ru@gmail.com> writes:

Finally - did you compile this from source yourself, or is it installed
via apt? I'm wondering whether you have an unusual version of a library
linked in, and it's taking a long time to parse the query.

I've compiled it from sources. BTW, I tested it on both 8.3.3 and 8.3.4.

What configure options did you use, what locale/encoding are you using,
what nondefault settings have you got in postgresql.conf?

regards, tom lane

Richard Huxton <dev@archonet.com> writes:

If you connect via psql and then (as root, in another terminal) do:
ps auxw | grep postgres
you should see the backend that corresponds to your psql connection.
strace -p <pid>
should then show system calls as they are executed (assuming you have it
installed). Execute the explain, and see what is output.

Mine flies past, but is composed almost entirely of "gettimeofday" calls
(10,000 of them) apart from at the very end where we get some write and
send/recv calls (to print the explain results). I've heard of some
people having slow "gettimeofday" calls, but not on linux. On the other
hand, that seems to be the main difference between strace output with
"not in" compared to "in".

AFAICT Sergey is complaining about the speed of EXPLAIN, *not* EXPLAIN
ANALYZE. There'd only be a lot of gettimeofday calls in an EXPLAIN
ANALYZE test.

The whole thing doesn't make a lot of sense to me either. All the
slowdown explanations I can think of would apply as much or more to the
IN case...

regards, tom lane

What configure options did you use, what locale/encoding are you using,
what nondefault settings have you got in postgresql.conf?

regards, tom lane

You are right. I've found the odd thing (that completely drives me
mad) in postgresql.conf.

You are able to reproduce slow-not-in queries by switching
constraint_exclusion to on in your postgresql.conf and running my test
(which is attached to the first message).

Looking forward to hearing from you.

--
Regards,
Sergey Konoplev
--
PostgreSQL articles in english & russian
http://gray-hemp.blogspot.com/search/label/postgresql/

What configure options did you use, what locale/encoding are you using,
what nondefault settings have you got in postgresql.conf?

regards, tom lane

You are right. I've found the odd thing (that completely drives me
mad) in postgresql.conf.

You are able to reproduce slow-not-in queries by switching
constraint_exclusion to on in your postgresql.conf and running my test
(which is attached to the first message).

On more thing:

If you do

EXPLAIN SELECT 1 FROM table1 WHERE table1_id NOT IN (SELECT column1
FROM (VALUES (123),(456),(789),... a lot of IDs here...)_);

it works as fast as with constraint_exclusion turned to off.

--
Regards,
Sergey Konoplev
--
PostgreSQL articles in english & russian
http://gray-hemp.blogspot.com/search/label/postgresql/

"Sergey Konoplev" <gray.ru@gmail.com> writes:

You are right. I've found the odd thing (that completely drives me
mad) in postgresql.conf.

You are able to reproduce slow-not-in queries by switching
constraint_exclusion to on in your postgresql.conf and running my test
(which is attached to the first message).

Hmph. It's trying to see if the NOT IN condition is self-contradictory,
which of course it isn't, but the predicate_refuted_by machinery isn't
smart enough to determine that except by running through all N^2
combinations of the individual x <> const conditions :-(.

(It's not really any smarter about the IN case either, but that only
takes constant time not O(N^2) because it will stop after finding that
the first equality condition doesn't refute itself.)

We could respond to this in a number of ways:

1. "Tough, don't do that."

2. Put some arbitrary limit on the number of subconditions in an AND or
OR clause before we give up and don't attempt to prove anything about
it.

3. Put in a narrow hack that will get us out of this specific case,
but might still allow very slow proof attempts in other large cases.

The specific narrow hack I'm considering for #3 goes like this: in this
case, we repeatedly pass btree_predicate_proof two clauses "x <> const1"
and "x <> const2", and after some fairly expensive probing of the system
catalogs it finds out that there's no way to prove that the former
refutes the latter. But when considering two ScalarArrayOps, the two
operators will be the same for all of the sub-clauses, and so we could
check once to find out that we can't refute anything. (It also seems
interesting to cache that catalog lookup in cases where we might be able
to prove something.)

Comments?

regards, tom lane

Sergey Konoplev wrote:

What configure options did you use, what locale/encoding are you using,
what nondefault settings have you got in postgresql.conf?

regards, tom lane

You are right. I've found the odd thing (that completely drives me
mad) in postgresql.conf.

You are able to reproduce slow-not-in queries by switching
constraint_exclusion to on in your postgresql.conf and running my test
(which is attached to the first message).

On more thing:

If you do

EXPLAIN SELECT 1 FROM table1 WHERE table1_id NOT IN (SELECT column1
FROM (VALUES (123),(456),(789),... a lot of IDs here...)_);

it works as fast as with constraint_exclusion turned to off.

Good detective work sir! I can reproduce the problem here with
constraint_exclusion = on.

Presumably what it's doing is looking to see if the target table has any
relevant CHECK constraints for each of the 2000 values provided. It
won't do so for the second example because it's not smart enough to look
into the results of another select clause.

Hmm - a little bit of grepping...
backend/optimizer/util/plancat.c
566:relation_excluded_by_constraints(PlannerInfo *root
called from
backend/optimizer/path/allpaths.c

You could presumably cache the results of the exclusion test, but that's
only going to be relevant where you have the same value more than once.
You could try to be smarter and evaluate all values in one go I suppose,
or limit how many you'll test against. I'm over my head here though -
you'll have to see what Tom says.

The good news is that you can just issue "SET constraint_exclusion"
before individual queries as a temporary workaround.

--
Richard Huxton
Archonet Ltd

Tom Lane wrote:

"Sergey Konoplev" <gray.ru@gmail.com> writes:

You are right. I've found the odd thing (that completely drives me
mad) in postgresql.conf.

You are able to reproduce slow-not-in queries by switching
constraint_exclusion to on in your postgresql.conf and running my test
(which is attached to the first message).

Hmph. It's trying to see if the NOT IN condition is self-contradictory,
which of course it isn't, but the predicate_refuted_by machinery isn't
smart enough to determine that except by running through all N^2
combinations of the individual x <> const conditions :-(.

So it's not checking the table, it's looking to see whether <clause1> OR
<clause2> end up excluding each other? Presumably becuase "OR" is just
another operator?

We could respond to this in a number of ways:

1. "Tough, don't do that."

2. Put some arbitrary limit on the number of subconditions in an AND or
OR clause before we give up and don't attempt to prove anything about
it.

Do we know the estimated cost of just executing the planner-node at this
point? You could scale with the cost of actually doing the tests.

3. Put in a narrow hack that will get us out of this specific case,
but might still allow very slow proof attempts in other large cases.

The specific narrow hack I'm considering for #3 goes like this:

The specific hack goes right over my head :-)

--
Richard Huxton
Archonet Ltd

Richard Huxton <dev@archonet.com> writes:

Tom Lane wrote:

Hmph. It's trying to see if the NOT IN condition is self-contradictory,
which of course it isn't, but the predicate_refuted_by machinery isn't
smart enough to determine that except by running through all N^2
combinations of the individual x <> const conditions :-(.

So it's not checking the table, it's looking to see whether <clause1> OR
<clause2> end up excluding each other? Presumably becuase "OR" is just
another operator?

Yeah. An example of a closely related expression that it *would* be
able to prove self-contradictory is
WHERE x = ALL (ARRAY[1, 2, ...])
or perhaps slightly more realistically
WHERE x = ANY (ARRAY[1, 2, 3]) AND x > 4

The NOT IN is equivalent to
WHERE x <> ALL (ARRAY[1, 2, ...])
which can't be proved false. (Well, it could if x is of a finite domain
and all the possible values are listed, but we aren't gonna check for
that.) So you can see that some fairly close analysis is needed to
determine whether anything can be done or not.

2. Put some arbitrary limit on the number of subconditions in an AND or
OR clause before we give up and don't attempt to prove anything about
it.

Do we know the estimated cost of just executing the planner-node at this
point? You could scale with the cost of actually doing the tests.

No, this is long before we've developed any cost estimates.

regards, tom lane

On Thu, Nov 13, 2008 at 4:52 AM, Tom Lane <tgl@sss.pgh.pa.us> wrote:

Yeah. An example of a closely related expression that it *would* be
able to prove self-contradictory is
WHERE x = ALL (ARRAY[1, 2, ...])
or perhaps slightly more realistically
WHERE x = ANY (ARRAY[1, 2, 3]) AND x > 4

It seems like the cure is worse than the disease here. Surely a user
who has a self-contradictory clause will realise the problem pretty
quickly (i.e., when he receives zero rows) and then just fix it.

I guess my question is, what's the real benefit of going to all this
trouble trying to prove that clauses are false? What real-world
problem does it address?

Cheers,
BJ

"Brendan Jurd" <direvus@gmail.com> writes:

I guess my question is, what's the real benefit of going to all this
trouble trying to prove that clauses are false?

Not having to scan gigabytes of data in an excluded partition, for
instance.

Now the docs do say

Currently, constraint_exclusion is disabled by default because
the constraint checks are relatively expensive, and in many
circumstances will yield no savings. It is recommended to turn
this on only if you are actually using partitioned tables
designed to take advantage of the feature.

so we could argue that it's the OP's own fault if he turns this option
on for queries where long planning time isn't worth the trouble.

regards, tom lane

Brendan Jurd wrote:

On Thu, Nov 13, 2008 at 4:52 AM, Tom Lane <tgl@sss.pgh.pa.us> wrote:

Yeah. An example of a closely related expression that it *would* be
able to prove self-contradictory is
WHERE x = ALL (ARRAY[1, 2, ...])
or perhaps slightly more realistically
WHERE x = ANY (ARRAY[1, 2, 3]) AND x > 4

It seems like the cure is worse than the disease here. Surely a user
who has a self-contradictory clause will realise the problem pretty
quickly (i.e., when he receives zero rows) and then just fix it.

I guess my question is, what's the real benefit of going to all this
trouble trying to prove that clauses are false? What real-world
problem does it address?

Constraint exclusion partitioning?

Which brings to mind an interesting customer case. They are running
queries like "WHERE id IN (...)", where ... is a *very* long list of
keys, against a table that's partitioned by ranges of id. The query was
running slow, because while constraint exclusion was able to eliminate
completely useless partitions, if there was even one id in the list that
falls into a given partition, the partition was probed for *all* of the
ids, even those that belong to other partitions. Ideally, we would not
only prove/refute the whole "x = ANY" expression, but individual values
within it.

Actually, the long list of keys was obtained by running another query
first. They originally had a single query with a join, but they split it
to two queries because constraint exclusion doesn't work at run-time..

--
Heikki Linnakangas
EnterpriseDB http://www.enterprisedb.com

On Thu, Nov 13, 2008 at 5:16 AM, Tom Lane <tgl@sss.pgh.pa.us> wrote:

"Brendan Jurd" <direvus@gmail.com> writes:

I guess my question is, what's the real benefit of going to all this
trouble trying to prove that clauses are false?

Not having to scan gigabytes of data in an excluded partition, for
instance.

[after RTFMing ...]

The docs also say:

"When this parameter is on, the planner compares query conditions with
table CHECK constraints, and omits scanning tables for which the
conditions contradict the constraints."

I would normally interpret the above to mean that the planner *only*
performs these checks where a table CHECK constraint is relevant. I
dug up the original test case posted by Sergey, and his test table
didn't have any CHECK constraint on it at all (unless you count the
NOT NULL implied by PRIMARY KEY).

Cheers,
BJ

I wrote:

We could respond to this in a number of ways:

1. "Tough, don't do that."

2. Put some arbitrary limit on the number of subconditions in an AND or
OR clause before we give up and don't attempt to prove anything about
it.

3. Put in a narrow hack that will get us out of this specific case,
but might still allow very slow proof attempts in other large cases.

The specific narrow hack I'm considering for #3 goes like this: in this
case, we repeatedly pass btree_predicate_proof two clauses "x <> const1"
and "x <> const2", and after some fairly expensive probing of the system
catalogs it finds out that there's no way to prove that the former
refutes the latter. But when considering two ScalarArrayOps, the two
operators will be the same for all of the sub-clauses, and so we could
check once to find out that we can't refute anything. (It also seems
interesting to cache that catalog lookup in cases where we might be able
to prove something.)

I find that it's not too hard to cache the operator lookup stuff, and
that helps some, but putting in a short-circuit path to make the test
only once for a ScalarArrayOpExpr is a lot harder than I expected. The
problem is the double recursion in predicate_refuted_by_recurse --- you
can stop the recursion when you are looking at two ScalarArrayOpExprs
at the same time, but that only shuts off one of three recursion paths
that are going to end up iterating over the lists.

So option #2 with a cutoff of 100 items or so is looking like the
best response.

Thoughts?

regards, tom lane

Heikki Linnakangas <heikki.linnakangas@enterprisedb.com> writes:

Which brings to mind an interesting customer case. They are running
queries like "WHERE id IN (...)", where ... is a *very* long list of
keys, against a table that's partitioned by ranges of id. The query was
running slow, because while constraint exclusion was able to eliminate
completely useless partitions, if there was even one id in the list that
falls into a given partition, the partition was probed for *all* of the
ids, even those that belong to other partitions. Ideally, we would not
only prove/refute the whole "x = ANY" expression, but individual values
within it.

Actually, the long list of keys was obtained by running another query
first. They originally had a single query with a join, but they split it
to two queries because constraint exclusion doesn't work at run-time..

Yeah, at some point (after we have an explicit notion of partitioning in
the system, instead of the current build-it-from-spare-parts approach)
we ought to look at managing this stuff at runtime rather than expecting
that exclusion can be proven at plan time. In particular a plan type
that acted like an indexscan across the whole partitioned table (select
proper partition, then indexscan) would be real handy.

regards, tom lane

I wrote:

2. Put some arbitrary limit on the number of subconditions in an AND or
OR clause before we give up and don't attempt to prove anything about
it.

So option #2 with a cutoff of 100 items or so is looking like the
best response.

I've applied a patch along this line to 8.2 and up, and also installed
some code (in HEAD only) to cache the results of proof-operator lookup.

regards, tom lane