Concurrent CTE

On Wed, Apr 4, 2018 at 3:20 AM Artur Formella <a.formella@tme3c.com> wrote:

Hello!
We have a lot of big CTE (~40 statements, ~1000 lines) for very dynamic
OLTP content and avg response time 50-300ms. Our setup has 96 threads
(Intel Xeon Gold 6128), 256 GB RAM and 12 SSD (3 tablespaces). DB size <
RAM.
Simplifying the problem:

WITH aa as (
SELECT * FROM table1
), bb (
SELECT * FROM table2
), cc (
SELECT * FROM table3
), dd (
SELECT * FROM aa,bb
), ee (
SELECT * FROM aa,bb,cc
), ff (
SELECT * FROM ee,dd
), gg (
SELECT * FROM table4
), hh (
SELECT * FROM aa
)
SELECT * FROM gg,hh,ff /* primary statement */

Execution now:
time-->
Thread1: aa | bb | cc | dd | ee | ff | gg | hh | primary

And the question: is it possible to achieve more concurrent execution
plan to reduce the response time? For example:
Thread1: aa | dd | ff | primary
Thread2: bb | ee | gg
Thread3: cc | -- | hh

Table1, table2 and table3 are located on separate tablespaces and are
independent.
Partial results (aa,bb,cc,dd,ee) are quite big and slow (full text
search, arrays, custom collations, function scans...).

We consider resigning from the CTE and rewrite to RX Java but we are
afraid of downloading partial results and sending it back with WHERE
IN(...).

Thanks!

Artur Formella

It is very difficult from your example to tell just what kind of data you
are querying and why you are doing it this way. I will give it a try.

If you are filtering any of this data later you are fencing off that
optimization. Also in your example it makes no sense to have cte aa when
you could just cross join table1 directly in all your other ctes (and bb
and cc for the same reason).

Also in my experience, you are not going to have a great query plan with
that many CTEs. Also are you using functions or prepared statements or are
you paying the price of planning this query every time?

It is hard to tell but your example leads me to question if there are some
serious issues in your db design. Where are your joins and where are you
leveraging indexes? Also it is very easy to misuse use a raise and
function scans to even make performance worse.

Thanks,
Jeremy

On Tuesday, April 3, 2018, Artur Formella <a.formella@tme3c.com> wrote:

And the question: is it possible to achieve more concurrent execution plan
to reduce the response time? For example:
Thread1: aa | dd | ff | primary
Thread2: bb | ee | gg
Thread3: cc | -- | hh

If and how depends greatly on your version.

https://www.postgresql.org/docs/10/static/parallel-query.html

David J.

On Wed, Apr 4, 2018 at 8:01 AM, Artur Formella <a.formella@tme3c.com> wrote:

Execution now:
time-->
Thread1: aa | bb | cc | dd | ee | ff | gg | hh | primary

And the question: is it possible to achieve more concurrent execution plan
to reduce the response time? For example:
Thread1: aa | dd | ff | primary
Thread2: bb | ee | gg
Thread3: cc | -- | hh

Parallel query can't be used for CTE queries currently. Other good
things also don't happen when you use CTEs -- it's an "optimiser
fence" (though there is discussion of changing that eventually).
Maybe try rewriting your query as:

SELECT ...
FROM (SELECT ...) AS aa,
(SELECT ...) AS bb,
...

Note that in the form of parallelism supported in PostgreSQL 10, every
process (we use processes instead of threads) runs the same execution
plan at the same time, but gives each worker only a part of the
problem using disk block granularity, so it looks more like this:

Process1: fragments of aa | fragments of bb | ...
Process2: fragments of aa | fragments of bb | ...

PostgreSQL 11 (not yet released) will introduce an exception that
looks more like what you showed: the Parallel Append operator (for
unions and scans of partitions) can give each worker a different part
of the plan approximately as you showed, but IIUC that's used as a
fallback strategy when it can't use block granularity (because of
technical restrictions). The problem with sub-plan granularity is
that the various sub-plans can finish at different times leaving some
CPU cores with nothing to do while others are still working, whereas
block granularity keeps everyone busy until the work is done and
should finish faster.

--
Thomas Munro
http://www.enterprisedb.com

On Wed, Apr 4, 2018 at 10:12 PM, Thomas Munro <thomas.munro@enterprisedb.com

wrote:

Parallel query can't be used for CTE queries currently.

​A pointer to the location in the docs covering this limitation would be
appreciated. It isn't covered here:

https://www.postgresql.org/docs/10/static/when-can-parallel-query-be-used.html

David J.

On Thu, Apr 5, 2018 at 5:16 PM, David G. Johnston
<david.g.johnston@gmail.com> wrote:

On Wed, Apr 4, 2018 at 10:12 PM, Thomas Munro
<thomas.munro@enterprisedb.com> wrote:

Parallel query can't be used for CTE queries currently.

A pointer to the location in the docs covering this limitation would be
appreciated. It isn't covered here:

https://www.postgresql.org/docs/10/static/when-can-parallel-query-be-used.html

https://www.postgresql.org/docs/10/static/parallel-safety.html

--
Thomas Munro
http://www.enterprisedb.com

Did you look at this approach using dblink already?

https://gist.github.com/mjgleaso/8031067

In your situation, you will have to modify the example but it may give an idea where to start.

Klaus

Can you pass full query & how many rows each table has & how often the
tables change & full explain ?

On Thu, Apr 5, 2018 at 8:01 AM, <kpi6288@gmail.com> wrote: