Re: Slow Planning Times

["David G. Johnston" <david.g.johnston@xxxxxxxxx>]

On Wed, Apr 6, 2022 at 5:27 PM Saurabh Sehgal <saurabh.r.s@xxxxxxxxx> wrote:

I have the following query:

 explain (analyze, costs, timing) SELECT  rr.* FROM rpc rpc

                       INNER JOIN rr rr

                           ON rr.uuid = rpc.rr_id

                       INNER JOIN rs rs

                           ON rs.r_id = rpc.r_id

                       INNER JOIN role r

                           ON r.uuid = rs.r_id

                       LEFT JOIN spc spc

                           ON spc.rr_id = rpc.rr_id

                   WHERE rs.s_id = 'caa767b8-8371-43a3-aa11-d1dba1893601' 

                       and spc.s_id  = 'caa767b8-8371-43a3-aa11-d1dba1893601' 

                       and spc.rd_id  = '9f33c45a-90c2-4e05-a42e-048ec1f2b2fa'

                       AND rpc.rd_id = '9f33c45a-90c2-4e05-a42e-048ec1f2b2fa'

                       AND rpc.c_id = '9fd29fdc-15fd-40bb-b85d-8cfe99734987'

                       and spc.c_id  = '9fd29fdc-15fd-40bb-b85d-8cfe99734987'

                       AND rr.b_id = 'xyz'

                       AND (('GLOBAL' = ' NO_PROJECT_ID + "' ) OR (rr.p_id = 'GLOBAL'))

                       AND spc.permission_type IS null and spc.is_active  = true

                       AND rpc.is_active = true AND rr.is_active = true AND rs.is_active = true AND r.is_active = true 

I don't think it is super complex. But when I run explain analyze on this I get the following:

Planning Time: 578.068 ms
Execution Time: 0.113 ms

This is a huge deviation in planning vs. execution times. The explain plan looks good since the execution time is < 1ms. It doesn't matter though since the planning time is high. I don't see anything in the explain analyze output that tells me why the planning time is high. On average, the tables being joined have 3 indexes/table. How can I debug this?

Been stuck on this for weeks. Any help is appreciated. Thank you!

The fundamental issue here is that you have basically 12 conditions across 5 tables that need to be evaluated to determine which one of the 1,680 possible join orders is the most efficient.  The fact that you have 5 is_active checks and 3 pairs of matching UUID checks seems odd and if you could reduce those 11 to 4 I suspect you'd get a better planning time.  Though it also may produce an inferior plan...thus consider the following option:

Assuming the ideal plan shape for your data doesn't change you can read the following and basically tell the planner to stop trying so hard and just trust the join order that exists in the query.

https://www.postgresql.org/docs/current/explicit-joins.html

Lastly, if you can leverage prepared statements you can at least amortize the cost (depending on whether a generic plan performs sufficiently quickly).

I'll admit I'm no expert at this.  I'd probably just follow the join_collapse_limit advice and move on if it works.  Maybe adding a periodic check to see if anything has changed.

David J.