Re: slow self-join query

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On Sat, Mar 17, 2012 at 23:07, Scott Marlowe <scott.marlowe@xxxxxxxxx> wrote:
Yeah try setting [work_mem] to something absurd like 500MB and see if the plan changes.

Suweet!  Sorting now runs in-memory, and that makes a big difference, even when groveling over 1M records (under 12 seconds rather than 7 hours).  Results in

   http://explain.depesz.com/s/hNO

On Sat, Mar 17, 2012 at 23:09, Scott Marlowe <scott.marlowe@xxxxxxxxx> wrote:
Also it looks like you're still not using the index on this:

Subquery Scan u1 (cost=0.00..313.55 rows=50 width=4) (actual
time=0.030..147.136 rows=10000 loops=1)

   Filter: ((u1.type)::text = 'User::Twitter'::text)

Are you sure you're using an indexable condition?

I know that users.type is indexed -- what would keep that from being honored?  FWIW, I believe that all user.type fields are set to User::Twitter, but that will change in the future.

On Sat, Mar 17, 2012 at 23:12, Scott Marlowe <scott.marlowe@xxxxxxxxx> wrote:

Also also this looks like it's the most expensive operation:

Seq Scan on followings f2 (cost=0.00..93523.95 rows=5534395 width=8)
(actual time=0.041..19365.834 rows=5535964 loops=1)

I'm guessing the f2.follower_id isn't very selective?

Not 100% sure what you mean -- f2.follower_id is very sparse (compared to f1.follower_id), but that's the point of this particular query.  But since upping work_mem makes it run really fast, I'm not overly concerned about this one.  Thanks for your help!

One last thought: I could re-cast this as a subquery / query pair, each with a single join.  Am I correct in thinking that could make it really easy on the planner (especially if the tables were properly indexed)?

Thanks again.

- r


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