Re: Joins and DELETE FROM - Mailing list pgsql-performance
| From | Kynn Jones |
|---|---|
| Subject | Re: Joins and DELETE FROM |
| Date | |
| Msg-id | c2350ba40803081102v14d7c3f0u349fb361351fec5a@mail.gmail.com Whole thread Raw |
| In response to | Re: Joins and DELETE FROM ("Heikki Linnakangas" <heikki@enterprisedb.com>) |
| Responses |
Re: Joins and DELETE FROM
Re: Joins and DELETE FROM |
| List | pgsql-performance |
On Sat, Mar 8, 2008 at 1:01 PM, Heikki Linnakangas <heikki@enterprisedb.com> wrote:
The planner knows how to produce such a plan, so it must thinking thatKynn Jones wrote:
> Hi!
>
> As part of a data warehousing project, I need to pre-process data downloaded
> from an external source, in the form of several large flat files. This
> preprocessing entails checking the validity of various data items, and
> discarding those that fail to pass all the checks.
>
> Currently, the code that performs the checks generates intermediate
> temporary tables of those bits of data that are invalid in some way. (This
> simplifies the process of generating various quality-control reports about
> the incoming data).
>
> The next step is to weed out the bad data from the main tables, and here's
> where I begin to get lost.
>
> To be concrete, suppose I have a table T consisting of 20 million rows,
> keyed on some column K. (There are no formal constrains on T at the moment,
> but one could define column K as T's primary key.) Suppose also that I have
> a second table B (for "bad") consisting of 20 thousand rows, and also keyed
> on some column K. For each value of B.K there is exactly one row in T such
> that T.K = B.K, and the task is to delete all these rows from T as
> efficiently as possible.
>
> My naive approach would something like
>
> DELETE FROM T WHERE T.K IN ( SELECT K FROM B );
>
> ...which, according to EXPLAIN, is a terrible idea, because it involves
> sequentially scanning all 20 million rows of T just to delete about only
> 0.1% of them.
>
> It seems to me better to sequentially scan B and rely on an index on T to
> zero-in the few rows in T that must be deleted.
>
> Is this strategy something that can be done with plain SQL (even if to do
> this I must produce additional helper tables, indices, etc.), or must I
> write a stored procedure to implement it?
it's not the fastest plan.
Curious.
Have you ANALYZEd the tables? You do have an index on T.K, right? What
does EXPLAIN ANALYZE output look like? (you can do BEGIN; EXPLAIN
ANALYZE ...; ROLLBACK; if you don't want to actually delete the rows)
Yes, all the tables have been vacuumed and analyzed, and there's an index on T.K (and on also on B.K for good measure).
You can try to coerce the planner to choose the indexscan with "set
enable_seqscan=off", to see how fast it actually is.
Thanks, that was a useful trick. I tried it on a simpler case: just the natural join of T and B. (I also used smaller versions of the table, but with a size ratio similar to the one in my hypothetical example.) Indeed, when I turn off sequential scans, the resulting query is over 2X faster.
my_db=> SET ENABLE_SEQSCAN TO ON;
my_db=> EXPLAIN ANALYZE SELECT * FROM T NATURAL JOIN B;
QUERY PLAN
------------------------------------------------------------------------------------------------------------------------
Hash Join (cost=7634.14..371997.64 rows=219784 width=13) (actual time=176.065..12041.486 rows=219784 loops=1)
Hash Cond: (t.k = b.k)
-> Seq Scan on t (cost=0.00..172035.56 rows=10509456 width=13) (actual time=0.023..2379.407 rows=10509456 loops=1)
-> Hash (cost=3598.84..3598.84 rows=219784 width=12) (actual time=171.868..171.868 rows=219784 loops=1)
-> Seq Scan on b (cost=0.00..3598.84 rows=219784 width=12) (actual time=0.013..49.626 rows=219784 loops=1)
Total runtime: 12064.966 ms
(6 rows)
my_db=> SET ENABLE_SEQSCAN TO OFF;
my_db=> EXPLAIN ANALYZE SELECT * FROM T NATURAL JOIN B;
QUERY PLAN
---------------------------------------------------------------------------------------------------------------------------------------
Merge Join (cost=0.00..423589.69 rows=219784 width=13) (actual time=0.114..5449.808 rows=219784 loops=1)
Merge Cond: (t.k = b.k)
-> Index Scan using idx__t on t (cost=0.00..386463.71 rows=10509456 width=13) (actual time=0.059..3083.182 rows=10509414 loops=1)
-> Index Scan using idx__b on b (cost=0.00..8105.04 rows=219784 width=12) (actual time=0.044..69.659 rows=219784 loops=1)
Total runtime: 5473.812 ms
(5 rows)
Honestly, I still have not learned to fully decipher the output of EXPLAN/EXPLAIN ANALYZE. (The PostgreSQL docs are generally superb, IMO, but there's still a big hole on the subject of the query planner, including the interpretation of these query plans.)
So it seems like turning off ENABLE_SEQSCAN is the way to go. I wonder how much faster the query would be if I could selectively turn of the sequential scan on T. (The one on B seems to me reasonable.)
You could also write the query as DELETE FROM t USING b WHERE t.k = b.k,
but I doubt it makes much difference.
You're right: no difference at all (same query plan).
Thanks again!
Kynn
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