Re: Slow SELECT by primary key? Postgres 9.1.2

Thanks again.

Well, I have two problems with using the CLUSTER option. It's only temporary since any updates, depending how much free space is reserved per page, requires re-running the CLUSTER. And my primary concern is that it arbitrarily gives an unfair advantage to the primary key SELECT. Still, it's easy to test so here are the results. The primary key still looses even with the CLUSTER. Granted it is close but considering this is now an unfair comparison it still doesn't make sense to me. How can a search for a specific row that should be fairly straight forward take longer than a search that includes an ORDER BY clause?

test=# CLUSTER test_select USING test_select_pkey ;

CLUSTER

test=# VACUUM ANALYZE test_select ;

VACUUM

(stopped postgres; reset O/S cache; started postgres)

test=# explain analyze SELECT * FROM test_select WHERE key1 >= 500000 ORDER BY key1, key2, key3, id LIMIT 1;

                                                              QUERY PLAN

--------------------------------------------------------------------------------------------------------------------------------------

 Limit  (cost=0.00..0.08 rows=1 width=21) (actual time=19.430..19.431 rows=1 loops=1)

   ->  Index Scan using my_key on test_select  (cost=0.00..41938.15 rows=499992 width=21) (actual time=19.428..19.428 rows=1 loops=1)

         Index Cond: (key1 >= 500000)

 Total runtime: 19.526 ms

(stopped postgres; reset O/S cache; started postgres)

test=# explain analyze SELECT * FROM test_select WHERE id = 500000;

                                                           QUERY PLAN                                                            

---------------------------------------------------------------------------------------------------------------------------------

 Index Scan using test_select_pkey on test_select  (cost=0.00..8.36 rows=1 width=21) (actual time=21.070..21.072 rows=1 loops=1)

   Index Cond: (id = 500000)

 Total runtime: 21.178 ms

On Mon, May 27, 2013 at 10:59 AM, Evgeny Shishkin <itparanoia@gmail.com> wrote:

On May 27, 2013, at 6:35 PM, John Mudd <johnbmudd@gmail.com> wrote:

Thanks, that's easy enough to test. Didn't seem to help though.

Ok. And if you CLUSTER tables USING PK?

test=# REINDEX index test_select_pkey;

REINDEX

test=# VACUUM ANALYZE test_select ;

VACUUM

(stopped postgres; reset O/S cache; started postgres)

test=# explain analyze SELECT * FROM test_select WHERE key1 >= 500000 ORDER BY key1, key2, key3, id LIMIT 1;

                                                              QUERY PLAN                                                              

--------------------------------------------------------------------------------------------------------------------------------------

 Limit  (cost=0.00..0.08 rows=1 width=21) (actual time=16.368..16.369 rows=1 loops=1)

   ->  Index Scan using my_key on test_select  (cost=0.00..41981.16 rows=501333 width=21) (actual time=16.366..16.366 rows=1 loops=1)

         Index Cond: (key1 >= 500000)

 Total runtime: 16.444 ms

(stopped postgres; reset O/S cache; started postgres)

test=# explain analyze SELECT * FROM test_select WHERE id = 500000;

                                                           QUERY PLAN

---------------------------------------------------------------------------------------------------------------------------------

 Index Scan using test_select_pkey on test_select  (cost=0.00..8.36 rows=1 width=21) (actual time=23.072..23.074 rows=1 loops=1)

   Index Cond: (id = 500000)

 Total runtime: 23.192 ms

On Mon, May 27, 2013 at 10:21 AM, Evgeny Shishkin <itparanoia@gmail.com> wrote:

On May 27, 2013, at 6:02 PM, John Mudd <johnbmudd@gmail.com> wrote:

> Postgres 9.1.2 on Ubuntu 12.04
>
> Any reason why a select by primary key would be slower than a select that includes an ORDER BY? I was really hoping using the primary key would give me a boost.
>

You created my_key after data loading, and PK was there all the time.
If you REINDEX PK, i bet it will be as fast.

> I stopped the server and cleared the O/S cache using "sync; echo 3 > /proc/sys/vm/drop_caches" between the runs.
>
>
>
> test=# VACUUM ANALYZE test_select;
> VACUUM
>
> (stopped postgres; reset O/S cache; started postgres)
>
> test=# explain analyze SELECT * FROM test_select WHERE key1 >= 500000 ORDER BY key1, key2, key3, id LIMIT 1;
>                                                               QUERY PLAN
> --------------------------------------------------------------------------------------------------------------------------------------
>  Limit  (cost=0.00..0.08 rows=1 width=21) (actual time=12.599..12.600 rows=1 loops=1)
>    ->  Index Scan using my_key on test_select  (cost=0.00..41895.49 rows=498724 width=21) (actual time=12.597..12.597 rows=1 loops=1)
>          Index Cond: (key1 >= 500000)
>  Total runtime: 12.678 ms
>
> (stopped postgres; reset O/S cache; started postgres)
>
> test=# explain analyze SELECT * FROM test_select WHERE id = 500000;
>                                                            QUERY PLAN
> ---------------------------------------------------------------------------------------------------------------------------------
>  Index Scan using test_select_pkey on test_select  (cost=0.00..8.36 rows=1 width=21) (actual time=31.396..31.398 rows=1 loops=1)
>    Index Cond: (id = 500000)
>  Total runtime: 31.504 ms
>
>
>
> Schema:
>
> test=# \d test_select
>                             Table "public.test_select"
>  Column |     Type     |                        Modifiers
> --------+--------------+----------------------------------------------------------
>  id     | integer      | not null default nextval('test_select_id_seq'::regclass)
>  key1   | integer      |
>  key2   | integer      |
>  key3   | integer      |
>  data   | character(4) |
> Indexes:
>     "test_select_pkey" PRIMARY KEY, btree (id)
>     "my_key" btree (key1, key2, key3, id)
>
> test=#
>
>
>
> Sample data:
>
> test=# SELECT * FROM test_select LIMIT 10;
>  id |  key1  |  key2  |  key3  | data
> ----+--------+--------+--------+------
>   1 | 984966 | 283954 | 772063 | x
>   2 | 817668 | 393533 | 924888 | x
>   3 | 751039 | 798753 | 454309 | x
>   4 | 128505 | 329643 | 280553 | x
>   5 | 105600 | 257225 | 710015 | x
>   6 | 323891 | 615614 |  83206 | x
>   7 | 194054 |  63506 | 353171 | x
>   8 | 212068 | 881225 | 271804 | x
>   9 | 644180 |  26693 | 200738 | x
>  10 | 136586 | 498699 | 554417 | x
> (10 rows)
>
>
>
>
> Here's how I populated the table:
>
> import psycopg2
>
> conn = psycopg2.connect('dbname=test')
>
> cur = conn.cursor()
>
> def random_int():
>     n = 1000000
>     return random.randint(0,n)
>
> def random_key():
>     return random_int(), random_int(), random_int()
>
> def create_table():
>     cur.execute('''
>             DROP TABLE IF EXISTS test_select;
>
>             CREATE TABLE test_select (
>                 id                      SERIAL PRIMARY KEY,
>                 key1                    INTEGER,
>                 key2                    INTEGER,
>                 key3                    INTEGER,
>                 data                    char(4)
>             );
>         ''')
>     conn.commit()
>
>     n = 1000000
>     for i in range(n):
>         cur.execute("INSERT INTO test_select(key1, key2, key3, data) VALUES(%s, %s, %s, 'x')", random_key())
>     conn.commit()
>
>     cur.execute('CREATE INDEX my_key ON test_select(key1, key2, key3, id)')
>     conn.commit()
>
> create_table()
>