On May 27, 2013, at 6:02 PM, John Mudd <johnbmudd@xxxxxxxxx> 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()
>
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