Hello,
I am doing some query optimizations for one of my clients who runs
PostgreSQL 8.1.1, and am trying to cut down on the runtime of this
particular query as it runs very frequently:
SELECT count(*) FROM test_table_1
INNER JOIN test_table_2 ON
(test_table_2.s_id = 13300613 AND test_table_1.id = test_table_2.n_id)
WHERE now() BETWEEN test_table_1.start_ts AND test_table_1.end_ts
AND test_table_1.id = test_table_1.g_id;
The related tables are as follows:
Table "public.test_table_1"
Column | Type | Modifiers
----------+--------------------------+-----------
id | numeric(20,0) | not null
g_id | numeric(20,0) |
start_ts | timestamp with time zone |
end_ts | timestamp with time zone |
Indexes:
"test_table_1_pkey" PRIMARY KEY, btree (id)
"test_table_1_ts_index" btree (start_ts, end_ts)
Table "public.test_table_2"
Column | Type | Modifiers
--------+---------------+-----------
s_id | numeric(20,0) |
n_id | numeric(20,0) |
Indexes:
"test_table_2_n_id" btree (n_id)
"test_table_2_s_id" btree (s_id)
When I run the query it uses the following plan:
Aggregate (cost=217.17..217.18 rows=1 width=0) (actual time=107.829..107.830 rows=1 loops=1)
-> Nested Loop (cost=11.09..217.16 rows=1 width=0) (actual time=107.817..107.817 rows=0 loops=1)
-> Index Scan using test_table_1_ts_index on test_table_1 (cost=0.01..204.05 rows=1 width=22) (actual time=3.677..4.388 rows=155 loops=1)
Index Cond: ((now() >= start_ts) AND (now() <= end_ts))
Filter: (id = g_id)
-> Bitmap Heap Scan on test_table_2 (cost=11.09..13.10 rows=1 width=12) (actual time=0.664..0.664 rows=0 loops=155)
Recheck Cond: ((test_table_2.s_id = 13300613::numeric) AND ("outer".id = test_table_2.n_id))
-> BitmapAnd (cost=11.09..11.09 rows=1 width=0) (actual time=0.662..0.662 rows=0 loops=155)
-> Bitmap Index Scan on test_table_2_s_id (cost=0.00..2.48 rows=136 width=0) (actual time=0.014..0.014 rows=1 loops=155)
Index Cond: (s_id = 13300613::numeric)
-> Bitmap Index Scan on test_table_2_n_id (cost=0.00..8.36 rows=959 width=0) (actual time=0.645..0.645 rows=891 loops=155)
Index Cond: ("outer".id = test_table_2.n_id)
Total runtime: 107.947 ms
However, when I turn off enable_nestloop it runs as follows:
Aggregate (cost=465.86..465.87 rows=1 width=0) (actual time=5.763..5.764 rows=1 loops=1)
-> Merge Join (cost=465.16..465.86 rows=1 width=0) (actual time=5.752..5.752 rows=0 loops=1)
Merge Cond: ("outer".id = "inner".n_id)
-> Sort (cost=204.06..204.07 rows=1 width=22) (actual time=5.505..5.505 rows=1 loops=1)
Sort Key: test_table_1.id
-> Index Scan using test_table_1_ts_index on test_table_1 (cost=0.01..204.05 rows=1 width=22) (actual time=4.458..4.995 rows=155 loops=1)
Index Cond: ((now() >= start_ts) AND (now() <= end_ts))
Filter: (id = g_id)
-> Sort (cost=261.10..261.44 rows=136 width=12) (actual time=0.235..0.236 rows=1 loops=1)
Sort Key: test_table_2.n_id
-> Bitmap Heap Scan on test_table_2 (cost=2.48..256.28 rows=136 width=12) (actual time=0.218..0.219 rows=1 loops=1)
Recheck Cond: (s_id = 13300613::numeric)
-> Bitmap Index Scan on test_table_2_s_id (cost=0.00..2.48 rows=136 width=0) (actual time=0.168..0.168 rows=1 loops=1)
Index Cond: (s_id = 13300613::numeric)
Total runtime: 5.893 ms
As you can see the total runtime drops from 108ms to 6ms, indicating
that it is much better to use a Merge Join rather than a Nested Loop in
this case. It looks like the planner chooses a Nested Loop because it
incorrectly estimates the (now() BETWEEN test_table_1.start_ts AND
test_table_1.end_ts AND test_table_1.id = test_table_1.g_id) condition
to return 1 row, whereas in reality it returns 155 rows.
I have set statistics for test_table_1.id and test_table_1.g_id to 1000,
and have ANALYZEd both tables. This does not seem to make a bit of a
difference -- it keeps thinking the criteria will only return 1 row.
However, if I add a boolean column named "equal_ids" to test_table_1
with the value (test_table_1.id = test_table_1.g_id), and use that in
the query instead of the equality it does make a much better row
estimate. Essentially:
ALTER TABLE test_table_1 ADD equal_ids BOOLEAN;
UPDATE test_table_1 SET equal_ids = (id = g_id);
VACUUM FULL test_table_1;
ANALYZE VERBOSE test_table_1;
INFO: analyzing "public.test_table_1"
INFO: "test_table_1": scanned 83 of 83 pages, containing 8827 live rows and 0 dead rows; 8827 rows in sample, 8827 estimated total rows
The plans listed above already reflect these changes. When I substitute
"test_table_1.id = test_table_1.g_id" with "test_table_1.equal_ids" in
the query I get the following plan:
Aggregate (cost=469.76..469.77 rows=1 width=0) (actual time=5.711..5.712 rows=1 loops=1)
-> Merge Join (cost=468.52..469.76 rows=2 width=0) (actual time=5.703..5.703 rows=0 loops=1)
Merge Cond: ("outer".id = "inner".n_id)
-> Sort (cost=207.42..207.69 rows=108 width=11) (actual time=5.462..5.462 rows=1 loops=1)
Sort Key: test_table_1.id
-> Index Scan using test_table_1_ts_index on test_table_1 (cost=0.01..203.77 rows=108 width=11) (actual time=4.547..4.984 rows=155 loops=1)
Index Cond: ((now() >= start_ts) AND (now() <= end_ts))
Filter: equal_ids
-> Sort (cost=261.10..261.44 rows=136 width=12) (actual time=0.231..0.232 rows=1 loops=1)
Sort Key: test_table_2.n_id
-> Bitmap Heap Scan on test_table_2 (cost=2.48..256.28 rows=136 width=12) (actual time=0.212..0.213 rows=1 loops=1)
Recheck Cond: (s_id = 13300613::numeric)
-> Bitmap Index Scan on test_table_2_s_id (cost=0.00..2.48 rows=136 width=0) (actual time=0.177..0.177 rows=1 loops=1)
Index Cond: (s_id = 13300613::numeric)
Total runtime: 5.830 ms
The row estimate (108) is much better in this case.
Here's some information on the data in these tables:
SELECT count(*) FROM test_table_1;
count
-------
8827
SELECT count(*) FROM test_table_2;
count
---------
1149533
SELECT equal_ids, count(equal_ids) FROM test_table_1 GROUP BY equal_ids;
equal_ids | count
-----------+-------
f | 281
t | 8546
SELECT equal_ids, count(equal_ids) FROM test_table_1 WHERE now() BETWEEN test_table_1.start_ts AND test_table_1.end_ts GROUP BY equal_ids;
equal_ids | count
-----------+-------
t | 155
SELECT attname, null_frac, n_distinct FROM pg_stats WHERE tablename = 'test_table_1' AND attname IN ('id', 'g_id', 'equal_ids');
attname | null_frac | n_distinct
-----------+-----------+------------
id | 0 | -1
g_id | 0 | -0.968166
equal_ids | 0 | 2
Any ideas on how I could go about getting PostgreSQL to use a Merge Join
without having to resort to using the equal_ids column or disabling
enable_nestloop? Let me know if you need any additional info.
Thanks!
Alex
