Re: Async execution of postgres_fdw.
От | Kyotaro HORIGUCHI |
---|---|
Тема | Re: Async execution of postgres_fdw. |
Дата | |
Msg-id | 20150116.171849.109146500.horiguchi.kyotaro@lab.ntt.co.jp обсуждение исходный текст |
Ответ на | Re: Async execution of postgres_fdw. (Kyotaro HORIGUCHI <horiguchi.kyotaro@lab.ntt.co.jp>) |
Ответы |
Re: Async execution of postgres_fdw.
(Kyotaro HORIGUCHI <horiguchi.kyotaro@lab.ntt.co.jp>)
|
Список | pgsql-hackers |
I revised the patch so that async scan will be done more aggressively, and took execution time for two very simple cases. As the result, simple seq scan gained 5% and hash join of two foreign tables gained 150%. (2.4 times faster). While measuring the performance, I noticed that each scan in a query runs at once rather than alternating with each other in many cases such as hash join or sorted joins and so. So I modified the patch so that async fetch is done more aggressively. The new v4 patch is attached. The following numbers are taken based on it. ======== Simple seq scan for the first test. > CREATE TABLE lt1 (a int, b timestamp, c text); > CREATE SERVER sv1 FOREIGN DATA WRAPPER postgres_fdw OPTIONS (host 'localhost'); > CREATE USER MAPPING FOR PUBLIC SERVER sv1; > CREATE FOREIGN TABLE ft1 () SERVER sv1 OPTIONS (table_name 'lt1'); > INSERT INTO lt1 (SELECT a, now(), repeat('x', 128) FROM generate_series(0, 999999) a); On this case, I took the the 10 times average of exec time of the following query for both master head and patched version. The fetch size is 100. > postgres=# EXPLAIN (ANALYZE ON, COSTS OFF) SELECT * FROM ft1; > QUERY PLAN > ------------------------------------------------------------------ > Foreign Scan on ft1 (actual time=0.79 5..4175.706 rows=1000000 loops=1) > Planning time: 0.060 ms > Execution time: 4276.043 ms master head : avg = 4256.621, std dev = 17.099 patched pgfdw: avg = 4036.463, std dev = 2.608 The patched version is faster by about 5%. This should be pure result of asynchronous fetching, not including the effect of early starting of remote execution in ExecInit. Interestingly, as fetch_count gets larger, the gain raises in spite of the decrease of the number of query sending. master head : avg = 2622.759, std dev = 38.379 patched pgfdw: avg = 2277.622, std dev = 27.269 About 15% gain. And for 10000, master head : avg = 2000.980, std dev = 6.434 patched pgfdw: avg = 1616.793, std dev = 13.192 19%.. It is natural that exec time reduces along with increase of fetch size, but I haven't found the reason why the patch's gain also increases. ====================== The second case is a simple join of two foreign tables sharing one connection. The master head runs this query in about 16 seconds with almost no fluctuation among multiple tries. > =# EXPLAIN (ANALYZE ON, COSTS OFF) SELECT x.a, x.c, y.c > FROM ft1 AS x JOIN ft1 AS y on x.a = y.a; > QUERY PLAN > ---------------------------------------------------------------------------- > Hash Join (actual time=7541.831..15924.631 rows=1000000 loops=1) > Hash Cond: (x.a = y.a) > -> Foreign Scan on ft1 x (actual time=1.176..6553.480 rows=1000000 loops=1) > -> Hash (actual time=7539.761..7539.761 rows=1000000 loops=1) > Buckets: 32768 Batches: 64 Memory Usage: 2829kB > -> Foreign Scan on ft1 y (actual time=1.067..6529.165 rows=1000000 loops=1) > Planning time: 0.223 ms > Execution time: 15973.916 ms But the v4 patch mysteriously accelerates this query, 6.5 seconds. > =# EXPLAIN (ANALYZE ON, COSTS OFF) SELECT x.a, x.c, y.c > FROM ft1 AS x JOIN ft1 AS y on x.a = y.a; > QUERY PLAN > ---------------------------------------------------------------------------- > Hash Join (actual time=2556.977..5812.937 rows=1000000 loops=1) > Hash Cond: (x.a = y.a) > -> Foreign Scan on ft1 x (actual time=32.689..1936.565 rows=1000000 loops=1) > -> Hash (actual time=2523.810..2523.810 rows=1000000 loops=1) > Buckets: 32768 Batches: 64 Memory Usage: 2829kB > -> Foreign Scan on ft1 y (actual time=50.345..1928.411 rows=1000000 loops=1) > Planning time: 0.220 ms > Execution time: 6512.043 ms The result data seems not broken. I don't know the reason yet but I'll investigate it. regards, -- Kyotaro Horiguchi NTT Open Source Software Center
В списке pgsql-hackers по дате отправления: