On 19.08.2019 11:51, Konstantin Knizhnik wrote:
On 18.08.2019 11:28, Pavel Stehule wrote:ne 18. 8. 2019 v 9:02 odesílatel Konstantin Knizhnik <k.knizh...@postgrespro.ru <mailto:k.knizh...@postgrespro.ru>> napsal:On 16.08.2019 20:17, Pavel Stehule wrote:pá 16. 8. 2019 v 16:12 odesílatel Konstantin Knizhnik <k.knizh...@postgrespro.ru <mailto:k.knizh...@postgrespro.ru>> napsal: I did more investigations of performance of global temp tables with shared buffers vs. vanilla (local) temp tables. 1. Combination of persistent and temporary tables in the same query. Preparation: create table big(pk bigint primary key, val bigint); insert into big values (generate_series(1,100000000),generate_series(1,100000000)); create temp table lt(key bigint, count bigint); create global temp table gt(key bigint, count bigint); Size of table is about 6Gb, I run this test on desktop with 16GB of RAM and postgres with 1Gb shared buffers. I run two queries: insert into T (select count(*),pk/P as key from big group by key); select sum(count) from T; where P is (100,10,1) and T is name of temp table (lt or gt). The table below contains times of both queries in msec: Percent of selected data 1% 10% 100% Local temp table 44610 90 47920 891 63414 21612 Global temp table 44669 35 47939 298 59159 26015 As you can see, time of insertion in temporary table is almost the same and time of traversal of temporary table is about twice smaller for global temp table when it fits in RAM together with persistent table and slightly worser when it doesn't fit. 2. Temporary table only access. The same system, but Postgres is configured with shared_buffers=10GB, max_parallel_workers = 4, max_parallel_workers_per_gather = 4 Local temp tables: create temp table local_temp(x1 bigint, x2 bigint, x3 bigint, x4 bigint, x5 bigint, x6 bigint, x7 bigint, x8 bigint, x9 bigint); insert into local_temp values (generate_series(1,100000000),0,0,0,0,0,0,0,0); select sum(x1) from local_temp; Global temp tables: create global temporary table global_temp(x1 bigint, x2 bigint, x3 bigint, x4 bigint, x5 bigint, x6 bigint, x7 bigint, x8 bigint, x9 bigint); insert into global_temp values (generate_series(1,100000000),0,0,0,0,0,0,0,0); select sum(x1) from global_temp; Results (msec): Insert Select Local temp table 37489 48322 Global temp table 44358 3003 So insertion in local temp table is performed slightly faster but select is 16 times slower! Conclusion: In the assumption then temp table fits in memory, global temp tables with shared buffers provides better performance than local temp table. I didn't consider here global temp tables with local buffers because for them results should be similar with local temp tables. Probably there is not a reason why shared buffers should be slower than local buffers when system is under low load. access to shared memory is protected by spin locks (are cheap for few processes), so tests in one or few process are not too important (or it is just one side of space) another topic can be performance on MS Sys - there are stories about not perfect performance of shared memory there. Regards PavelOne more test which is used to simulate access to temp tables under high load. I am using "upsert" into temp table in multiple connections. create global temp table gtemp (x integer primary key, y bigint); upsert.sql: insert into gtemp values (random() * 1000000, 0) on conflict(x) do update set y=gtemp.y+1; pgbench -c 10 -M prepared -T 100 -P 1 -n -f upsert.sql postgres I failed to find some standard way in pgbech to perform per-session initialization to create local temp table, so I just insert this code in pgbench code: diff --git a/src/bin/pgbench/pgbench.c b/src/bin/pgbench/pgbench.c index 570cf33..af6a431 100644 --- a/src/bin/pgbench/pgbench.c +++ b/src/bin/pgbench/pgbench.c @@ -5994,6 +5994,7 @@ threadRun(void *arg) { if ((state[i].con = doConnect()) == NULL) goto done; + executeStatement(state[i].con, "create temp table ltemp(x integer primary key, y bigint)"); } } Results are the following: Global temp table: 117526 TPS Local temp table: 107802 TPS So even for this workload global temp table with shared buffers are a little bit faster. I will be pleased if you can propose some other testing scenario. please, try to increase number of connections.With 20 connections and 4 pgbench threads results are similar: 119k TPS for global temp tables and 115k TPS for local temp tables.I have tried yet another scenario: read-only access to temp tables: \set id random(1,10000000) select sum(y) from ltemp where x=:id; Tables are created and initialized in pgbench session startup: knizhnik@knizhnik:~/postgresql$ git diff diff --git a/src/bin/pgbench/pgbench.c b/src/bin/pgbench/pgbench.c index 570cf33..95295b0 100644 --- a/src/bin/pgbench/pgbench.c +++ b/src/bin/pgbench/pgbench.c @@ -5994,6 +5994,8 @@ threadRun(void *arg) { if ((state[i].con = doConnect()) == NULL) goto done;+ executeStatement(state[i].con, "create temp table ltemp(x integer primary key, y bigint)"); + executeStatement(state[i].con, "insert into ltemp values (generate_series(1,1000000), generate_series(1,1000000))");} }Results for 10 connections with 10 million inserted records per table and 100 connections with 1 million inserted record per table :#connections: 10 100 local temp 68k 90k global temp, shared_buffers=1G 63k 61k global temp, shared_buffers=10G 150k 150kSo temporary tables with local buffers are slightly faster when data doesn't fit in shared buffers, but significantly slower when it fits.
All previously reported results were produced at my desktop.I also run this read-only test on huge IBM server (POWER9, 2 NUMA nodes, 176 CPU, 1Tb RAM).
Here the difference between local and global tables is not so large: Local temp: 739k TPS Global temp: 924k TPS -- Konstantin Knizhnik Postgres Professional: http://www.postgrespro.com The Russian Postgres Company
