Re: LSM tree for Postgres

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От Konstantin Knizhnik
Тема Re: LSM tree for Postgres
Дата
Msg-id d5619cec-c591-536a-a941-aeb4fcd33206@postgrespro.ru
обсуждение исходный текст
Ответ на Re: LSM tree for Postgres  (Tomas Vondra <tomas.vondra@2ndquadrant.com>)
Список pgsql-hackers


On 04.08.2020 20:44, Tomas Vondra wrote:

IMO the 6x difference is rather misleading, as it very much depends on
the duration of the benchmark and how much data it ends up with. I think
it's better to test 'stable states' i.e. with small data set that does
not exceed RAM during the whole test, and large ones that already starts
larger than RAM. Not sure if it makes sense to make a difference between
cases that fit into shared buffers and those that exceed shared buffers
but still fit into RAM.

I have changed benchmark scenario.
Now I inserted 200 million records with sequential key: it is fast enough and makes index size about 19Gb.
Then I perform 1 million random inserts.

-- init schema
create table t(k bigint, v1 bigint, v2 bigint, v3 bigint, v4 bigint, v5 bigint, v6 bigint, v7 bigint, v8 bigint);
create index lsm_index on t using lsm3(k) include (v1,v2,v3,v4,v5,v6,v7,v8);
create table t2(k bigint, v1 bigint, v2 bigint, v3 bigint, v4 bigint, v5 bigint, v6 bigint, v7 bigint, v8 bigint);
create index on t2(k) include (v1,v2,v3,v4,v5,v6,v7,v8);

-- fill with sequential data
insert into t values (generate_series(1,200000000),0,0,0,0,0,0,0,0);
Time: 520655,635 ms (08:40,656)

insert into t2 values (generate_series(1,200000000),0,0,0,0,0,0,0,0);
Time: 372245,093 ms (06:12,245)

-- random inserts
insert into t (v1,k,v2,v3,v4,v5,v6,v7,v8) values (generate_series(1,1000000),(random()*1000000000)::bigint,0,0,0,0,0,0,0);
Time: 3781,614 ms (00:03,782)

insert into t2 (v1,k,v2,v3,v4,v5,v6,v7,v8) values (generate_series(1,1000000),(random()*1000000000)::bigint,0,0,0,0,0,0,0);
Time: 39034,574 ms (00:39,035)

The I perform random selects

select.sql:
\set k random(1, 1000000000)
select * from t where k=:k;

select2.sql:
\set k random(1, 1000000000)
select * from t2 where k=:k;

pgbench -n -T 100 -P 10 -M prepared -f select.sql postgres
tps = 11372.821006 (including connections establishing)

pgbench -n -T 100 -P 10 -M prepared -f select2.sql postgres
tps = 10392.729026 (including connections establishing)


So as you can see - insertion speed of Lsm3 is ten times higher and select speed is the same as of nbtree.

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