• 腾讯云TDSQL PostgreSQL版 -最佳实践 |优化 SQL 语句


    查看是否为分布键查询
    postgres=# explain select * from tbase_1 where f1=1;
    QUERY PLAN
    --------------------------------------------------------------------------------
    Remote Fast Query Execution (cost=0.00..0.00 rows=0 width=0)
    Node/s: dn001, dn002
    -> Gather (cost=1000.00..7827.20 rows=1 width=14)
    Workers Planned: 2
    -> Parallel Seq Scan on tbase_1 (cost=0.00..6827.10 rows=1 width=14)
    Filter: (f1 = 1)
    (6 rows)
    postgres=# explain select * from tbase_1 where f2=1;
    QUERY PLAN
    --------------------------------------------------------------------------------
    Remote Fast Query Execution (cost=0.00..0.00 rows=0 width=0)
    Node/s: dn001
    -> Gather (cost=1000.00..7827.20 rows=1 width=14)
    Workers Planned: 2
    -> Parallel Seq Scan on tbase_1 (cost=0.00..6827.10 rows=1 width=14)
    Filter: (f2 = 1)
    (6 rows)
    如上,第一个查询为非分布键查询,需要发往所有节点,这样最慢的节点决定了整个业务的速度,需要保持所有节点的响应性能一致,如第二个查询所示,业务设计查询时尽可能带上分布键。

    查看是否使用索引
    postgres=# create index tbase_2_f2_idx on tbase_2(f2);
    CREATE INDEX
    postgres=# explain select * from tbase_2 where f2=1;
    QUERY PLAN
    -------------------------------------------------------------------------------------
    Remote Fast Query Execution (cost=0.00..0.00 rows=0 width=0)
    Node/s: dn001, dn002
    -> Index Scan using tbase_2_f2_idx on tbase_2 (cost=0.42..4.44 rows=1 width=14)
    Index Cond: (f2 = 1)
    (4 rows)
    postgres=# explain select * from tbase_2 where f3='1';
    QUERY PLAN
    --------------------------------------------------------------------------------
    Remote Fast Query Execution (cost=0.00..0.00 rows=0 width=0)
    Node/s: dn001, dn002
    -> Gather (cost=1000.00..7827.20 rows=1 width=14)
    Workers Planned: 2
    -> Parallel Seq Scan on tbase_2 (cost=0.00..6827.10 rows=1 width=14)
    Filter: (f3 = '1'::text)
    (6 rows)
    postgres=#
    第一个查询使用了索引,第二个没有使用索引,通常情况下,使用索引可以加速查询速度,但索引也会增加更新的开销。

    查看是否为分布 key join
    postgres=# explain select tbase_1.* from tbase_1,tbase_2 where tbase_1.f1=tbase_2.f1 ;
    QUERY PLAN
    ------------------------------------------------------------------------------------------------
    Remote Subquery Scan on all (dn001,dn002) (cost=29.80..186.32 rows=3872 width=40)
    -> Hash Join (cost=29.80..186.32 rows=3872 width=40)
    Hash Cond: (tbase_1.f1 = tbase_2.f1)
    -> Remote Subquery Scan on all (dn001,dn002) (cost=100.00..158.40 rows=880 width=40)
    Distribute results by S: f1
    -> Seq Scan on tbase_1 (cost=0.00..18.80 rows=880 width=40)
    -> Hash (cost=18.80..18.80 rows=880 width=4)
    -> Seq Scan on tbase_2 (cost=0.00..18.80 rows=880 width=4)
    (8 rows)
    postgres=# explain select tbase_1.* from tbase_1,tbase_2 where tbase_1.f2=tbase_2.f1 ;
    QUERY PLAN
    ---------------------------------------------------------------------------------
    Remote Fast Query Execution (cost=0.00..0.00 rows=0 width=0)
    Node/s: dn001, dn002
    -> Hash Join (cost=18904.69..46257.08 rows=500564 width=14)
    Hash Cond: (tbase_1.f2 = tbase_2.f1)
    -> Seq Scan on tbase_1 (cost=0.00..9225.64 rows=500564 width=14)
    -> Hash (cost=9225.64..9225.64 rows=500564 width=4)
    -> Seq Scan on tbase_2 (cost=0.00..9225.64 rows=500564 width=4)
    (7 rows)
    第一个查询需要数据重分布,而第二个不需要,分布键 join 查询性能会更高。

    查看 join 发生的节点
    postgres=# explain select tbase_1.* from tbase_1,tbase_2 where tbase_1.f1=tbase_2.f1 ;
    QUERY PLAN
    -----------------------------------------------------------------------------------------------
    Hash Join (cost=29.80..186.32 rows=3872 width=40)
    Hash Cond: (tbase_1.f1 = tbase_2.f1)
    -> Remote Subquery Scan on all (dn001,dn002) (cost=100.00..158.40 rows=880 width=40)
    -> Seq Scan on tbase_1 (cost=0.00..18.80 rows=880 width=40)
    -> Hash (cost=126.72..126.72 rows=880 width=4)
    -> Remote Subquery Scan on all (dn001,dn002) (cost=100.00..126.72 rows=880 width=4)
    -> Seq Scan on tbase_2 (cost=0.00..18.80 rows=880 width=4)
    (7 rows)
    postgres=# set prefer_olap to on;
    SET
    postgres=# explain select tbase_1.* from tbase_1,tbase_2 where tbase_1.f1=tbase_2.f1 ;
    QUERY PLAN
    ------------------------------------------------------------------------------------------------
    Remote Subquery Scan on all (dn001,dn002) (cost=29.80..186.32 rows=3872 width=40)
    -> Hash Join (cost=29.80..186.32 rows=3872 width=40)
    Hash Cond: (tbase_1.f1 = tbase_2.f1)
    -> Remote Subquery Scan on all (dn001,dn002) (cost=100.00..158.40 rows=880 width=40)
    Distribute results by S: f1
    -> Seq Scan on tbase_1 (cost=0.00..18.80 rows=880 width=40)
    -> Hash (cost=18.80..18.80 rows=880 width=4)
    -> Seq Scan on tbase_2 (cost=0.00..18.80 rows=880 width=4)
    (8 rows)
    第一个 join 在 cn 节点执行,第二个在 dn 上重分布后再 join,业务设计上,一般 OLTP 类业务在 cn 上进行少数据量 join ,性能会更好。

    查看并行的 worker 数
    postgres=# explain select count(1) from tbase_1;
    QUERY PLAN
    ---------------------------------------------------------------------------------------
    Finalize Aggregate (cost=118.81..118.83 rows=1 width=8)
    -> Remote Subquery Scan on all (dn001,dn002) (cost=118.80..118.81 rows=1 width=0)
    -> Partial Aggregate (cost=18.80..18.81 rows=1 width=8)
    -> Seq Scan on tbase_1 (cost=0.00..18.80 rows=880 width=0)
    (4 rows)
    postgres=# analyze tbase_1;
    ANALYZE
    postgres=# explain select count(1) from tbase_1;
    QUERY PLAN
    ----------------------------------------------------------------------------------------------------
    Parallel Finalize Aggregate (cost=14728.45..14728.46 rows=1 width=8)
    -> Parallel Remote Subquery Scan on all (dn001,dn002) (cost=14728.33..14728.45 rows=1 width=0)
    -> Gather (cost=14628.33..14628.44 rows=1 width=8)
    Workers Planned: 2
    -> Partial Aggregate (cost=13628.33..13628.34 rows=1 width=8)
    -> Parallel Seq Scan on tbase_1 (cost=0.00..12586.67 rows=416667 width=0)
    (6 rows)
    上面第一个查询没走并行,第二个查询 analyze 后走并行才是正确的,建议大数据量更新再执行 analyze。

    查看各节点的执行计划是否一致
    ./tbase_run_sql_dn_master.sh "explain select * from tbase_2 where f2=1"
    dn006 --- psql -h 172.16.0.13 -p 11227 -d postgres -U tbase -c "explain select * from tbase_2 where f2=1"
    QUERY PLAN
    -----------------------------------------------------------------------------
    Bitmap Heap Scan on tbase_2 (cost=2.18..7.70 rows=4 width=40)
    Recheck Cond: (f2 = 1)
    -> Bitmap Index Scan on tbase_2_f2_idx (cost=0.00..2.18 rows=4 width=0)
    Index Cond: (f2 = 1)
    (4 rows)
    dn002 --- psql -h 172.16.0.42 -p 11012 -d postgres -U tbase -c "explain select * from tbase_2 where f2=1"
    QUERY PLAN
    -------------------------------------------------------------------------------
    Index Scan using tbase_2_f2_idx on tbase_2 (cost=0.42..4.44 rows=1 width=14)
    Index Cond: (f2 = 1)
    (2 rows)
    两个 dn 的执行计划不一致,最大可能是数据倾斜或者是执行计划被禁用。
    如有可能,DBA 可以配置在系统空闲时执行全库 analyze 和 vacuum。

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  • 原文地址:https://www.cnblogs.com/tencentdb/p/15130105.html
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