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  • merge into 和 update 的效率对比

    以前只考虑 merge into 只是在特定场合下方便才使用的,今天才发现,merge into 竟然会比 update 在更新数据时有这么大的改进。
    其实呢,merge into部分的update和update也没啥不同的,不同的地方在于使用merge into后执行计划变了。

    赶紧测试看看,但是看到下面的结果,我和我的小伙伴惊呆了~
    测试数据:
    create table test1 as select * from dba_objects where rownum<=10000;--10000条记录
    create table test2 as select * from dba_objects;--13438条记录
    更新相同的数据,看看下面merge into和update相比性能上有何改进。
    测试1:update
    SQL> alter system flush shared_pool;
    系统已更改。
    SQL> alter system flush buffer_cache;
    系统已更改。
    SQL> set linesize 400 pagesize 400
    SQL> set autot trace
    SQL> set timing on
    SQL> update test1 t1
    2 set t1.object_name =
    3 (select t2.object_name
    4 from test2 t2
    5 where t2.object_id = t1.object_id);
    已更新10000行。
    已用时间:  00: 00: 25.24
    执行计划
    ----------------------------------------------------------
    Plan hash value: 3883393169
    ----------------------------------------------------------------------------
    | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
    ----------------------------------------------------------------------------
    | 0 | UPDATE STATEMENT | | 9606 | 741K| 518K (2)| 01:43:46 |
    | 1 | UPDATE | TEST1 | | | | |
    | 2 | TABLE ACCESS FULL| TEST1 | 9606 | 741K| 40 (0)| 00:00:01 |
    |* 3 | TABLE ACCESS FULL| TEST2 | 167 | 13193 | 53 (0)| 00:00:01 |
    ----------------------------------------------------------------------------
    Predicate Information (identified by operation id):
    ---------------------------------------------------
       3 - filter("T2"."OBJECT_ID"=:B1)
    Note
    -----
    - dynamic sampling used for this statement (level=4)

    统计信息
    ----------------------------------------------------------
    234 recursive calls
    10665 db block gets
    2282027 consistent gets
    335 physical reads
    1631056 redo size
    685 bytes sent via SQL*Net to client
    705 bytes received via SQL*Net from client
    3 SQL*Net roundtrips to/from client
    17 sorts (memory)
    0 sorts (disk)
    10000 rows processed
    测试2:merge into
    SQL> alter system flush shared_pool;
    系统已更改。
    已用时间:  00: 00: 00.33
    SQL> alter system flush buffer_cache;
    系统已更改。
    已用时间:  00: 00: 00.11
    SQL> merge into test1 t1
    2 using test2 t2
    3 on (t1.object_id = t2.object_id)
    4 when matched then
    5 update set t1.object_name = t2.object_name;
    10000 行已合并。
    已用时间:  00: 00: 01.14
    执行计划
    ----------------------------------------------------------
    Plan hash value: 818823782
    --------------------------------------------------------------------------------------
    | Id | Operation | Name | Rows | Bytes |TempSpc| Cost (%CPU)| Time |
    --------------------------------------------------------------------------------------
    | 0 | MERGE STATEMENT | | 9607 | 1238K| | 373 (1)| 00:00:05 |
    | 1 | MERGE | TEST1 | | | | | |
    | 2 | VIEW | | | | | | |
    |* 3 | HASH JOIN | | 9607 | 3996K| 2168K| 373 (1)| 00:00:05 |
    | 4 | TABLE ACCESS FULL| TEST1 | 9606 | 2054K| | 40 (0)| 00:00:01 |
    | 5 | TABLE ACCESS FULL| TEST2 | 16669 | 3369K| | 53 (0)| 00:00:01 |
    --------------------------------------------------------------------------------------
    Predicate Information (identified by operation id):
    ---------------------------------------------------
       3 - access("T1"."OBJECT_ID"="T2"."OBJECT_ID")
    Note
    -----
    - dynamic sampling used for this statement (level=4)

    统计信息
    ----------------------------------------------------------
    359 recursive calls
    10265 db block gets
    964 consistent gets
    343 physical reads
    2725336 redo size
    685 bytes sent via SQL*Net to client
    698 bytes received via SQL*Net from client
    3 SQL*Net roundtrips to/from client
    23 sorts (memory)
    0 sorts (disk)
    10000 rows processed

    测试结果对比:update和merge into 都更新1w条记录,update耗时25.24,逻辑读消耗2282027;merge into 耗时01.14s,消耗逻辑读964.相差太大了。
    其实看着执行计划,这个结果也很容易理解:update采用的类似nested loop的方式,对更新的每一行,都会对查询的表扫描一次;merge into这里选择的是hash join,
    则针对每张表都是做了一次 full table scan,对每张表都只是扫描一次。
    具体看下面的结果:
    SQL> set autot off
    SQL> update /*+gather_plan_statistics*/test1 t1
    2 set t1.object_name =
    3 (select t2.object_name
    4 from test2 t2
    5 where t2.object_id = t1.object_id);
    已更新10000行。
    已用时间:  00: 00: 27.26
    SQL> select * from table(dbms_xplan.display_cursor(null,null,'iostats'));
    PLAN_TABLE_OUTPUT
    --------------------------------------------------------------------------------------------------------------------
    --------------------------------------------------------------------------------------------------------------------
    ------------------------------------------------------------
    SQL_ID c0pc2fq4pj4zq, child number 0
    -------------------------------------
    update /*+gather_plan_statistics*/test1 t1 set t1.object_name =
    (select t2.object_name from test2 t2 where
    t2.object_id = t1.object_id)
    Plan hash value: 3883393169
    --------------------------------------------------------------------------------------
    | Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers |
    --------------------------------------------------------------------------------------
    | 0 | UPDATE STATEMENT | | 1 | | 0 |00:00:27.26 | 1800K|
    | 1 | UPDATE | TEST1 | 1 | | 0 |00:00:27.26 | 1800K|
    | 2 | TABLE ACCESS FULL| TEST1 | 1 | 9606 | 10000 |00:00:00.04 | 134 |
    |* 3 | TABLE ACCESS FULL| TEST2 | 10000 | 167 | 10000 |00:00:27.03 | 1800K|
    --------------------------------------------------------------------------------------
    Predicate Information (identified by operation id):
    ---------------------------------------------------
       3 - filter("T2"."OBJECT_ID"=:B1)
    Note
    -----
    - dynamic sampling used for this statement (level=4)

    已选择26行。
    SQL> merge /*+gather_plan_statistics*/into test1 t1
    2 using test2 t2
    3 on (t1.object_id = t2.object_id)
    4 when matched then
    5 update set t1.object_name = t2.object_name;
    10000 行已合并。
    已用时间:  00: 00: 00.25
    SQL> select * from table(dbms_xplan.display_cursor(null,null,'iostats'));
    PLAN_TABLE_OUTPUT
    ------------------------------------------------------------------------------------------------------------------
    ------------------------------------------------------------------------------------------------------------------
    ------------------------------------------------------------
    SQL_ID cg8wb3hrjx2bd, child number 0
    -------------------------------------
    merge /*+gather_plan_statistics*/into test1 t1 using test2 t2 on
    (t1.object_id = t2.object_id) when matched then update set
    t1.object_name = t2.object_name
    Plan hash value: 818823782
    -------------------------------------------------------------------------------------------------
    | Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | Reads |
    -------------------------------------------------------------------------------------------------
    | 0 | MERGE STATEMENT | | 1 | | 0 |00:00:00.22 | 10568 | 1 |
    | 1 | MERGE | TEST1 | 1 | | 0 |00:00:00.22 | 10568 | 1 |
    | 2 | VIEW | | 1 | | 10000 |00:00:00.05 | 314 | 0 |
    |* 3 | HASH JOIN | | 1 | 9607 | 10000 |00:00:00.05 | 314 | 0 |
    | 4 | TABLE ACCESS FULL| TEST1 | 1 | 9606 | 10000 |00:00:00.01 | 134 | 0 |
    | 5 | TABLE ACCESS FULL| TEST2 | 1 | 16669 | 13438 |00:00:00.01 | 180 | 0 |
    -------------------------------------------------------------------------------------------------
    Predicate Information (identified by operation id):
    ---------------------------------------------------
       3 - access("T1"."OBJECT_ID"="T2"."OBJECT_ID")
    Note
    -----
    - dynamic sampling used for this statement (level=4)

    已选择28行。
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  • 原文地址:https://www.cnblogs.com/zhaoshuangshuang/p/3274605.html
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