| SELECT B.ID, B.NAME, B.TASK_ID, B.DICTION, B.GROUP_ID, NVL(B.ATTEST_FLAG, 'N'), NVL(B.DOUWIN_FLAG, 'N'), B.DESC, NVL(B.SIGN_FLAG, 'N'), B.MAX_EXECUTE_NUM FROM (SELECT DISTINCT (ID) FROM TEST_TAB WHERE STATUS = '04' AND CHN_TYPE = :B1) A, TABLE(CAST(:B2 AS TYPE_INFO_TABLE)) B WHERE A.ID = B.ID |
执行计划如下：
| Plan hash value: 918180822 ----------------------------------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ----------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | | | 839 (100)| | |* 1 | HASH JOIN | | 5784 | 75192 | 839 (5)| 00:00:05 | | 2 | COLLECTION ITERATOR PICKLER FETCH| | | | | | | 3 | VIEW | | 12361 | 132K| 818 (5)| 00:00:05 | | 4 | HASH UNIQUE | | 12361 | 301K| 818 (5)| 00:00:05 | |* 5 | TABLE ACCESS FULL | TEST_TAB | 21104 | 515K| 814 (4)| 00:00:05 | ----------------------------------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 1 - access("A"."ID"=SYS_OP_ATG(VALUE(KOKBF$),1,2,2)) 5 - filter(("CHN_TYPE"=:B1 AND "STATUS"='04')) |
问题分析与优化建议：
1）主要原因使用了嵌套表+TABLE函数，ORACLE对TABLE函数的基数使用1个固定值：返回8168行，这个值比较大，可以导致执行计划与其他表JOIN的时候可能走错，比如应该走NESTED LOOPS的走成HASH JOIN，导致部分表无法使用索引访问。对于在SQL中适用嵌套表和TABLE函数的，如果TABLE函数实际返回的数据量较小，比如返回200行之下，在11g之前只能使用hint:cardinality(9i可使用)、opt_estimate(10g可使用)，这2个hint都是undocument的，而且必须手动设置比较小的基数，比如100。11g可以适用动态采样，对table函数起作用.对应hint:dynamic_sampling。通过以上设置，可以使TABLE函数与其它表JOIN可以走NESTED LOOPS，从而使用索引访问。
当然，这个设置的前提是实际情况下，大部分时候，TABLE函数返回的结果行数较少，如果返回的结果集行数接近或大于8168，那将基数设置为很小的值，也就失去了意义。ORACLE估算TABLE函数返回8168行，如下所示：
CBO估算TABLE函数的cardinality为8168行，这与实际情况200以下，差别太大。
| SQL> explain plan for 2 SELECT * 3 FROM TABLE(CAST(:B2 AS TYPE_INFO_TABLE)); Explained. Elapsed: 00:00:00.01 SQL> select * from table(dbms_xplan.display); PLAN_TABLE_OUTPUT ---------------------------------------------------------------------------------------- Plan hash value: 1692170009 ------------------------------------------------------------------------------------------ | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ------------------------------------------------------------------------------------------ | 0 | SELECT STATEMENT | | 8168 | 16336 | 14 (0)| 00:00:01 | | 1 | COLLECTION ITERATOR PICKLER FETCH| | | | | | ------------------------------------------------------------------------------------------ |
通过cardinality hint强制返回100行：
| SQL> explain plan for 2 select/*+cardinality(b 100)*/ * from 3 TABLE(CAST(:B2 AS TYPE_INFO_TABLE)) B; Explained. Elapsed: 00:00:00.06 SQL> select * from table(dbms_xplan.display); PLAN_TABLE_OUTPUT ---------------------------------------------------------------------------------------- Plan hash value: 1692170009 ------------------------------------------------------------------------------------------ | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ------------------------------------------------------------------------------------------ | 0 | SELECT STATEMENT | | 100 | 200 | 20 (0)| 00:00:01 | | 1 | COLLECTION ITERATOR PICKLER FETCH| | | | | | ------------------------------------------------------------------------------------------ 8 rows selected. |
通过opt_estimate hint强制返回100行：
| SQL> explain plan for 2 select/*+opt_estimate(table,b,rows=100)*/ * from 3 TABLE(CAST(:B2 AS TYPE_INFO_TABLE)) B; Explained. Elapsed: 00:00:00.01 SQL> select * from table(dbms_xplan.display); PLAN_TABLE_OUTPUT ---------------------------------------------------------------------------------------- Plan hash value: 1692170009 ------------------------------------------------------------------------------------------ | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ------------------------------------------------------------------------------------------ | 0 | SELECT STATEMENT | | 100 | 200 | 20 (0)| 00:00:01 | | 1 | COLLECTION ITERATOR PICKLER FETCH| | | | | | ------------------------------------------------------------------------------------------ 8 rows selected. Elapsed: 00:00:00.04 |
2）通过分析语句只访问TABLE函数返回的行，为了做JOIN，使用了DISTINCT，是没有必要的，而且会影响执行计划，这里通过EXISTS子查询改写。
优化方案与效果：
1）优化方案
使用cardinality hint，并且将语句中DISTINCT修改为EXISTS子查询，如下：
| SELECT/*+cardinality(b 100)*/ B.ID, B.NAME, B.TASK_ID, B.DICTION, B.GROUP_ID,NVL(B.ATTEST_FLAG,'N'), NVL(B.DOUWIN_FLAG,'N'), B.DESC, NVL(B.SIGN_FLAG,'N'),B.MAX_EXECUTE_NUM FROM TABLE(CAST(:B2 AS TYPE_INFO_TABLE)) B WHERE EXISTS(SELECT 1 FROM TEST_TAB A WHERE A.STATUS = '04' AND A.CHN_TYPE = :B1 AND A.ID = B.ID ); |
2）优化效果
优化后buffer gets从4283到227，是原来的5.3%，时间也从原来的0.27到0.01。
优化前走HASH JOIN，全表扫描表TEST_TAB：
| Plan hash value: 3464704515 ------------------------------------------------------------------------------------------------------------------------------------------ | Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | OMem | 1Mem | Used-Mem | ------------------------------------------------------------------------------------------------------------------------------------------ |* 1 | HASH JOIN | | 1 | 1787 | 75 |00:00:00.27 | 4283 | 1959K| 1363K| 2182K (0)| | 2 | VIEW | | 1 | 3807 | 27100 |00:00:00.25 | 4283 | | | | | 3 | HASH UNIQUE | | 1 | 3807 | 27100 |00:00:00.25 | 4283 | 1983K| 1380K| 1725K (0)| |* 4 | TABLE ACCESS FULL | TEST_TAB | 1 | 4281 | 208K|00:00:00.21 | 4283 | | | | | 5 | COLLECTION ITERATOR PICKLER FETCH| | 1 | | 75 |00:00:00.01 | 0 | | | | ------------------------------------------------------------------------------------------------------------------------------------------ Predicate Information (identified by operation id): --------------------------------------------------- 1 - access("A"."ID"=SYS_OP_ATG(VALUE(KOKBF$),1,2,2)) 4 - filter(("CHN_TYPE"=:B1 AND "STATUS"='04')) |
优化后的执行计划，走NESTED LOOPS+索引访问TEST_TAB：
| Plan hash value: 884413475 ------------------------------------------------------------------------------------------------------------------ | Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | ------------------------------------------------------------------------------------------------------------------ | 1 | NESTED LOOPS SEMI | | 1 | 1 | 75 |00:00:00.01 | 227 | | 2 | COLLECTION ITERATOR PICKLER FETCH| | 1 | | 75 |00:00:00.01 | 0 | |* 3 | TABLE ACCESS BY INDEX ROWID | TEST_TAB | 75 | 1 | 75 |00:00:00.01 | 227 | |* 4 | INDEX RANGE SCAN | PK_TEST_TAB | 75 | 2 | 75 |00:00:00.01 | 152 | ------------------------------------------------------------------------------------------------------------------ Predicate Information (identified by operation id): --------------------------------------------------- 3 - filter("A"."STATUS"='04') 4 - access("A"."ID"=SYS_OP_ATG(VALUE(KOKBF$),1,2,2) AND "A"."CHN_TYPE"=:B2) filter("A"."CHN_TYPE"=:B2) |
总结与建议：
如果SQL中使用TABLE函数，但是实际情况返回的行数比ORACLE估算的8168行少很多，使用ORACLE CBO的估算方式，导致不正确的执行计划，这时，就需要人工干预，使用HINT等方式，让SQL走更优的计划，从而提高效率。