函数使得索引列失效

      在索引列上使用函数使得索引失效的是常见的索引失效原因之一，因此尽可能的避免在索引列上使用函数。尽管可以使用基于函数的索引来
解决索引失效的问题，但如此一来带来的比如磁盘空间的占用以及列上过多的索引导致DML性能的下降。本文描述的是一个索引列上使用函数使
其失效的案例。

一、数据版本与原始语句及相关信息
  1.版本信息    

SQL> select * from v$version; BANNER ---------------------------------------------------------------- Oracle Database 10g Release 10.2.0.3.0 - 64bit Production PL/SQL Release 10.2.0.3.0 - Production CORE 10.2.0.3.0 Production TNS for Linux: Version 10.2.0.3.0 - Production NLSRTL Version 10.2.0.3.0 - Production

  2.原始语句与其执行计划   

SQL> set autotrace traceonly exp; SELECT acc_num, curr_cd, DECODE('20110728', (SELECT TO_CHAR(LAST_DAY(TO_DATE('20110728', 'YYYYMMDD')), 'YYYYMMDD') FROM DUAL), 0, adj_credit_int_lv1_amt + adj_credit_int_lv2_amt - adj_debit_int_lv1_amt - adj_debit_int_lv2_amt) AS interest FROM acc_pos_int_tbl ACC_POS_INT_TBL1 WHERE SUBSTR(business_date, 1, 6) = SUBSTR('20110728', 1, 6) AND business_date <= '20110728'; Execution Plan ---------------------------------------------------------- Plan hash value: 3114115399 ------------------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 336K| 12M| 96399 (1)| 00:19:17 | | 1 | FAST DUAL | | 1 | | 2 (0)| 00:00:01 | |* 2 | TABLE ACCESS FULL| ACC_POS_INT_TBL | 336K| 12M| 96399 (1)| 00:19:17 | ------------------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 2 - filter(SUBSTR("BUSINESS_DATE",1,6)='201107' AND "BUSINESS_DATE"<='20110728')

    从执行计划可以看出，SQL语句使用了全表扫描，而where 子句中只有唯一的一列business_date

  3.表上的索引信息     

SQL> set autotrace off; SQL> set linesize 190 SQL> @Idx_Info Enter value for owner: goex_admin old 10: AND owner = upper('&owner') new 10: AND owner = upper('goex_admin') Enter value for table_name: ACC_POS_INT_TBL old 11: AND a.table_name = upper('&table_name') new 11: AND a.table_name = upper('ACC_POS_INT_TBL') TABLE_NAME INDEX_NAME COL_NAM CL_POS STATUS IDX_TYP DSCD ------------------ ------------------------ -------------------- ------ -------- --------------- ---- ACC_POS_INT_TBL ACC_POS_INT_10DIG_IDX SYS_NC00032$ 1 VALID FUNCTION-BASED ASC NORMAL ACC_POS_INT_TBL ACC_POS_INT_10DIG_IDX BUSINESS_DATE 2 VALID FUNCTION-BASED ASC NORMAL ACC_POS_INT_TBL ACC_POS_INT_10DIG_IDX CURR_CD 3 VALID FUNCTION-BASED ASC NORMAL ACC_POS_INT_TBL PK_ACC_POS_INT_TBL ACC_NUM 1 VALID NORMAL ASC ACC_POS_INT_TBL PK_ACC_POS_INT_TBL BUSINESS_DATE 2 VALID NORMAL ASC

    从索引的情况上来看有一个基于主键的索引包含了BUSINESS_DATE列，而查询语句并没有走索引而是选择的全表扫描，而且预估所返回
    的行Rows与bytes也是大的惊人，cost的值96399，接近10W。

二、分析与改造SQL语句
  1.原始的SQL语句分析
       SQL语句中where子句的business_date列实现对记录过滤
       business_date <= '20110728'条件不会限制索引的使用
       SUBSTR(business_date, 1, 6) = SUBSTR('20110728', 1, 6)使用了SUBSTR函数，限制了优化器选择索引
       基于business_date列来建立索引函数，从已存在的索引来看，必要性不大
   
  2.改造SQL语句
    SUBSTR(business_date, 1, 6) = SUBSTR('20110728', 1, 6)的实质是等于当月，即限制返回的行为从2011.7.1日至2011.7.28
    因此其返回的记录大于等于2011.7.1，且小于2011.7.28
    做如下改造
     business_date >=to_char(last_day(add_months(to_date('20110728','yyyymmdd'),-1)) + 1,'yyyymmdd')
   
  3.改造后的SQL语句   

SELECT acc_num, curr_cd, DECODE('20110728', (SELECT TO_CHAR(LAST_DAY(TO_DATE('20110728', 'YYYYMMDD')), 'YYYYMMDD') FROM DUAL), 0, adj_credit_int_lv1_amt + adj_credit_int_lv2_amt - adj_debit_int_lv1_amt - adj_debit_int_lv2_amt) AS interest FROM acc_pos_int_tbl ACC_POS_INT_TBL1 WHERE business_date >= to_char(last_day(add_months(to_date('20110728', 'yyyymmdd'), -1)) + 1, 'yyyymmdd') AND business_date <= '20110728';

   4.改造后的执行计划  

Execution Plan ---------------------------------------------------------- Plan hash value: 66267922 -------------------------------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | -------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1065K| 39M| 75043 (1)| 00:15:01 | | 1 | FAST DUAL | | 1 | | 2 (0)| 00:00:01 | | 2 | TABLE ACCESS BY INDEX ROWID| ACC_POS_INT_TBL | 1065K| 39M| 75043 (1)| 00:15:01 | |* 3 | INDEX SKIP SCAN | PK_ACC_POS_INT_TBL | 33730 | | 41180 (1)| 00:08:15 | -------------------------------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 3 - access("BUSINESS_DATE">='20110701' AND "BUSINESS_DATE"<='20110728') filter("BUSINESS_DATE">='20110701' AND "BUSINESS_DATE"<='20110728')

    改造后可以看到SQL语句的执行计划已经由原来的全表扫描改为执行INDEX SKIP SCAN，但其cost也并没有降低多少

三、进一步分析
  1.表的相关信息  

SQL> @Tab_Stat Enter value for input_table_name: ACC_POS_INT_TBL old 11: WHERE table_name = upper('&input_table_name') new 11: WHERE table_name = upper('ACC_POS_INT_TBL') Enter value for input_owner: goex_admin old 12: AND owner = upper('&input_owner') new 12: AND owner = upper('goex_admin') NUM_ROWS BLKS EM_BLKS AVG_SPACE CHAIN_CNT AVG_ROW_LEN AVG_ROWS_PER_BLOCK LST_ANLY STA ---------- ---------- ---------- ---------- ---------- ----------- ------------------ --------- --- 33659947 437206 1322 855 0 99 77 27-SEP-11 NO

  2.索引的相关信息 

SQL> @Idx_Stat Enter value for input_table_name: ACC_POS_INT_TBL old 11: WHERE table_name = upper('&input_table_name') new 11: WHERE table_name = upper('ACC_POS_INT_TBL') Enter value for input_owner: goex_admin old 12: AND owner = upper('&input_owner') new 12: AND owner = upper('goex_admin') BLEV IDX_NAME LF_BLKS DST_KEYS NUM_ROWS LF_PER_KEY DAT_BLK_PER_KEY CLUS_FCT LST_ANLY ---- ------------------------------ ---------- ---------- ---------- ---------- --------------- ---------- --------- 3 PK_ACC_POS_INT_TBL 155658 33777720 33777720 1 1 33777447 27-SEP-11 3 ACC_POS_INT_10DIG_IDX 160247 32850596 32850596 1 1 32763921 27-SEP-11

  3.尝试在BUSINESS_DATE列上创建索引   

SQL> create index I_ACC_POS_INT_TBL_BS_DT on ACC_POS_INT_TBL(BUSINESS_DATE) tablespace tbs_tmp nologging; Index created. SQL> @Idx_Stat Enter value for input_table_name: ACC_POS_INT_TBL old 11: WHERE table_name = upper('&input_table_name') new 11: WHERE table_name = upper('ACC_POS_INT_TBL') Enter value for input_owner: goex_admin old 12: AND owner = upper('&input_owner') new 12: AND owner = upper('goex_admin') BLEV IDX_NAME LF_BLKS DST_KEYS NUM_ROWS LF_PER_KEY DAT_BLK_PER_KEY CLUS_FCT LST_ANLY ---- ------------------------------ ---------- ---------- ---------- ---------- --------------- ---------- --------- 2 I_ACC_POS_INT_TBL_BS_DT 93761 908 33659855 103 506 460007 30-SEP-11 3 PK_ACC_POS_INT_TBL 155658 33777720 33777720 1 1 33777447 27-SEP-11 3 ACC_POS_INT_10DIG_IDX 160247 32850596 32850596 1 1 32763921 27-SEP-11

  建立索引后聚簇因子较小，差不多接近表上块的数量
  
  4.使用新创建索引后的执行计划   

Execution Plan ---------------------------------------------------------- Plan hash value: 2183566226 ------------------------------------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ------------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1065K| 39M| 17586 (1)| 00:03:32 | | 1 | FAST DUAL | | 1 | | 2 (0)| 00:00:01 | | 2 | TABLE ACCESS BY INDEX ROWID| ACC_POS_INT_TBL | 1065K| 39M| 17586 (1)| 00:03:32 | |* 3 | INDEX RANGE SCAN | I_ACC_POS_INT_TBL_BS_DT | 1065K| | 2984 (1)| 00:00:36 | ------------------------------------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 3 - access("BUSINESS_DATE">='20110701' AND "BUSINESS_DATE"<='20110728')

  从上面的执行计划看出，SQL语句已经选择了新建的索引
  尽管返回的rows,bytes没有明显的变化，但cost已经少了近7倍。