时间：2022-07-10 09:40:54 | 栏目：Oracle | 点击：次
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。
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
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
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。
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
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')
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';
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
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
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
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
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。