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在索引列上使用函數使得索引失效的是常見的索引失效原因之一，因此盡可能的避免在索引列上使用函數。盡管可以使用基于函數的索引來解決索引失效的問題，但如此一來帶來的比如磁盤空間的占用以及列上過多的索引導致DML性能的下降。本文描述的是一個索引列上使用函數使其失效的案例。
一、數據版本與原始語句及相關信息
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.原始語句與其執行計劃
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')
從執行計劃可以看出，SQL語句使用了全表掃描，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
從索引的情況上來看有一個基于主鍵的索引包含了BUSINESS_DATE列，而查詢語句并沒有走索引而是選擇的全表掃描，而且預估所返回的行Rows與bytes也是大的驚人，cost的值96399，接近10W。
二、分析與改造SQL語句
1.原始的SQL語句分析
SQL語句中where子句的business_date列實現對記錄過濾
business_date <= '20110728'條件不會限制索引的使用
SUBSTR(business_date, 1, 6) = SUBSTR('20110728', 1, 6)使用了SUBSTR函數，限制了優化器選擇索引
基于business_date列來建立索引函數，從已存在的索引來看，必要性不大
2.改造SQL語句
SUBSTR(business_date, 1, 6) = SUBSTR('20110728', 1, 6)的實質是等于當月，即限制返回的行為從2011.7.1日至2011.7.28
因此其返回的記錄大于等于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語句
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.改造后的執行計劃
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語句的執行計劃已經由原來的全表掃描改為執行INDEX SKIP SCAN，但其cost也并沒有降低多少
三、進一步分析
1.表的相關信息
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.索引的相關信息
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.嘗試在BUSINESS_DATE列上創建索引
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較小，差不多接近表上塊的數量
4.使用新創建索引后的執行計劃
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')
從上面的執行計劃看出，SQL語句已經選擇了新建的索引盡管返回的rows,bytes沒有明顯的變化，但cost已經少了近7倍。
原文鏈接：https://blog.csdn.net/leshami/article/details/6851973
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