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分类目录归档:Oracle性能优化
执行计划改变导致数据库负载过高
核心生产库突然负载飙升,我的压力来了,通过分析是一条sql的执行计划改变引起该故障,最终通过sql profile固定执行计划解决该问题
数据库主机负载
这里明显表现系统load 偏高,而且还在上升中;top的进程中,占用cpu都计划100%
top - 16:25:39 up 123 days, 1:42, 4 users, load average: 46.19, 45.08, 43.93 Tasks: 1469 total, 28 running, 1439 sleeping, 0 stopped, 2 zombie Cpu(s): 45.9%us, 1.1%sy, 0.0%ni, 47.1%id, 5.2%wa, 0.1%hi, 0.6%si, 0.0%st Mem: 264253752k total, 262605260k used, 1648492k free, 413408k buffers Swap: 33554424k total, 458684k used, 33095740k free, 67110504k cached PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND 2622 oracle 18 0 150g 34m 28m R 100.0 0.0 11:58.21 oracleq9db1 (LOCAL=NO) 15881 oracle 21 0 150g 35m 28m R 100.0 0.0 72:14.20 oracleq9db1 (LOCAL=NO) 17214 oracle 19 0 150g 38m 32m R 100.0 0.0 20:47.44 oracleq9db1 (LOCAL=NO) 17705 oracle 21 0 150g 34m 28m R 100.0 0.0 27:33.00 oracleq9db1 (LOCAL=NO) 6110 oracle 19 0 150g 34m 28m R 99.8 0.0 12:33.34 oracleq9db1 (LOCAL=NO) 6876 oracle 19 0 150g 34m 27m R 99.5 0.0 12:43.90 oracleq9db1 (LOCAL=NO) 17205 oracle 23 0 150g 34m 27m R 99.5 0.0 21:37.18 oracleq9db1 (LOCAL=NO) 24629 oracle 20 0 150g 35m 29m R 99.5 0.0 28:10.62 oracleq9db1 (LOCAL=NO) 26959 oracle 19 0 150g 34m 27m R 99.5 0.0 47:17.87 oracleq9db1 (LOCAL=NO) 7655 oracle 18 0 150g 30m 25m R 98.5 0.0 2:28.45 oracleq9db1 (LOCAL=NO) 16377 oracle 18 0 150g 34m 28m R 98.5 0.0 36:07.11 oracleq9db1 (LOCAL=NO) 24637 oracle 18 0 150g 37m 30m R 98.2 0.0 26:39.15 oracleq9db1 (LOCAL=NO) 6106 oracle 21 0 150g 40m 33m R 97.2 0.0 11:37.75 oracleq9db1 (LOCAL=NO) 28785 oracle 18 0 150g 34m 28m R 96.9 0.0 24:03.29 oracleq9db1 (LOCAL=NO) 24278 oracle 17 0 150g 31m 26m S 96.5 0.0 3:15.51 oracleq9db1 (LOCAL=NO) 24283 oracle 17 0 150g 33m 28m S 96.5 0.0 6:25.26 oracleq9db1 (LOCAL=NO) 7098 oracle 18 0 150g 32m 27m R 94.6 0.0 2:20.22 oracleq9db1 (LOCAL=NO) 6874 oracle 17 0 150g 34m 28m R 87.0 0.0 12:02.92 oracleq9db1 (LOCAL=NO) 18206 oracle 16 0 150g 34m 27m R 86.1 0.0 16:11.28 oracleq9db1 (LOCAL=NO) 7096 oracle 17 0 150g 29m 24m R 85.4 0.0 3:01.72 oracleq9db1 (LOCAL=NO)
数据库等待事件
SID EVENT ---------- ---------------------------------------------------------------- 183 gc cr request 185 latch: cache buffers chains 239 db file sequential read 292 gc cr request 406 gc cr request 410 db file sequential read 463 gc current request 572 gc buffer busy acquire 575 gc buffer busy acquire 577 latch: cache buffers chains 629 db file sequential read 747 gc cr request 919 latch: cache buffers chains 974 gc cr request 1033 log file sync 1141 db file parallel write 1153 gc cr request 1199 db file sequential read 1378 db file sequential read 1495 gc cr request 1540 db file parallel write 1547 gc buffer busy acquire 1662 gc cr request 1715 gc buffer busy acquire 1770 SQL*Net message to client 1830 latch: cache buffers chains 1884 gc cr request 2113 db file sequential read 2173 db file sequential read 2229 rdbms ipc reply 2292 db file sequential read 2341 db file sequential read 2348 gc cr request 2460 gc cr request 2632 gc cr request 2684 gc cr request 2687 db file sequential read 2749 db file sequential read 2913 gc cr request 2967 db file sequential read 3038 gc cr request 3087 SQL*Net message to client 3089 gc cr request 3194 db file sequential read 3195 db file sequential read 3309 latch: cache buffers chains 3371 gc cr request 3485 gc cr request 3535 gc cr request
可以这里有很多gc cr request等待和cache buffers chains等待,第一反应就是很可能系统某条sql执行计划不正确导致逻辑读剧增.
分析awr报告
故障时候的逻辑读 top sql可以看出来cdwjdd67x27mh的sql逻辑读异常大
分析正常时间点awr报告中cdwjdd67x27mh逻辑读情况
通过对比可以发现两个awr中,cdwjdd67x27mh 语句执行次数差不多,但是单次逻辑读从800多突变为34000多,增加了40多倍
cdwjdd67x27mh 语句分析
执行计划
17:36:08 sys@Q9DB>select * from table(dbms_xplan.display_awr('cdwjdd67x27mh')); PLAN_TABLE_OUTPUT ----------------------------------------------------------------------------------------------------------------------------------------------------------------- SQL_ID cdwjdd67x27mh -------------------- select * from ( select * from GE_TAOBAO_BILL o WHERE 1=1 and o.CREATED_TIME >= :1 and o.CREATED_TIME < :2 and o.REC_SITE_ID = :3 and o.STATUS_ID = :4 and o.SERVICE_TYPE = :5 ) where rownum <= 36000 Plan hash value: 647855111 ---------------------------------------------------------------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | Pstart| Pstop | ---------------------------------------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | | | 5 (100)| | | | 1 | COUNT STOPKEY | | | | | | | | 2 | FILTER | | | | | | | | 3 | PARTITION RANGE ITERATOR | | 1 | 455 | 5 (0)| 00:00:01 | KEY | KEY | | 4 | TABLE ACCESS BY LOCAL INDEX ROWID| GE_TAOBAO_BILL | 1 | 455 | 5 (0)| 00:00:01 | KEY | KEY | | 5 | INDEX RANGE SCAN | IDX_TAOBAO_BILL_CR_ISDP_S | 1 | | 4 (0)| 00:00:01 | KEY | KEY | ---------------------------------------------------------------------------------------------------------------------------------- SQL_ID cdwjdd67x27mh -------------------- select * from ( select * from GE_TAOBAO_BILL o WHERE 1=1 and o.CREATED_TIME >= :1 and o.CREATED_TIME < :2 and o.REC_SITE_ID = :3 and o.STATUS_ID = :4 and o.SERVICE_TYPE = :5 ) where rownum <= 36000 Plan hash value: 2979024279 --------------------------------------------------------------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | Pstart| Pstop | --------------------------------------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | | | 13 (100)| | || | 1 | COUNT STOPKEY | | | | | | || | 2 | FILTER | | | | | | || | 3 | PARTITION RANGE ITERATOR | | 1 | 455 | 13 (0)| 00:00:01 | KEY | KEY | | 4 | TABLE ACCESS BY LOCAL INDEX ROWID| GE_TAOBAO_BILL | 1 | 455 | 13 (0)| 00:00:01 | KEY | KEY | | 5 | INDEX RANGE SCAN | IDX_TAOBAO_BILL_CR_REC_S | 4 | | 9 (0)| 00:00:01 | KEY | KEY | ---------------------------------------------------------------------------------------------------------------------------------
这里可以发现cdwjdd67x27mh在数据库中有两个执行计划
通过awr数据,看执行计划的变化情况
10:50:29 sys@Q9DB>select a.INSTANCE_NUMBER,a.snap_id,a.sql_id,a.plan_hash_value,b.begin_interval_time 10:50:30 2 from dba_hist_sqlstat a, dba_hist_snapshot b 10:50:30 3 where sql_id ='cdwjdd67x27mh' 10:50:30 4 and a.snap_id = b.snap_id 10:50:30 5 order by instance_number,begin_interval_time desc; INSTANCE_NUMBER SNAP_ID SQL_ID PLAN_HASH_VALUE BEGIN_INTERVAL_TIME --------------- ---------- ------------- --------------- ---------------------------------------- 1 20719 cdwjdd67x27mh 2979024279 12-MAY-14 05.00.12.753 PM 1 20719 cdwjdd67x27mh 647855111 12-MAY-14 05.00.12.753 PM 1 20719 cdwjdd67x27mh 2979024279 12-MAY-14 05.00.12.702 PM 1 20719 cdwjdd67x27mh 647855111 12-MAY-14 05.00.12.702 PM 1 20718 cdwjdd67x27mh 647855111 12-MAY-14 04.00.24.197 PM 1 20718 cdwjdd67x27mh 2979024279 12-MAY-14 04.00.24.197 PM 1 20718 cdwjdd67x27mh 647855111 12-MAY-14 04.00.24.172 PM 1 20718 cdwjdd67x27mh 2979024279 12-MAY-14 04.00.24.172 PM 1 20717 cdwjdd67x27mh 647855111 12-MAY-14 03.11.22.251 PM 1 20717 cdwjdd67x27mh 2979024279 12-MAY-14 03.11.22.251 PM 1 20717 cdwjdd67x27mh 647855111 12-MAY-14 03.11.22.188 PM 1 20717 cdwjdd67x27mh 2979024279 12-MAY-14 03.11.22.188 PM ……………… 1 20696 cdwjdd67x27mh 2979024279 11-MAY-14 07.00.07.142 PM 1 20696 cdwjdd67x27mh 2979024279 11-MAY-14 07.00.07.105 PM 1 20695 cdwjdd67x27mh 2979024279 11-MAY-14 06.00.12.771 PM 1 20695 cdwjdd67x27mh 2979024279 11-MAY-14 06.00.12.707 PM 1 20694 cdwjdd67x27mh 2979024279 11-MAY-14 05.00.48.249 PM 1 20694 cdwjdd67x27mh 2979024279 11-MAY-14 05.00.48.170 PM 1 20693 cdwjdd67x27mh 2979024279 11-MAY-14 04.00.37.841 PM ………… 2 20719 cdwjdd67x27mh 2979024279 12-MAY-14 05.00.12.753 PM 2 20719 cdwjdd67x27mh 2979024279 12-MAY-14 05.00.12.702 PM 2 20718 cdwjdd67x27mh 2979024279 12-MAY-14 04.00.24.197 PM 2 20718 cdwjdd67x27mh 2979024279 12-MAY-14 04.00.24.172 PM 2 20717 cdwjdd67x27mh 2979024279 12-MAY-14 03.11.22.251 PM 2 20717 cdwjdd67x27mh 2979024279 12-MAY-14 03.11.22.188 PM
这里可以清晰看到,执行计划在1节点中发生震荡(两个执行计划都有选择),仔细看两个执行计划,会发现就是查询的时候所使用的index不同而已,继续分析两个index
IDX_TAOBAO_BILL_CR_ISDP_S CREATED_TIME 1 IDX_TAOBAO_BILL_CR_ISDP_S IS_DISPART 2 IDX_TAOBAO_BILL_CR_ISDP_S STATUS_ID 3 IDX_TAOBAO_BILL_CR_REC_S REC_SITE_ID 1 IDX_TAOBAO_BILL_CR_REC_S CREATED_TIME 2 IDX_TAOBAO_BILL_CR_REC_S STATUS_ID 3
分析数据分布情况(其他列省略)
TABLE_NAME COLUMN_NAME NUM_DISTINCT LAST_ANAL ------------------------------ ------------------------------ ------------ --------- GE_TAOBAO_BILL CREATED_TIME 287080448 05-MAY-14 GE_TAOBAO_BILL REC_SITE_ID 13176 05-MAY-14 GE_TAOBAO_BILL IS_DISPART 2 05-MAY-14 GE_TAOBAO_BILL STATUS_ID 7 05-MAY-14
这里可以看到数据库在正常的时候使用IDX_TAOBAO_BILL_CR_REC_S没有问题,但是在某些情况下选择使用IDX_TAOBAO_BILL_CR_ISDP_S这个就有问题,导致逻辑读过高,其实对于该sql语句,是因为IDX_TAOBAO_BILL_CR_REC_S 索引不合理导致,如果创建CREATED_TIME,REC_SITE_ID,STATUS_ID,就不会因为传输的值范围不同而使用IDX_TAOBAO_BILL_CR_ISDP_S的情况。针对该情况,因为表非常大,短时间内无法修改index,只能考虑使用 sql profile固定执行计划
sql profile固定计划
SQL>@coe_xfr_sql_profile.sql cdwjdd67x27mh Parameter 1: SQL_ID (required) PLAN_HASH_VALUE AVG_ET_SECS --------------- ----------- 2979024279 .011 647855111 5.164 Parameter 2: PLAN_HASH_VALUE (required) Enter value for 2: 2979024279 Values passed: ~~~~~~~~~~~~~ SQL_ID : "cdwjdd67x27mh" PLAN_HASH_VALUE: "2979024279" Execute coe_xfr_sql_profile_cdwjdd67x27mh_2979024279.sql on TARGET system in order to create a custom SQL Profile with plan 2979024279 linked to adjusted sql_text. COE_XFR_SQL_PROFILE completed. SQL>@coe_xfr_sql_profile_cdwjdd67x27mh_2979024279.sql SQL>DECLARE 2 sql_txt CLOB; 3 h SYS.SQLPROF_ATTR; 4 BEGIN 5 sql_txt := q'[ 6 select * from ( select 7 * 8 9 from 10 11 GE_TAOBAO_BILL 12 13 o 14 15 WHERE 1=1 16 17 18 19 20 21 22 23 24 25 26 27 and o.CREATED_TIME >= :1 28 29 30 and o.CREATED_TIME < :2 31 32 33 and o.REC_SITE_ID = :3 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 and o.STATUS_ID = :4 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 and o.SERVICE_TYPE = :5 ) where rownum <= 36000 65 ]'; 66 h := SYS.SQLPROF_ATTR( 67 q'[BEGIN_OUTLINE_DATA]', 68 q'[IGNORE_OPTIM_EMBEDDED_HINTS]', 69 q'[OPTIMIZER_FEATURES_ENABLE('11.2.0.3')]', 70 q'[DB_VERSION('11.2.0.3')]', 71 q'[FIRST_ROWS]', 72 q'[OUTLINE_LEAF(@"SEL$F5BB74E1")]', 73 q'[MERGE(@"SEL$2")]', 74 q'[OUTLINE(@"SEL$1")]', 75 q'[OUTLINE(@"SEL$2")]', 76 q'[INDEX_RS_ASC(@"SEL$F5BB74E1" "O"@"SEL$2" ("GE_TAOBAO_BILL"."REC_SITE_ID" "GE_TAOBAO_BILL"."CREATED_TIME" "GE_TAOBAO_BILL"."STATUS_ID"))]', 77 q'[END_OUTLINE_DATA]'); 78 :signature := DBMS_SQLTUNE.SQLTEXT_TO_SIGNATURE(sql_txt); 79 DBMS_SQLTUNE.IMPORT_SQL_PROFILE ( 80 sql_text => sql_txt, 81 profile => h, 82 name => 'coe_cdwjdd67x27mh_2979024279', 83 description => 'coe cdwjdd67x27mh 2979024279 '||:signature||'', 84 category => 'DEFAULT', 85 validate => TRUE, 86 replace => TRUE, 87 force_match => FALSE /* TRUE:FORCE (match even when different literals in SQL). FALSE:EXACT (similar to CURSOR_SHARING) */ ); 88 END; 89 / PL/SQL procedure successfully completed. SQL>WHENEVER SQLERROR CONTINUE SQL>SET ECHO OFF; SIGNATURE --------------------- 18414135509058398362 ... manual custom SQL Profile has been created COE_XFR_SQL_PROFILE_cdwjdd67x27mh_2979024279 completed
固定执行计划后,系统负载恢复正常
load恢复正常,单个进程占用cpu 也正常
top - 18:25:29 up 123 days, 4:25, 3 users, load average: 17.59, 16.72, 16.10 Tasks: 1559 total, 6 running, 1551 sleeping, 0 stopped, 2 zombie Cpu(s): 6.2%us, 1.2%sy, 0.0%ni, 84.3%id, 7.4%wa, 0.1%hi, 0.9%si, 0.0%st Mem: 264253752k total, 262395300k used, 1858452k free, 305928k buffers Swap: 33554424k total, 467420k used, 33087004k free, 66811412k cached PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND 3010 oracle 15 0 150g 26m 21m S 23.6 0.0 0:08.60 oracleq9db2 (LOCAL=NO) 26936 oracle 15 0 150g 33m 28m S 22.9 0.0 0:12.53 oracleq9db2 (LOCAL=NO) 9691 oracle 15 0 150g 34m 28m D 21.0 0.0 0:48.73 oracleq9db2 (LOCAL=NO) 9694 oracle 15 0 150g 34m 28m S 17.4 0.0 0:45.74 oracleq9db2 (LOCAL=NO) 14366 oracle 15 0 150g 33m 28m R 17.4 0.0 0:25.11 oracleq9db2 (LOCAL=NO) 2471 oracle -2 0 150g 180m 37m S 16.7 0.1 10795:55 ora_lms3_q9db2 2463 oracle -2 0 150g 180m 37m S 15.7 0.1 10648:38 ora_lms1_q9db2 2459 oracle -2 0 150g 180m 37m S 14.8 0.1 10726:42 ora_lms0_q9db2 2467 oracle -2 0 150g 180m 36m S 14.8 0.1 10980:33 ora_lms2_q9db2 13324 oracle 15 0 150g 31m 26m S 14.1 0.0 0:22.75 oracleq9db2 (LOCAL=NO) 16740 oracle 15 0 150g 34m 28m R 13.4 0.0 0:43.85 oracleq9db2 (LOCAL=NO) 1908 oracle 15 0 150g 27m 22m S 11.8 0.0 0:03.95 oracleq9db2 (LOCAL=NO) 9689 oracle 15 0 150g 33m 27m S 11.8 0.0 0:46.01 oracleq9db2 (LOCAL=NO) 19410 oracle 15 0 150g 31m 26m S 11.8 0.0 0:43.18 oracleq9db2 (LOCAL=NO) 14102 oracle 15 0 150g 31m 25m S 11.5 0.0 2:17.23 oracleq9db2 (LOCAL=NO) 1914 oracle 15 0 150g 29m 24m S 11.1 0.0 0:04.77 oracleq9db2 (LOCAL=NO) 31106 oracle 15 0 150g 34m 28m S 9.8 0.0 1:24.85 oracleq9db2 (LOCAL=NO) 31139 oracle 15 0 150g 30m 24m S 9.8 0.0 1:21.75 oracleq9db2 (LOCAL=NO) 2498 oracle 15 0 150g 42m 35m S 7.9 0.0 3838:43 ora_lgwr_q9db2 28108 oracle 15 0 150g 36m 29m S 7.9 0.0 0:18.19 oracleq9db2 (LOCAL=NO) 2392 oracle 15 0 150g 35m 17m S 7.5 0.0 5304:57 ora_lmd0_q9db2
含is null sql语句优化
原sql语句与执行计划
SQL> set autot trace SQL> WITH AL AS (SELECT * FROM XIFENFEI_LOG WHERE CLEAR_TIME IS NULL) 2 SELECT SWP.ID SWP_ID, AL.* FROM AL FULL OUTER JOIN XIFENFEI_LOG_SWAP SWP ON SWP.ID = AL.ID; 54 rows selected. Execution Plan ---------------------------------------------------------- Plan hash value: 888046630 ---------------------------------------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ---------------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 24 | 11064 | 24658 (2)| 00:04:56 | | 1 | TEMP TABLE TRANSFORMATION | | | | | | | 2 | LOAD AS SELECT | | | | | | |* 3 | TABLE ACCESS FULL | XIFENFEI_LOG | 23 | 2576 | 24652 (2)| 00:04:56 | | 4 | VIEW | | 24 | 11064 | 6 (17)| 00:00:01 | | 5 | UNION-ALL | | | | | | | 6 | NESTED LOOPS OUTER | | 23 | 10465 | 2 (0)| 00:00:01 | | 7 | VIEW | | 23 | 10304 | 2 (0)| 00:00:01 | | 8 | TABLE ACCESS FULL | SYS_TEMP_0FD9D6605_51B4E691 | 23 | 2576 | 2 (0)| 00:00:01 | |* 9 | INDEX UNIQUE SCAN | XIFENFEI_LOG_SWP_PK | 1 | 7 | 0 (0)| 00:00:01 | |* 10 | HASH JOIN ANTI | | 1 | 20 | 4 (25)| 00:00:01 | | 11 | INDEX FULL SCAN | XIFENFEI_LOG_SWP_PK | 20 | 140 | 1 (0)| 00:00:01 | | 12 | VIEW | | 23 | 299 | 2 (0)| 00:00:01 | | 13 | TABLE ACCESS FULL | SYS_TEMP_0FD9D6605_51B4E691 | 23 | 2576 | 2 (0)| 00:00:01 | ---------------------------------------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 3 - filter("CLEAR_TIME" IS NULL) 9 - access("SWP"."ID"(+)="AL"."ID") 10 - access("SWP"."ID"="AL"."ID") Statistics ---------------------------------------------------------- 2 recursive calls 8 db block gets 111504 consistent gets 1 physical reads 692 redo size 8075 bytes sent via SQL*Net to client 502 bytes received via SQL*Net from client 5 SQL*Net roundtrips to/from client 0 sorts (memory) 0 sorts (disk) 54 rows processed
这里很明显占用资源多,执行时间长的都在XIFENFEI_LOG表的全表扫描上,而该表的where 条件是CLEAR_TIME is null.
分析CLEAR_TIME 列null值的分布
SQL> SELECT count(*) FROM XIFENFEI_LOG WHERE CLEAR_TIME IS NULL; COUNT(*) ---------- 48 SQL> SELECT count(*) FROM XIFENFEI_LOG WHERE CLEAR_TIME IS not NULL; COUNT(*) ---------- 6899211
通过这里分析可以知道,CLEAR_TIME is null的值非常少,如果能够创建一个index,取到CLEAR_TIME 列null的值,那效率将非常搞.但是有oracle index知识的人都知道,B树index是不包含null列,因此一般性index无法满足该需求.这里思考创建含常数的复合index,而且把CLEAR_TIME放在前面,因为后面的常数一定存在,因此CLEAR_TIME中含有null的记录也就包含在该复合index中.
创建含常数复合index
SQL> create index ind_XIFENFEI_LOG_null on XIFENFEI_LOG (CLEAR_TIME,0) online; Index created.
再次查看执行计划
SQL> WITH AL AS (SELECT * FROM XIFENFEI_LOG WHERE CLEAR_TIME IS NULL) 2 SELECT SWP.ID SWP_ID, AL.* FROM AL FULL OUTER JOIN XIFENFEI_LOG_SWAP SWP ON SWP.ID = AL.ID; 50 rows selected. Execution Plan ---------------------------------------------------------- Plan hash value: 2359331571 ------------------------------------------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ------------------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 24 | 11064 | 25 (4)| 00:00:01 | | 1 | TEMP TABLE TRANSFORMATION | | | | | | | 2 | LOAD AS SELECT | | | | | | | 3 | TABLE ACCESS BY INDEX ROWID| XIFENFEI_LOG | 23 | 2576 | 19 (0)| 00:00:01 | |* 4 | INDEX RANGE SCAN | IND_XIFENFEI_LOG_NULL | 23 | | 3 (0)| 00:00:01 | | 5 | VIEW | | 24 | 11064 | 6 (17)| 00:00:01 | | 6 | UNION-ALL | | | | | | | 7 | NESTED LOOPS OUTER | | 23 | 10465 | 2 (0)| 00:00:01 | | 8 | VIEW | | 23 | 10304 | 2 (0)| 00:00:01 | | 9 | TABLE ACCESS FULL | SYS_TEMP_0FD9D660D_51B4E691 | 23 | 2576 | 2 (0)| 00:00:01 | |* 10 | INDEX UNIQUE SCAN | XIFENFEI_LOG_SWP_PK | 1 | 7 | 0 (0)| 00:00:01 | |* 11 | HASH JOIN ANTI | | 1 | 20 | 4 (25)| 00:00:01 | | 12 | INDEX FULL SCAN | XIFENFEI_LOG_SWP_PK | 20 | 140 | 1 (0)| 00:00:01 | | 13 | VIEW | | 23 | 299 | 2 (0)| 00:00:01 | | 14 | TABLE ACCESS FULL | SYS_TEMP_0FD9D660D_51B4E691 | 23 | 2576 | 2 (0)| 00:00:01 | ------------------------------------------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 4 - access("CLEAR_TIME" IS NULL) 10 - access("SWP"."ID"(+)="AL"."ID") 11 - access("SWP"."ID"="AL"."ID") Statistics ---------------------------------------------------------- 2 recursive calls 8 db block gets 33 consistent gets 1 physical reads 648 redo size 7688 bytes sent via SQL*Net to client 502 bytes received via SQL*Net from client 5 SQL*Net roundtrips to/from client 0 sorts (memory) 0 sorts (disk) 50 rows processed
这里可以发现,该sql使用了创建的含常数的复合index,sql执行时间从4分56秒,提高到现在的1秒钟,逻辑读从当初的111504减小到现在的33,巧用含常数的复合索引使得sql执行效率极大提高.
一次数据库优化全过程分析
最近对客户的一个数据库进行了优化,在本次优化过程中,主要涉及以下方面:
1. 确保系统有足够的内存,处理方法配置Hugepage,减小SGA
2. 优化因为主键表频繁插入引起的user$,con$,cdef$递归查询sql
SQL> select c.name, u.name from con$ c, cdef$ cd, user$ u where 2 c.con# = cd.con# and cd.enabled = :1 and c.owner# = u.user#; Execution Plan ---------------------------------------------------------- Plan hash value: 2409458995 ----------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ----------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 3820 | 164K| 38 (6)| 00:00:01 | |* 1 | HASH JOIN | | 3820 | 164K| 38 (6)| 00:00:01 | | 2 | TABLE ACCESS FULL | USER$ | 64 | 896 | 3 (0)| 00:00:01 | |* 3 | HASH JOIN | | 3820 | 111K| 34 (3)| 00:00:01 | |* 4 | TABLE ACCESS FULL| CDEF$ | 3820 | 34380 | 25 (0)| 00:00:01 | | 5 | TABLE ACCESS FULL| CON$ | 6368 | 130K| 8 (0)| 00:00:01 | -----------------------------------------------------------------------------
具体见:一次数据库优化全过程分析