Top N需求SQL优化提升案例

发表于由

前几日，朋友发来微信，测试系统中抓到一条即将上线的SQL，严重消耗数据库资源，SQL执行计划如下：

SELECT DT,TI,ST CONT,ANCT,PIID,CID FROM 
       (SELECT A.ID,a.INFO, 
             TO_CHAR(A.DT,'YYYY')||'年'||TO_CHAR(A.DT,'MM')||'月'||TO_CHAR(A.DT,'DD')||'日' AS DT,
             A.TI,
             A.MED,
             A.AT,
             B.ID AS CONT_ID,  
             to_char(SUBSTR(regexp_REPLACE(B.CONT, '\s',''),1,100)) AS ST, 
             E.ANNT,
             E.ID PIID,
             ROW_NUMBER() OVER(ORDER BY A.DT DESC,A.ID DESC)AS RN    
         FROM NWBAS A
         JOIN BASTXT B ON A.ID = B.OID
         JOIN NWSANN E ON A.ID=E.OID
       WHERE  EXISTS(SELECT 1 FROM NWSTYP C WHERE A.ID = C.ORID AND SUBSTR(C.code,1,2) in(11,12,13))        
              and a.PIC=1
       order by A.dt DESC
       )WHERE RN <=4;

---------------------------------------------------------------------------------------------------------------------------------------------
| Id  | Operation                      | Name            | Starts | E-Rows | Cost (%CPU)| E-Time   | A-Rows |   A-Time   | Buffers | Reads  |
---------------------------------------------------------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT               |                 |      1 |        | 36016 (100)|          |      4 |00:00:04.52 |     267K|  74660 |
|*  1 |  VIEW                          |                 |      1 |   5237 | 36016   (1)| 00:07:13 |      4 |00:00:04.52 |     267K|  74660 |
|*  2 |   WINDOW SORT PUSHED RANK      |                 |      1 |   5237 | 36016   (1)| 00:07:13 |      5 |00:00:04.51 |     266K|  74660 |
|   3 |    NESTED LOOPS                |                 |      1 |   5237 | 36016   (1)| 00:07:13 |  67739 |00:00:04.38 |     266K|  74660 |
|   4 |     NESTED LOOPS               |                 |      1 |   5237 | 36016   (1)| 00:07:13 |  67739 |00:00:03.88 |     198K|  74660 |
|*  5 |      HASH JOIN                 |                 |      1 |   5237 | 27234   (1)| 00:05:27 |  67741 |00:00:03.59 |   93944 |  74660 |
|*  6 |       HASH JOIN RIGHT SEMI     |                 |      1 |  71164 | 25527   (1)| 00:05:07 |  68836 |00:00:03.36 |   91427 |  74660 |
|*  7 |        INDEX FAST FULL SCAN    | NWSTYP          |      1 |  71211 |  4120   (2)| 00:00:50 |    753K|00:00:02.14 |   16744 |      0 |
|*  8 |        TABLE ACCESS FULL       | NWSBAS          |      1 |   1281K| 21403   (1)| 00:04:17 |    102K|00:00:00.78 |   74683 |  74660 |
|   9 |       TABLE ACCESS FULL        | NWSANN          |      1 |  94294 |   653   (1)| 00:00:08 |  97456 |00:00:00.09 |    2517 |      0 |
|* 10 |      INDEX UNIQUE SCAN         | BASTXT          |  67741 |      1 |     1   (0)| 00:00:01 |  67739 |00:00:00.26 |     104K|      0 |
|  11 |     TABLE ACCESS BY INDEX ROWID| BASTXT          |  67739 |      1 |     2   (0)| 00:00:01 |  67739 |00:00:00.48 |   67813 |      0 |
---------------------------------------------------------------------------------------------------------------------------------------------

问题SQL单次消耗需要267K的逻辑读，大致需要4秒左右执行完成，并且执行计划中多数步骤中评估行数与实际返回行数严重不符，ID=10、11两步NESTED LOOP BASTXT表被驱动6万多次，效率低下。但是此SQL的逻辑是利用分析函数 ROW_NUMBER() OVER(ORDER BY A.DT DESC,A.ID DESC) 排序后，最终取4行而已，那么其实就是一个取Top N的SQL，可以将SQL改写为如下形式：

 SELECT created,object_name,owner,namespace FROM
       (SELECT /*+ INDEX_DESC(A t1_idx01) use_nl(A) use_nl(B) use_nl(C) use_nl(E) leading(A C B E)*/  A.object_id,
             A.object_name,
             a.CREATED,
             A.owner,
             B.object_id AS CONT_ID,
             E.namespace,
             E.OBJECT_ID PICTURE_ID
         FROM T1 A
         JOIN T2 B ON A.object_id = B.object_id
         JOIN T3 E ON A.object_id=E.object_id
        JOIN (SELECT DISTINCT D.OBJECT_ID FROM T4 D WHERE D.namespace in(29,30)) C on A.OBJECT_ID=C.OBJECT_ID
              where A.TEMPORARY='N'
       ORDER BY A.CREATED DESC,A.object_id DESC,A.LAST_DDL_TIME DESC --依照原SQL逻辑 order by A.LAST_DDL_TIME DESC其实可以去掉，此处加order by没有意义
       ) WHERE rownum <=4;
create index t1_idx01 on t1(TEMPORARY,CREATED,object_id,LAST_DDL_TIME,0);
create index t2_idx02 on t2(object_id,0);
create index t3_idx03 on t3(object_id,0);
create index t4_idx01 on t4(object_id,namespace,0);
利用索引有序特性，因SQL选择性很差，大部分记录都满足SQL关联条件，理想中的执行计划利用INDEX RANGE SCAN DESCENDING降序扫描，扫描少数记录后便满足需求停止扫描 count stop by key
-----------------------------------------------------------------------------------------------------------------------------------------
| Id  | Operation                         | Name     | Starts | E-Rows | Cost (%CPU)| E-Time   | A-Rows |   A-Time   | Buffers | Reads  |
-----------------------------------------------------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT                  |          |      1 |        |    33 (100)|          |      4 |00:00:00.01 |     344 |      7 |
|*  1 |  COUNT STOPKEY                    |          |      1 |        |            |          |      4 |00:00:00.01 |     344 |      7 |
|   2 |   VIEW                            |          |      1 |      5 |    33   (0)| 00:00:01 |      4 |00:00:00.01 |     344 |      7 |
|   3 |    NESTED LOOPS SEMI              |          |      1 |      5 |    33   (0)| 00:00:01 |      4 |00:00:00.01 |     344 |      7 |
|   4 |     NESTED LOOPS                  |          |      1 |      5 |    23   (0)| 00:00:01 |   1056 |00:00:00.01 |     331 |      4 |
|   5 |      NESTED LOOPS                 |          |      1 |      6 |    12   (0)| 00:00:01 |   1057 |00:00:00.01 |     170 |      0 |
|   6 |       TABLE ACCESS BY INDEX ROWID | T1       |      1 |      8 |     4   (0)| 00:00:01 |   1163 |00:00:00.01 |      88 |      0 |
|*  7 |        INDEX RANGE SCAN DESCENDING| T1_IDX01 |      1 |      8 |     3   (0)| 00:00:01 |   1163 |00:00:00.01 |      10 |      0 |
|*  8 |       INDEX RANGE SCAN            | T2_IDX02 |   1163 |      1 |     1   (0)| 00:00:01 |   1057 |00:00:00.01 |      82 |      0 |
|   9 |      TABLE ACCESS BY INDEX ROWID  | T3       |   1057 |      1 |     2   (0)| 00:00:01 |   1056 |00:00:00.01 |     161 |      4 |
|* 10 |       INDEX RANGE SCAN            | T3_IDX03 |   1057 |      1 |     1   (0)| 00:00:01 |   1056 |00:00:00.01 |      88 |      4 |
|  11 |     VIEW PUSHED PREDICATE         |          |   1056 |      2 |     2   (0)| 00:00:01 |      4 |00:00:00.01 |      13 |      3 |
|* 12 |      INDEX RANGE SCAN             | T4_IDX01 |   1056 |      2 |     2   (0)| 00:00:01 |      4 |00:00:00.01 |      13 |      3 |
-----------------------------------------------------------------------------------------------------------------------------------------

目标SQL优化后执行计划如下,单次执行只需要2000多个buffer，执行时间只需要几个毫秒即可

--------------------------------------------------------------------------------------------------------------------------------------------------
| Id  | Operation                        | Name               | Starts | E-Rows | Cost (%CPU)| E-Time   | A-Rows |   A-Time   | Buffers | Reads  |
--------------------------------------------------------------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT                 |                    |      1 |        |   228 (100)|          |      4 |00:00:00.05 |    2905 |    780 |
|*  1 |  COUNT STOPKEY                   |                    |      1 |        |            |          |      4 |00:00:00.05 |    2905 |    780 |
|   2 |   VIEW                           |                    |      1 |      4 |   228   (0)| 00:00:03 |      4 |00:00:00.05 |    2905 |    780 |
|   3 |    NESTED LOOPS SEMI             |                    |      1 |      4 |   228   (0)| 00:00:03 |      4 |00:00:00.04 |    1631 |      0 |
|   4 |     NESTED LOOPS                 |                    |      1 |      4 |   216   (0)| 00:00:03 |      8 |00:00:00.04 |    1616 |      0 |
|   5 |      NESTED LOOPS                |                    |      1 |     55 |   104   (0)| 00:00:02 |      8 |00:00:00.04 |    1595 |      0 |
|   6 |       TABLE ACCESS BY INDEX ROWID| NWSBAS             |      1 |   1282K|    12   (0)| 00:00:01 |      8 |00:00:00.04 |    1571 |      0 |
|*  7 |        INDEX FULL SCAN DESCENDING| IDX_NWSBAS_01      |      1 |     64 |     3   (0)| 00:00:01 |      8 |00:00:00.04 |    1566 |      0 |
|   8 |       TABLE ACCESS BY INDEX ROWID| BASTXT             |      8 |      1 |     2   (0)| 00:00:01 |      8 |00:00:00.01 |      24 |      0 |
|*  9 |        INDEX UNIQUE SCAN         | BASTXT             |      8 |      1 |     1   (0)| 00:00:01 |      8 |00:00:00.01 |      16 |      0 |
|  10 |      TABLE ACCESS BY INDEX ROWID | NWSANN             |      8 |      1 |     3   (0)| 00:00:01 |      8 |00:00:00.01 |      21 |      0 |
|* 11 |       INDEX RANGE SCAN           | NWSANN             |      8 |      1 |     2   (0)| 00:00:01 |      8 |00:00:00.01 |      17 |      0 |
|  12 |     VIEW PUSHED PREDICATE        |                    |      8 |      1 |     3   (0)| 00:00:01 |      4 |00:00:00.01 |      15 |      0 |
|* 13 |      INDEX RANGE SCAN            | NWSTYP             |      8 |      1 |     3   (0)| 00:00:01 |      4 |00:00:00.01 |      15 |      0 |
--------------------------------------------------------------------------------------------------------------------------------------------------

SQL中or操作借助改写提升效率案例一则

发表于由

昨日，朋友发来一则SQL询问有没有什么优化思路，并反馈给我Oracle 的STA给出的SQL”优化”建议是加并行操作提升SQL响应时间，SQL 脱敏后TEXT与执行计划如下：

SELECT A.ID,
       C.ANN AS FILENAME,
       B.CNT AS CONT,
       A.TT,
       A.INFO,
       A.U_TIME AS PUB_DT
FROM A
LEFT JOIN  B ON A.ID = B.O_ID
AND B.CNT IS NOT NULL
LEFT JOIN  C ON C.O_ID = A.ID
WHERE A.U_TIME > NVL(TO_DATE(:1 , 'yyyy-MM-dd HH24:mi:ss'), DATE '2015-01-01')
  OR B.U_TIME > NVL(TO_DATE(:2 , 'yyyy-MM-dd HH24:mi:ss'), DATE '2015-01-01')

-------------------------------------------------------------------------------------------------------------------------------------------
| Id  | Operation                    | Name            | Starts | E-Rows | Cost (%CPU)| E-Time   | A-Rows |   A-Time   | Buffers | Reads  |
-------------------------------------------------------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT             |                 |      1 |        |   337K(100)|          |   6187 |00:00:47.88 |     670K|    636K|
|   1 |  NESTED LOOPS OUTER          |                 |      1 |     48 |   337K  (1)| 01:07:29 |   6187 |00:00:47.88 |     670K|    636K|
|*  2 |   FILTER                     |                 |      1 |        |            |          |   6187 |00:00:47.61 |     641K|    636K|
|*  3 |    HASH JOIN OUTER           |                 |      1 |     48 |   337K  (1)| 01:07:27 |   5594K|00:00:46.87 |     641K|    636K|
|   4 |     TABLE ACCESS FULL        | A               |      1 |   5442K| 52131   (1)| 00:10:26 |   5592K|00:00:06.88 |     200K|    200K|
|*  5 |     TABLE ACCESS FULL        | B               |      1 |   2442K|   142K  (1)| 00:28:36 |   2460K|00:00:24.05 |     441K|    436K|
|   6 |   TABLE ACCESS BY INDEX ROWID| C               |   6187 |      1 |     3   (0)| 00:00:01 |   5657 |00:00:00.25 |   29121 |     0 |
|*  7 |    INDEX RANGE SCAN          | C               |   6187 |      1 |     2   (0)| 00:00:01 |   5657 |00:00:00.18 |   23463 |     0 |
-------------------------------------------------------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
   2 - filter(("A"."U_TIME">TO_DATE(' 2021-03-17 13:38:11', 'syyyy-mm-dd hh24:mi:ss') OR "B"."U_TIME">TO_DATE('2021-03-17
              13:38:11', 'syyyy-mm-dd hh24:mi:ss')))
   3 - access("A"."ID"="B"."O_ID")
   5 - filter("B"."CNT" IS NOT NULL)
   7 - access("C"."O_ID"="A"."ID")

从真实的执行计划中看到最终反馈6188行记录，并且资源消耗（buffer gets和reads）高达600K+,这个资源消耗，SQL执行了47s并不奇怪。SQL逻辑并不复杂，并且SQL中存在or的操作，并且朋友反馈如果传值为空可以不用考虑，这种情况基本不会出现，并且经过确认Utime字段上存在索引的，那么我们可以考虑将此SQL进行拆分,同时考虑到or的每一个步骤都返回行数不大的情况下，用到索引，将or改写成union all+lnnvl的形式：

SELECT /*+        gather_plan_statistics  */ A.ID,
                                             C.ANN AS FILENAME,
                                             B.CNT AS CONT,
                                             A.TT,
                                             A.INFO,
                                             A.U_TIME AS PUB_DT
FROM A
LEFT JOIN B ON A.ID = B.O_ID
AND B.CNT IS NOT NULL
LEFT JOIN C ON C.O_ID = A.ID
WHERE A.U_TIME > NVL(TO_DATE('2021-03-17 13:38:11' , 'yyyy-MM-dd HH24:mi:ss'), DATE'2015-01-01')
UNION ALL
SELECT A.ID,
       C.ANN AS FILENAME,
       B.CNT AS CONT,
       A.TT,
       A.INFO,
       A.U_TIME AS PUB_DT
FROM A
LEFT JOIN B ON A.ID = B.O_ID
AND B.CNT IS NOT NULL
LEFT JOIN C ON C.O_ID = A.ID
WHERE B.U_TIME > NVL(TO_DATE('2021-03-17 13:38:11', 'yyyy-MM-dd HH24:mi:ss'), DATE '2015-01-01')
  AND LNNVL(A.U_TIME > NVL(TO_DATE('2021-03-17 13:38:11' , 'yyyy-MM-dd HH24:mi:ss'), DATE'2015-01-01'));

-------------------------------------------------------------------------------------------------------------------------------------------------
| Id  | Operation                      | Name                | Starts | E-Rows | Cost (%CPU)| E-Time   | A-Rows |   A-Time   | Buffers | Reads |
-------------------------------------------------------------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT               |                     |      1 |        |   170 (100)|          |   6187 |00:00:00.75 | 66639 |      2 |
|   1 |  UNION-ALL                     |                     |      1 |        |            |          |   6187 |00:00:00.75 | 66639 |      2 |
|   2 |   NESTED LOOPS OUTER           |                     |      1 |     17 |    94   (0)| 00:00:02 |   5253 |00:00:00.55 | 45122 |      2 |
|   3 |    NESTED LOOPS OUTER          |                     |      1 |     17 |    48   (0)| 00:00:01 |   5253 |00:00:00.33 | 27337 |      2 |
|   4 |     TABLE ACCESS BY INDEX ROWID| A                   |      1 |     17 |     6   (0)| 00:00:01 |   5253 |00:00:00.09 | 10508 |      0 |
|*  5 |      INDEX RANGE SCAN          | A_UPD               |      1 |     17 |     3   (0)| 00:00:01 |   5253 |00:00:00.05 |  5255 |      0 |
|*  6 |     TABLE ACCESS BY INDEX ROWID| B                   |   5253 |      1 |     3   (0)| 00:00:01 |   4749 |00:00:00.23 | 16829 |      2 |
|*  7 |      INDEX RANGE SCAN          | B_TXT               |   5253 |      1 |     2   (0)| 00:00:01 |   4749 |00:00:00.12 | 12079 |      1 |
|   8 |    TABLE ACCESS BY INDEX ROWID | C                   |   5253 |      1 |     3   (0)| 00:00:01 |   4798 |00:00:00.20 | 17785 |      0 |
|*  9 |     INDEX RANGE SCAN           | C                   |   5253 |      1 |     2   (0)| 00:00:01 |   4798 |00:00:00.13 | 12987 |      0 |
|  10 |   NESTED LOOPS OUTER           |                     |      1 |     14 |    75   (0)| 00:00:01 |    934 |00:00:00.15 | 21517 |      0 |
|  11 |    NESTED LOOPS                |                     |      1 |     14 |    37   (0)| 00:00:01 |    934 |00:00:00.09 | 17148 |      0 |
|* 12 |     TABLE ACCESS BY INDEX ROWID| B                   |      1 |     14 |     9   (0)| 00:00:01 |   5591 |00:00:00.04 |  3535 |      0 |
|* 13 |      INDEX RANGE SCAN          | B_UPD               |      1 |     14 |     3   (0)| 00:00:01 |   5591 |00:00:00.01 |   978 |      0 |
|* 14 |     TABLE ACCESS BY INDEX ROWID| A                   |   5591 |      1 |     2   (0)| 00:00:01 |    934 |00:00:00.05 | 13613 |      0 |
|* 15 |      INDEX UNIQUE SCAN         | PK_A                |   5591 |      1 |     1   (0)| 00:00:01 |   5590 |00:00:00.03 |  8023 |      0 |
|  16 |    TABLE ACCESS BY INDEX ROWID | C                   |    934 |      1 |     3   (0)| 00:00:01 |    859 |00:00:00.05 |  4369 |      0 |
|* 17 |     INDEX RANGE SCAN           | C                   |    934 |      1 |     2   (0)| 00:00:01 |    859 |00:00:00.04 |  3510 |      0 |
-------------------------------------------------------------------------------------------------------------------------------------------------

恰好被驱动的表连接列中均有索引，经过优化后SQL，并且带入多个变量测试，耗时效率不到1秒。

SQL EXISTS写法遭遇FILTER

发表于由

前几天，看到一篇公众号文章谈到一个SQL优化的问题，原SQL逻辑大致如下，看到这个SQL，发现其中一个小问题感觉需要提示出来，否则很容易忽视。

select min(created)
FROM t1
WHERE '1606270446000' = '1606270446000'
  AND EXISTS
    (SELECT 1
     FROM t2 m
     WHERE m.object_type = t1.object_type
       AND m.owner = t1.owner
       AND m.object_id = '33'
       AND t1.namespace = '4')
  OR EXISTS
    (SELECT 1
     FROM t3 n
     WHERE n.object_type = t1.object_type
       AND n.owner = t1.owner
       AND n.object_id = '33'
       AND t1.namespace = '4');

Plan hash value: 1283715866

-----------------------------------------------------------------------------------------------------------------------------
| Id  | Operation			| Name	  | Starts | E-Rows | Cost (%CPU)| E-Time   | A-Rows |	 A-Time   | Buffers |
-----------------------------------------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT		|	  |	 1 |	    |	395 (100)|	    |	   1 |00:00:00.15 |   14591 |
|   1 |  SORT AGGREGATE 		|	  |	 1 |	  1 |		 |	    |	   1 |00:00:00.15 |   14591 |
|*  2 |   FILTER			|	  |	 1 |	    |		 |	    |	2628 |00:00:00.15 |   14591 |
|   3 |    TABLE ACCESS FULL		| T1	  |	 1 |	101K|	391   (1)| 00:00:05 |	 203K|00:00:00.04 |    2867 |
|   4 |    UNION-ALL			|	  |   7925 |	    |		 |	    |	   1 |00:00:00.03 |   11724 |
|*  5 |     FILTER			|	  |   7925 |	    |		 |	    |	   1 |00:00:00.01 |    5863 |
|*  6 |      TABLE ACCESS BY INDEX ROWID| T3	  |   2929 |	  1 |	  2   (0)| 00:00:01 |	   1 |00:00:00.01 |    5863 |
|*  7 |       INDEX RANGE SCAN		| N_IDX01 |   2929 |	  1 |	  1   (0)| 00:00:01 |	2929 |00:00:00.01 |    2934 |
|*  8 |     FILTER			|	  |   7924 |	    |		 |	    |	   0 |00:00:00.01 |    5861 |
|*  9 |      TABLE ACCESS BY INDEX ROWID| T2	  |   2928 |	  1 |	  2   (0)| 00:00:01 |	   0 |00:00:00.01 |    5861 |
|* 10 |       INDEX RANGE SCAN		| M_IDX01 |   2928 |	  1 |	  1   (0)| 00:00:01 |	2928 |00:00:00.01 |    2933 |
-----------------------------------------------------------------------------------------------------------------------------

COLUMN_NAME			      NDV NUL  NUM_NULLS DATA_TYPE    LOW_VAL_25		HIGH_VAL_25		  LAST_ANALYZED        HISTOGRAM
------------------------------ ---------- --- ---------- ------------ ------------------------- ------------------------- -------------------- ---------
CREATED 			    28480 Y	       0 DATE	      78760202122A38		78790318010404		  2021-03-07 10:26:30  NONE
DATA_OBJECT_ID			    29582 Y	  144370 NUMBER       80			C31A3E5F		  2021-03-07 10:26:30  NONE
EDITION_NAME				0 Y	  203482 VARCHAR2							  2021-03-07 10:26:30  NONE
GENERATED				2 Y	       0 VARCHAR2     4E			59			  2021-03-07 10:26:30  NONE
LAST_DDL_TIME			     3050 Y	      10 DATE	      78760201122A38		787903040E3124		  2021-03-07 10:26:30  NONE
NAMESPACE			       19 Y	      10 NUMBER       C102			C141			  2021-03-07 10:26:30  FREQUENCY
OBJECT_ID			   203482 Y	       0 NUMBER       C102			C3152353		  2021-03-07 10:26:30  NONE
OBJECT_NAME			    48784 Y	       0 VARCHAR2     2F31303030333233645F44656 73756E2F7574696C2F7265736 2021-03-07 10:26:30  NONE
OBJECT_TYPE			       44 Y	       0 VARCHAR2     434C5553544552		57494E444F57		  2021-03-07 10:26:30  FREQUENCY
OWNER				      251 Y	       0 VARCHAR2     414752			5A4142424958		  2021-03-07 10:26:30  FREQUENCY
SECONDARY				1 Y	       0 VARCHAR2     4E			4E			  2021-03-07 10:26:30  NONE
STATUS					2 Y	       0 VARCHAR2     494E56414C4944		56414C4944		  2021-03-07 10:26:30  NONE
SUBOBJECT_NAME			      171 Y	  202738 VARCHAR2     5030			575248245F5741495453545F3 2021-03-07 10:26:30  NONE
TEMPORARY				2 Y	       0 VARCHAR2     4E			59			  2021-03-07 10:26:30  NONE
TIMESTAMP			     3887 Y	      10 VARCHAR2     313939372D30342D31323A313 323032312D30332D30343A313 2021-03-07 10:26:30  NONE

从执行计划中看到，采用了FILTER的方式，原文中该SQL执行了“2小时39分钟40秒，逻辑读2874多万，物理读270多万”，T表数据量很大，Filter 主查询结果集大，子查询结果小，也不能影响驱动关系，驱动表只能是主查询。驱动表驱动次数越多，效率越差。主查询结果集大，只能利用改写的方式消除FILTER。原文作者利用了如下方式进行改写：

SELECT min(t.created)
FROM t1 t,
     t2 m ,
     t3 n
WHERE ('1606270446000' = '1606270446000')
  AND m.object_type = t.object_type
  AND m.owner = t.owner
  AND m.object_id = '33'
  AND t.namespace = '1'
  OR (n.object_type = t.object_type
      AND n.owner = t.owner
      AND n.object_id = '33'
      AND t.namespace = '4');

因为最终的结果集取MIN，则将半连接直接改为了inner join，无需考虑重复数据的问题，但是需要注意的是，半连接（in或exists）改为inner join时，如果最终结果集没有去重逻辑，需要将中间涉及关联的结果集去重后，再改写为内连接，从而体现“半”连接，这是在我们日常SQL改写中，常见却又容易忽略的问题：

create index t1_idx01 on t1(object_type,owner,namespace,created);
create index m_idx01 on t2(object_id);
create index n_idx01 on t3(object_id);

SELECT created  --普通结果集
FROM t1,
  (SELECT DISTINCT m.object_type,  --distinct去重
                   m.owner
   FROM t2 m
   WHERE m.object_id = '33') x1,
  (SELECT DISTINCT n.object_type,  --distinct去重
                   n.owner
   FROM t3 n
   WHERE n.object_id = '33') x2
WHERE 1=1
  AND (x1.object_type = t1.object_type
       AND x1.owner = t1.owner)
  OR (x2.object_type = t1.object_type
      AND x2.owner = t1.owner)
  AND t1.namespace = '4';

Plan hash value: 3647106578

--------------------------------------------------------------------------------------------------------------------------------
| Id  | Operation			  | Name     | Starts | E-Rows | Cost (%CPU)| E-Time   | A-Rows |   A-Time   | Buffers |
--------------------------------------------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT		  |	     |	    1 |        |    16 (100)|	       |   2628 |00:00:00.01 |	   215 |
|   1 |  CONCATENATION			  |	     |	    1 |        |	    |	       |   2628 |00:00:00.01 |	   215 |
|   2 |   NESTED LOOPS			  |	     |	    1 |      3 |     8	(25)| 00:00:01 |   2628 |00:00:00.01 |	   195 |
|   3 |    MERGE JOIN CARTESIAN 	  |	     |	    1 |      1 |     6	(34)| 00:00:01 |      1 |00:00:00.01 |	     6 |
|   4 |     VIEW			  |	     |	    1 |      1 |     3	(34)| 00:00:01 |      1 |00:00:00.01 |	     3 |
|   5 |      HASH UNIQUE		  |	     |	    1 |      1 |     3	(34)| 00:00:01 |      1 |00:00:00.01 |	     3 |
|   6 |       TABLE ACCESS BY INDEX ROWID | T2	     |	    1 |      1 |     2	 (0)| 00:00:01 |      1 |00:00:00.01 |	     3 |
|*  7 |        INDEX RANGE SCAN 	  | M_IDX01  |	    1 |      1 |     1	 (0)| 00:00:01 |      1 |00:00:00.01 |	     2 |
|   8 |     BUFFER SORT 		  |	     |	    1 |      1 |     6	(34)| 00:00:01 |      1 |00:00:00.01 |	     3 |
|   9 |      VIEW			  |	     |	    1 |      1 |     3	(34)| 00:00:01 |      1 |00:00:00.01 |	     3 |
|  10 |       HASH UNIQUE		  |	     |	    1 |      1 |     3	(34)| 00:00:01 |      1 |00:00:00.01 |	     3 |
|  11 |        TABLE ACCESS BY INDEX ROWID| T3	     |	    1 |      1 |     2	 (0)| 00:00:01 |      1 |00:00:00.01 |	     3 |
|* 12 | 	INDEX RANGE SCAN	  | N_IDX01  |	    1 |      1 |     1	 (0)| 00:00:01 |      1 |00:00:00.01 |	     2 |
|* 13 |    INDEX RANGE SCAN		  | T1_IDX01 |	    1 |      3 |     2	 (0)| 00:00:01 |   2628 |00:00:00.01 |	   189 |
|  14 |   NESTED LOOPS			  |	     |	    1 |      1 |     8	(25)| 00:00:01 |      0 |00:00:00.01 |	    20 |
|  15 |    NESTED LOOPS 		  |	     |	    1 |      1 |     5	(20)| 00:00:01 |   2628 |00:00:00.01 |	    17 |
|  16 |     VIEW			  |	     |	    1 |      1 |     3	(34)| 00:00:01 |      1 |00:00:00.01 |	     3 |
|  17 |      HASH UNIQUE		  |	     |	    1 |      1 |     3	(34)| 00:00:01 |      1 |00:00:00.01 |	     3 |
|  18 |       TABLE ACCESS BY INDEX ROWID | T2	     |	    1 |      1 |     2	 (0)| 00:00:01 |      1 |00:00:00.01 |	     3 |
|* 19 |        INDEX RANGE SCAN 	  | M_IDX01  |	    1 |      1 |     1	 (0)| 00:00:01 |      1 |00:00:00.01 |	     2 |
|* 20 |     INDEX RANGE SCAN		  | T1_IDX01 |	    1 |      1 |     2	 (0)| 00:00:01 |   2628 |00:00:00.01 |	    14 |
|* 21 |    VIEW 			  |	     |	 2628 |      1 |     3	(34)| 00:00:01 |      0 |00:00:00.01 |	     3 |
|  22 |     SORT UNIQUE 		  |	     |	 2628 |      1 |     3	(34)| 00:00:01 |   2628 |00:00:00.01 |	     3 |
|  23 |      TABLE ACCESS BY INDEX ROWID  | T3	     |	    1 |      1 |     2	 (0)| 00:00:01 |      1 |00:00:00.01 |	     3 |
|* 24 |       INDEX RANGE SCAN		  | N_IDX01  |	    1 |      1 |     1	 (0)| 00:00:01 |      1 |00:00:00.01 |	     2 |
--------------------------------------------------------------------------------------------------------------------------------

Query Block Name / Object Alias (identified by operation id):
-------------------------------------------------------------

   1 - SEL$1
   4 - SEL$2   / X1@SEL$1
   5 - SEL$2
   6 - SEL$2   / M@SEL$2
   7 - SEL$2   / M@SEL$2
   9 - SEL$3   / X2@SEL$1
  10 - SEL$3
  11 - SEL$3   / N@SEL$3
  12 - SEL$3   / N@SEL$3
  13 - SEL$1_1 / T1@SEL$1
  16 - SEL$2   / X1@SEL$1_2
  18 - SEL$2   / M@SEL$2
  19 - SEL$2   / M@SEL$2
  20 - SEL$1_2 / T1@SEL$1_2
  21 - SEL$3   / X2@SEL$1_2
  23 - SEL$3   / N@SEL$3
  24 - SEL$3   / N@SEL$3

Outline Data
-------------

  /*+
      BEGIN_OUTLINE_DATA
      IGNORE_OPTIM_EMBEDDED_HINTS
      OPTIMIZER_FEATURES_ENABLE('11.2.0.4')
      DB_VERSION('11.2.0.4')
      OPT_PARAM('_optim_peek_user_binds' 'false')
      OPT_PARAM('_optimizer_use_feedback' 'false')
      ALL_ROWS
      OUTLINE_LEAF(@"SEL$2")
      OUTLINE_LEAF(@"SEL$3")
      OUTLINE_LEAF(@"SEL$1")
      OUTLINE_LEAF(@"SEL$1_1")
      USE_CONCAT(@"SEL$1" 8 OR_PREDICATES(1))
      OUTLINE_LEAF(@"SEL$1_2")
      OUTLINE(@"SEL$1")
      NO_ACCESS(@"SEL$1_1" "X1"@"SEL$1")
      NO_ACCESS(@"SEL$1_1" "X2"@"SEL$1")
      INDEX(@"SEL$1_1" "T1"@"SEL$1" ("T1"."OBJECT_TYPE" "T1"."OWNER" "T1"."NAMESPACE" "T1"."CREATED"))
      NO_ACCESS(@"SEL$1_2" "X1"@"SEL$1_2")
      INDEX(@"SEL$1_2" "T1"@"SEL$1_2" ("T1"."OBJECT_TYPE" "T1"."OWNER" "T1"."NAMESPACE" "T1"."CREATED"))
      NO_ACCESS(@"SEL$1_2" "X2"@"SEL$1_2")
      LEADING(@"SEL$1_1" "X1"@"SEL$1" "X2"@"SEL$1" "T1"@"SEL$1")
      LEADING(@"SEL$1_2" "X1"@"SEL$1_2" "T1"@"SEL$1_2" "X2"@"SEL$1_2")
      USE_MERGE_CARTESIAN(@"SEL$1_1" "X2"@"SEL$1")
      USE_NL(@"SEL$1_1" "T1"@"SEL$1")
      USE_NL(@"SEL$1_2" "T1"@"SEL$1_2")
      USE_NL(@"SEL$1_2" "X2"@"SEL$1_2")
      INDEX_RS_ASC(@"SEL$2" "M"@"SEL$2" ("T2"."OBJECT_ID"))
      USE_HASH_AGGREGATION(@"SEL$2")
      INDEX_RS_ASC(@"SEL$3" "N"@"SEL$3" ("T3"."OBJECT_ID"))
      END_OUTLINE_DATA
  */

Predicate Information (identified by operation id):
---------------------------------------------------

   7 - access("M"."OBJECT_ID"=33)
  12 - access("N"."OBJECT_ID"=33)
  13 - access("X2"."OBJECT_TYPE"="T1"."OBJECT_TYPE" AND "X2"."OWNER"="T1"."OWNER" AND "T1"."NAMESPACE"=4)
  19 - access("M"."OBJECT_ID"=33)
  20 - access("X1"."OBJECT_TYPE"="T1"."OBJECT_TYPE" AND "X1"."OWNER"="T1"."OWNER")
  21 - filter((LNNVL("X2"."OBJECT_TYPE"="T1"."OBJECT_TYPE") OR LNNVL("X2"."OWNER"="T1"."OWNER") OR
	      LNNVL("T1"."NAMESPACE"=4)))
  24 - access("N"."OBJECT_ID"=33)

SQL优化，写法很关键

发表于由

近期听到一位Oracle业界前辈，说道:”SQL优化，关键在写法”。我在生产过程中碰到的SQL问题，因为写法有误造成SQL产生严重的性能问题非常多，开发人员可能更关心我的代码功能是否实现，SQL上线前因测试系统环境、数据量与生产存在差异，导致SQL在生产上实际运行时效率远远小于预期，前几天，碰到如下这个SQL案例，个人感觉非常典型，SQL写法很关键！

SELECT count(*)
FROM pnrresultdata
WHERE TO_NUMBER(SYSDATE - CREATEtime)* 86400 > 5*60
  AND TO_NUMBER(SYSDATE - CREATEtime)* 86400 < 4*60*60
  AND username ='baosheng_dps'
  AND (getTime >0)
  AND postType='R'
  AND isSuccess=0

SQL逻辑很简单，只是单纯输出一下符合条件的count(*)，资源消耗如下图所示

然而，表中CREATETIME字段选择性很好，NUM_ROWS:64186660 NDV：2497536，此字段上没有索引，但是因为写法问题，常规组合索引中包含此字段也没有办法利用上索引，非常常见的原因：字段上参与了运算。

将SQL等价改写为：

SELECT count(*)
FROM pnrresultdata
WHERE CREATETIME < SYSDATE - interval '5' MINUTE
  AND CREATETIME > SYSDATE - interval '4' hour
  AND username ='baosheng_dps'
  AND (getTime >0)
  AND postType='R'
  AND isSuccess=0

原SQL执行计划，采用了ISSUCCESS列上的低效索引：

-------------------------------------
SQL_ID  76d58v13x8z90, child number 0
-------------------------------------
SELECT count(*)
FROM pnrresultdata
WHERE TO_NUMBER(SYSDATE - CREATEtime)* 86400 > 5*60
  AND TO_NUMBER(SYSDATE - CREATEtime)* 86400 < 4*60*60
  AND username ='baosheng_dps'
  AND (getTime >0)
  AND postType='R'
  AND isSuccess=0

Plan hash value: 3822156680

-----------------------------------------------------------------------------------------------------------------------------------------------------------
| Id  | Operation                    | Name                    | Starts | E-Rows |E-Bytes| Cost (%CPU)| E-Time   | A-Rows |   A-Time   | Buffers | Reads  |
-----------------------------------------------------------------------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT             |                         |      1 |        |       | 14814 (100)|          |      1 |00:00:01.03 |     296K|   4761 |
|   1 |  SORT AGGREGATE              |                         |      1 |      1 |    26 |            |          |      1 |00:00:01.03 |     296K|   4761 |
|*  2 |   TABLE ACCESS BY INDEX ROWID| PNRRESULTDATA           |      1 |      1 |    26 | 14814   (1)| 00:02:58 |    429 |00:00:01.03 |     296K|   4761 |
|*  3 |    INDEX RANGE SCAN          | PNRRESULTDATA_ISSUCCESS |      1 |    452K|       |  2765   (1)| 00:00:34 |    413K|00:00:00.06 |    2949 |     34 |
-----------------------------------------------------------------------------------------------------------------------------------------------------------

2 - filter(("USERNAME"='baosheng_dps' AND "POSTTYPE"='R' AND TO_NUMBER(SYSDATE@!-"CREATETIME")*86400>300 AND
              TO_NUMBER(SYSDATE@!-"CREATETIME")*86400<14400 AND "GETTIME">0))
   3 - access("ISSUCCESS"=0)

改写后，因其他字段缺失索引，目前状态仍不为最佳，同时出现了BITMAP CONVERSION

-------------------------------------
SQL_ID  00xz7m7u33wgg, child number 1
-------------------------------------
SELECT count(*)
FROM pnrresultdata
WHERE CREATETIME < SYSDATE - interval '5' MINUTE
  AND CREATETIME > SYSDATE - interval '4' hour
  AND username ='baosheng_dps'
  AND (getTime >0)
  AND postType='R'
  AND isSuccess=0

Plan hash value: 2537524006

------------------------------------------------------------------------------------------------------------------------------------------------------------------
| Id  | Operation                          | Name                     | Starts | E-Rows |E-Bytes| Cost (%CPU)| E-Time   | A-Rows |   A-Time   | Buffers | Reads  |
------------------------------------------------------------------------------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT                   |                          |      1 |        |       |  9313 (100)|          |      1 |00:00:00.23 |    4339 |   1531 |
|   1 |  SORT AGGREGATE                    |                          |      1 |      1 |    26 |            |          |      1 |00:00:00.23 |    4339 |   1531 |
|*  2 |   FILTER                           |                          |      1 |        |       |            |          |    429 |00:00:00.23 |    4339 |   1531 |
|*  3 |    TABLE ACCESS BY INDEX ROWID     | PNRRESULTDATA            |      1 |    429 | 11154 |  9313   (1)| 00:01:52 |    429 |00:00:00.23 |    4339 |   1531 |
|   4 |     BITMAP CONVERSION TO ROWIDS    |                          |      1 |        |       |            |          |   1164 |00:00:00.23 |    3477 |   1531 |
|   5 |      BITMAP AND                    |                          |      1 |        |       |            |          |      1 |00:00:00.23 |    3477 |   1531 |
|   6 |       BITMAP CONVERSION FROM ROWIDS|                          |      1 |        |       |            |          |      6 |00:00:00.06 |    1937 |      0 |
|*  7 |        INDEX RANGE SCAN            | PNRRESULTDATA_ISSUCCESS  |      1 |    452K|       |  2765   (1)| 00:00:34 |    288K|00:00:00.03 |    1937 |      0 |
|   8 |       BITMAP CONVERSION FROM ROWIDS|                          |      1 |        |       |            |          |      2 |00:00:00.17 |    1540 |   1531 |
|   9 |        SORT ORDER BY               |                          |      1 |        |       |            |          |    177K|00:00:00.16 |    1540 |   1531 |
|* 10 |         INDEX RANGE SCAN           | PNRRESULTDATA_CREATETIME |      1 |    452K|       |  1593   (1)| 00:00:20 |    177K|00:00:00.10 |    1540 |   1531 |
------------------------------------------------------------------------------------------------------------------------------------------------------------------

结合字段的选择性与在索引中的过滤必要，需要创建:

create index t1_idx01 on t1(username,postType,isSuccess,CREATEtime) &tablespace parallel ∥

借助sys_connect_by_path函数的SQL改写

发表于由

近期在网上看到一个这样的SQL需求，需求源自scott.emp表中的数据：

create or replace view v1 as select * from scott.emp;
create or replace view v2 as select * from scott.emp;

SQL> select * from v1;

     EMPNO ENAME      JOB	       MGR HIREDATE	    SAL       COMM     DEPTNO
---------- ---------- --------- ---------- --------- ---------- ---------- ----------
      7369 SMITH      CLERK	      7902 17-DEC-80	    800 		   20
      7499 ALLEN      SALESMAN	      7698 20-FEB-81	   1600        300	   30
      7521 WARD       SALESMAN	      7698 22-FEB-81	   1250        500	   30
      7566 JONES      MANAGER	      7839 02-APR-81	   2975 		   20
      7654 MARTIN     SALESMAN	      7698 28-SEP-81	   1250       1400	   30
      7698 BLAKE      MANAGER	      7839 01-MAY-81	   2850 		   30
      7782 CLARK      MANAGER	      7839 09-JUN-81	   2450 		   10
      7788 SCOTT      ANALYST	      7566 19-APR-87	   3000 		   20
      7839 KING       PRESIDENT 	   17-NOV-81	   5000 		   10
      7844 TURNER     SALESMAN	      7698 08-SEP-81	   1500 	 0	   30
      7876 ADAMS      CLERK	      7788 23-MAY-87	   1100 		   20
      7900 JAMES      CLERK	      7698 03-DEC-81	    950 		   30
      7902 FORD       ANALYST	      7566 03-DEC-81	   3000 		   20
      7934 MILLER     CLERK	      7782 23-JAN-82	   1300 		   10

14 rows selected.

SQL的需求是，得到员工编号、员工姓名、工作类别、主管编号、主管姓名信息。网上的网友是这么实现的：

SQL> select a.empno,a.ename,a.job,a.mgr as v1_mgr,b.empno as v2_mgr,b.ename from v1 a left join v2 b on a.MGR=b.empno order by 1;

     EMPNO ENAME      JOB	    V1_MGR     V2_MGR ENAME
---------- ---------- --------- ---------- ---------- ----------
      7369 SMITH      CLERK	      7902	 7902 FORD
      7499 ALLEN      SALESMAN	      7698	 7698 BLAKE
      7521 WARD       SALESMAN	      7698	 7698 BLAKE
      7566 JONES      MANAGER	      7839	 7839 KING
      7654 MARTIN     SALESMAN	      7698	 7698 BLAKE
      7698 BLAKE      MANAGER	      7839	 7839 KING
      7782 CLARK      MANAGER	      7839	 7839 KING
      7788 SCOTT      ANALYST	      7566	 7566 JONES
      7839 KING       PRESIDENT
      7844 TURNER     SALESMAN	      7698	 7698 BLAKE
      7876 ADAMS      CLERK	      7788	 7788 SCOTT
      7900 JAMES      CLERK	      7698	 7698 BLAKE
      7902 FORD       ANALYST	      7566	 7566 JONES
      7934 MILLER     CLERK	      7782	 7782 CLARK

14 rows selected.

Plan hash value: 2322654302

--------------------------------------------------------------------------------------------------------------
| Id  | Operation	    | Name | Starts | E-Rows | Cost (%CPU)| E-Time   | A-Rows |   A-Time   | Buffers |
--------------------------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT    |	   |	  1 |	     |	   7 (100)|	     |	   14 |00:00:00.01 |	  12 |
|   1 |  SORT ORDER BY	    |	   |	  1 |	  14 |	   7  (15)| 00:00:01 |	   14 |00:00:00.01 |	  12 |
|*  2 |   HASH JOIN OUTER   |	   |	  1 |	  14 |	   6   (0)| 00:00:01 |	   14 |00:00:00.01 |	  12 |
|   3 |    TABLE ACCESS FULL| EMP  |	  1 |	  14 |	   3   (0)| 00:00:01 |	   14 |00:00:00.01 |	   6 |
|   4 |    TABLE ACCESS FULL| EMP  |	  1 |	  14 |	   3   (0)| 00:00:01 |	   14 |00:00:00.01 |	   6 |
--------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   2 - access("MGR"="EMPNO")

此方法最终实现了目标需求，利用了自关联的方式，也就是emp表需要扫描2次，小表是OK的，emp表中主管与员工是存在层级关系的，我们能否利用上层级查询消除自关联？

SQL> set line 1000 pagesize 200
col new_name for a20
col new_mgr for a20
col mgr_name for a60
select empno,ename,job,mgr,mgr_name from (
select empno,ename,job,mgr,path,regexp_substr(path,'[^,]+',1,decode((lv-1),0,null,(lv-1))) as mgr_name from (
SELECT empno,
       ename,
       job,
       mgr,
       LEVEL lv,
       sys_connect_by_path(ename,',') AS path
FROM emp connect by prior empno=mgr start with mgr is null));SQL> SQL> SQL> SQL>   2    3    4    5    6    7    8    9

     EMPNO ENAME      JOB	       MGR MGR_NAME
---------- ---------- --------- ---------- ------------------------------------------------------------
      7839 KING       PRESIDENT
      7566 JONES      MANAGER	      7839 KING
      7788 SCOTT      ANALYST	      7566 JONES
      7876 ADAMS      CLERK	      7788 SCOTT
      7902 FORD       ANALYST	      7566 JONES
      7369 SMITH      CLERK	      7902 FORD
      7698 BLAKE      MANAGER	      7839 KING
      7499 ALLEN      SALESMAN	      7698 BLAKE
      7521 WARD       SALESMAN	      7698 BLAKE
      7654 MARTIN     SALESMAN	      7698 BLAKE
      7844 TURNER     SALESMAN	      7698 BLAKE
      7900 JAMES      CLERK	      7698 BLAKE
      7782 CLARK      MANAGER	      7839 KING
      7934 MILLER     CLERK	      7782 CLARK

14 rows selected.


Plan hash value: 422387769

-----------------------------------------------------------------------------------------------------------------------------------
| Id  | Operation				 | Name | Starts | E-Rows | Cost (%CPU)| E-Time   | A-Rows |   A-Time	| Buffers |
-----------------------------------------------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT			 |	|      1 |	  |	3 (100)|	  |	14 |00:00:00.01 |	2 |
|   1 |  VIEW					 |	|      1 |	3 |	3  (34)| 00:00:01 |	14 |00:00:00.01 |	2 |
|*  2 |   CONNECT BY NO FILTERING WITH START-WITH|	|      1 |	  |	       |	  |	14 |00:00:00.01 |	2 |
|   3 |    TABLE ACCESS FULL			 | EMP	|      1 |     14 |	2   (0)| 00:00:01 |	14 |00:00:00.01 |	2 |
-----------------------------------------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):
---------------------------------------------------

   2 - access("MGR"=PRIOR NULL)
       filter("MGR" IS NULL)

利用sys_connect_by_path与regexp_substr利用层级关系截取，消除了自关联，并且emp表只访问了1次。

MRP0进程Hung？

发表于由

前天晚上，同事发来微信求助，监控到一套2节点数据库RAC 数据库主备库同步状态异常，并且同事经过分析发现造成此问题的是因为Dataguard MRP0进程存在，但是停止在某一个seqence#上，应用的sequnce#与block不进行恢复。

随即登录备库数据库查看同步状态，发现MRP0进程停滞在sequnce：197788与block：186030上，实际上并没有进行“APPLYING_LOG”。

SQL> set linesize 200
select process,status,client_process,thread#,sequence#,block#,active_agents,known_agents from gv$managed_standby where process in ('LNS','RFS','MRP0') and  THREAD# <> 0
SQL>   2  ;

PROCESS   STATUS       CLIENT_P    THREAD#  SEQUENCE#     BLOCK# ACTIVE_AGENTS KNOWN_AGENTS
--------- ------------ -------- ---------- ---------- ---------- ------------- ------------
RFS       IDLE         LGWR              1     199217     123144             0            0
RFS       IDLE         LGWR              2     142409      77956             0            0
MRP0      APPLYING_LOG N/A               1     197788     186030             9            9

此日志197788归档日志文件存在与备库，并且同事反馈尝试alter database register logfile、主库RMAN重新恢复此197788归档日志，均无效。

查询v$archived_log确认197788这个归档文件为20210109 15:00左右主库产生的，分别查看一下主库/备库的alert日志，看看那时数据库有无异常情况发生：

节点1，传输至备时出现异常：
Thread 1 advanced to log sequence 197788 (LGWR switch)
  Current log# 5 seq# 197788 mem# 0: +DG_REDO/Travelskydba/onlinelog/group_5.287.1003922183
  Current log# 5 seq# 197788 mem# 1: +DG_REDO/Travelskydba/onlinelog/group_5.286.1003922183
Sat Jan 09 15:32:25 2021
Archived Log entry 275332 added for thread 1 sequence 197787 ID 0x9c755e67 dest 1:
Sat Jan 09 15:32:25 2021
ARCj: Standby redo logfile selected for thread 1 sequence 197787 for destination LOG_ARCHIVE_DEST_2
Sat Jan 09 15:33:14 2021
LNS: Standby redo logfile selected for thread 1 sequence 197788 for destination LOG_ARCHIVE_DEST_2
Sat Jan 09 15:43:17 2021
Thread 1 advanced to log sequence 197789 (LGWR switch)
  Current log# 1 seq# 197789 mem# 0: +DG_REDO/Travelskydba/onlinelog/group_1.295.1003922179
  Current log# 1 seq# 197789 mem# 1: +DG_REDO/Travelskydba/onlinelog/group_1.294.1003922179
Sat Jan 09 15:43:17 2021
Archived Log entry 275335 added for thread 1 sequence 197788 ID 0x9c755e67 dest 1:
Sat Jan 09 15:47:06 2021
WARN: ARC1: Terminating pid 4047 hung on an I/O operation
Killing 1 processes with pids 4047 (Process by index) in order to remove hung processes. Requested by OS process 31580 on instance 1
ARC1: Error 16198 due to hung I/O operation to LOG_ARCHIVE_DEST_2
ARCo: Standby redo logfile selected for thread 1 sequence 197788 for destination LOG_ARCHIVE_DEST_2

节点2，传输至备库时出现异常：
Sat Jan 09 15:47:15 2021
Archived Log entry 275337 added for thread 2 sequence 141662 ID 0x9c755e67 dest 1:
Sat Jan 09 15:47:35 2021
WARN: ARC2: Terminating pid 27590 hung on an I/O operation
Killing 1 processes with pids 27590 (Process by index) in order to remove hung processes. Requested by OS process 27465 on instance 2
ARC2: Error 16198 due to hung I/O operation to LOG_ARCHIVE_DEST_2
Sat Jan 09 15:47:37 2021
NSA2 started with pid=29, OS id=2625
Sat Jan 09 15:47:42 2021


备库节点：
Archived Log entry 77427 added for thread 1 sequence 197786 ID 0x9c755e67 dest 1:
Media Recovery Log /oracle/archive_Travelskydba/Travelskydba/2_141661_853598219.arc
Media Recovery Waiting for thread 2 sequence 141662 (in transit)
Recovery of Online Redo Log: Thread 2 Group 11 Seq 141662 Reading mem 0
  Mem# 0: /oracle/redo_Travelskydba/Travelskydba/group_11.301.1003923935
  Mem# 1: /oracle/redo_Travelskydba/Travelskydba/group_11.304.1003923937
Media Recovery Waiting for thread 1 sequence 197788 (in transit)
Recovery of Online Redo Log: Thread 1 Group 7 Seq 197788 Reading mem 0
  Mem# 0: /oracle/redo_Travelskydba/Travelskydba/group_7.282.1003923169
  Mem# 1: /oracle/redo_Travelskydba/Travelskydba/group_7.280.1003923169

备库节点在1月9日 16:24:31时已经应用完成197788日志
Sat Jan 09 16:24:31 2021
Media Recovery Log /oracle/archive_Travelskydba/Travelskydba/1_197788_853598219.arc

197788这个日志已经应用完毕，并且197789日志也完好的存在与备库节点 ，那么很有可能目前备库MRP0进程不工作的原因是在等其他日志应用完毕，。备库应用日志需要连续，那么是否有可能其他节点或本节点的其他日志？

我们可以利用主库如下sql查询进行确认：

SQL> SELECT FIRST_CHANGE#,
       THREAD#,
       DEST_ID,
       STATUS,
       FAL,
       APPLIED,
       DELETED,
       to_char(FIRST_TIME,'yyyymmdd hh24:mi:ss') FIRST_TIME,
       to_char(COMPLETION_TIME,'yyyymmdd hh24:mi:ss') COMPLETION_TIME,
       sequence#
FROM v$archived_log
WHERE to_char(COMPLETION_TIME,'yyyymmdd hh24:mi:ss') BETWEEN '20210109 15:00:17' AND '20210109 16:00:17'  order by 1,5  2    3    4    5    6    7    8    9   10   11   12  ;

   FIRST_CHANGE#          THREAD#          DEST_ID S FAL APPLIED   DEL FIRST_TIME        COMPLETION_TIME          SEQUENCE#
---------------- ---------------- ---------------- - --- --------- --- ----------------- ----------------- ----------------
   9555246783243                2                2 A NO  YES       NO  20210109 14:32:30 20210109 15:04:31           141659
   9555246783243                2                1 D NO  NO        YES 20210109 14:32:30 20210109 15:04:32           141659
   9555247407959                1                1 D NO  NO        YES 20210109 14:54:15 20210109 15:04:31           197783
   9555247407959                1                2 A NO  YES       NO  20210109 14:54:15 20210109 15:04:31           197783
   9555247700807                1                2 A NO  YES       NO  20210109 15:04:30 20210109 15:15:10           197784
   9555247700807                1                1 D NO  NO        YES 20210109 15:04:30 20210109 15:15:10           197784
   9555247701783                2                2 A NO  YES       NO  20210109 15:04:31 20210109 15:32:20           141660
   9555247701783                2                1 D NO  NO        YES 20210109 15:04:31 20210109 15:32:21           141660
   9555248017764                1                1 D NO  NO        YES 20210109 15:15:10 20210109 15:25:40           197785
   9555248017764                1                2 A NO  YES       NO  20210109 15:15:10 20210109 15:25:40           197785
   9555248313954                1                2 A NO  YES       NO  20210109 15:25:40 20210109 15:33:14           197786
   9555248313954                1                1 D NO  NO        YES 20210109 15:25:40 20210109 15:32:19           197786
   9555248508993                1                1 D NO  NO        YES 20210109 15:32:19 20210109 15:32:25           197787
   9555248508993                1                2 A YES YES       NO  20210109 15:32:19 20210109 15:32:26           197787
   9555248509181                2                1 D NO  NO        YES 20210109 15:32:20 20210109 15:32:23           141661
   9555248509181                2                2 A NO  YES       NO  20210109 15:32:20 20210109 15:32:23           141661
   9555248510236                2                1 D NO  NO        YES 20210109 15:32:23 20210109 15:47:15           141662
   9555248510774                1                1 D NO  NO        YES 20210109 15:32:25 20210109 15:43:17           197788
   9555248831803                1                1 D NO  NO        YES 20210109 15:43:17 20210109 15:47:14           197789
   9555248831803                1                2 A YES NO        NO  20210109 15:43:17 20210109 15:52:30           197789
   9555248943929                1                1 D NO  NO        YES 20210109 15:47:14 20210109 15:52:14           197790
   9555248944032                2                1 D NO  NO        YES 20210109 15:47:15 20210109 15:47:42           141663
   9555248944032                2                2 A YES NO        NO  20210109 15:47:15 20210109 15:53:18           141663
   9555248950448                2                1 D NO  NO        YES 20210109 15:47:42 20210109 15:53:18           141664
   9555248950448                2                2 A YES NO        NO  20210109 15:47:42 20210109 15:55:13           141664

25 rows selected.

上述查询确认后，每个sequence应当归档到dest_id=1（本地），dest_id=2(备库)，但是发现thread 2的141662，未显示归档到DEST_ID=2，并且下一个日志便是197788
Media Recovery Log /oracle/archive_Travelskydba/Travelskydba/2_141661_853598219.arc
Media Recovery Waiting for thread 2 sequence 141662 (in transit)
Recovery of Online Redo Log: Thread 2 Group 11 Seq 141662 Reading mem 0
  Mem# 0: /oracle/redo_Travelskydba/Travelskydba/group_11.301.1003923935
  Mem# 1: /oracle/redo_Travelskydba/Travelskydba/group_11.304.1003923937
Media Recovery Waiting for thread 1 sequence 197788 (in transit)
Recovery of Online Redo Log: Thread 1 Group 7 Seq 197788 Reading mem 0
  Mem# 0: /oracle/redo_Travelskydba/Travelskydba/group_7.282.1003923169
  Mem# 1: /oracle/redo_Travelskydba/Travelskydba/group_7.280.1003923169
Sat Jan 09 15:49:02 2021
RFS[31]: Possible network disconnect with primary database
后续，备库一值在读取141662这个日志文件，但

Recovery of Online Redo Log: Thread 2 Group 11 Seq 141662 Reading mem 0
  Mem# 0: /oracle/redo_Travelskydba/Travelskydba/group_11.301.1003923935
  Mem# 1: /oracle/redo_Travelskydba/Travelskydba/group_11.304.1003923937

Mon Jan 18 20:42:42 2021
Managed Standby Recovery starting Real Time Apply
Parallel Media Recovery started with 8 slaves
Waiting for all non-current ORLs to be archived...
All non-current ORLs have been archived.
Recovery of Online Redo Log: Thread 2 Group 11 Seq 141662 Reading mem 0
  Mem# 0: /oracle/redo_Travelskydba/Travelskydba/group_11.301.1003923935
  Mem# 1: /oracle/redo_Travelskydba/Travelskydba/group_11.304.1003923937

此时，主库141662这个归档认为已经传输到备库并且已经删除，但备库实际并未接收到。Threa#1 的197788无法应用的根因为Thread# 2 归档141662并未应用。

让同事将141662归档从主库归档备份中恢复出来 ，拷贝至备库注册或等待备库（fal_client）从主库（fal_server）中获取。同事恢复此归档文件后，备库MRP0进程立即开始工作，进行正常的日志应用，同时主库的v$archived_log中的日志记录变成了复合预期的状态：

SQL> SELECT FIRST_CHANGE#,
       THREAD#,
       DEST_ID,
       STATUS,
       FAL,
       APPLIED,
       DELETED,
       to_char(FIRST_TIME,'yyyymmdd hh24:mi:ss') FIRST_TIME,
       to_char(COMPLETION_TIME,'yyyymmdd hh24:mi:ss') COMPLETION_TIME,
       sequence#
FROM v$archived_log
WHERE sequence#=141662  2    3    4    5    6    7    8    9   10   11   12  ;

   FIRST_CHANGE#          THREAD#          DEST_ID S FAL APPLIED   DEL FIRST_TIME        COMPLETION_TIME          SEQUENCE#
---------------- ---------------- ---------------- - --- --------- --- ----------------- ----------------- ----------------
   9555248510236                2                1 D NO  NO        YES 20210109 15:32:23 20210109 15:47:15           141662
   9555248510236                2                1 A NO  NO        NO  20210109 15:32:23 20210118 21:39:53           141662
   9555248510236                2                2 A YES YES       NO  20210109 15:32:23 20210118 21:40:33           141662

利用sysmetric_history与dba_hist_event_histogram定位IO性能问题

发表于由

近期发现，公司生产4套数据库从12月9日起，每周三22:00-22:30时间段均有应用事务DML缓慢的现象，IO等待事件明显增多：

IO等待类事件明显均有显著抬头的现象，例如log file sync等，但是我们如何定位是否真正的数据库IO真正出现问题？是因还是果？是否是io requeset变多还是IO真正出现问题？

问题时间段的AWR：

AWR中的Avg Wait极有可能被平均
另外一套库的显示的较为直观，log file sync平均等待高达17ms之多

换一个角度，我们从Oracle提供的数据库内部的v$metric_history与dba_hist_sysmetric_history动态视图中可以从“ Average Synchronous Single-Block Read Latency、I/O Megabytes per Second、I/O Requests per Second”等指标中辅助定位：

select to_char(end_time, 'yyyymmdd hh24:mi:ss') as time,
       max(case
             when metric_name = 'Average Synchronous Single-Block Read Latency' then
              round(value,2)
             else null
           end) as "Single Block Read Latency",
       max(case
             when metric_name = 'I/O Megabytes per Second' then
              round(value,2)
             else null
           end) as "IO Megabytes per Second",
       max(case
             when metric_name = 'I/O Requests per Second' then
              round(value,2)
             else null
           end) as "I/O Requests per Second"
  from dba_hist_sysmetric_history where instance_number=1 and to_char(end_time, 'yyyymmdd hh24:mi:ss') between '20210106 22:00:00' and '20210106 23:00:00'
 group by to_char(end_time, 'yyyymmdd hh24:mi:ss') order by 1

TIME              Single Block Read Latency IO Megabytes per Second I/O Requests per Second
----------------- ------------------------- ----------------------- -----------------------
20210106 21:00:44                      1.75                   23.69                 2060.17
20210106 21:01:44                       2.1                   13.32                 1474.73
20210106 21:02:43                      1.99                    18.6                 1716.56
20210106 21:03:43                      1.43                   11.54                 1089.31
20210106 21:04:43                      1.69                   20.77                 1567.28
20210106 21:05:43                      1.61                   17.92                 1806.92
20210106 21:06:44                      2.21                   27.95                 2466.91
20210106 21:07:44                      1.63                   11.29                 1052.18
20210106 21:08:44                      2.01                   17.23                 1729.85
20210106 21:09:43                      1.63                   12.53                  1309.2
20210106 21:10:43                      1.36                   15.53                 1180.81
20210106 21:11:43                      2.57                   12.97                 1399.38
20210106 21:12:43                      1.42                   16.71                 1323.95
20210106 21:13:44                      1.65                   10.37                 1367.22
20210106 21:14:44                      1.42                   20.49                    1493
20210106 21:15:44                      1.66                    8.21                 1186.28
20210106 21:16:43                      2.39                   23.23                 2012.56
20210106 21:17:43                       1.3                   11.34                 1219.04
20210106 21:18:43                      1.15                   15.06                 1219.79
20210106 21:19:43                      1.66                       7                 1057.58
20210106 21:20:44                      1.38                   19.74                 1402.93
20210106 21:21:44                      2.59                    7.66                 1086.08
20210106 21:22:44                      1.22                   16.51                 1307.65
20210106 21:23:43                      1.39                   12.68                 1391.17
20210106 21:24:43                      1.43                   15.38                 1255.99
20210106 21:25:43                      1.37                   13.82                 1489.76
20210106 21:26:44                       1.9                   24.64                 2456.92
20210106 21:27:44                      1.49                    7.35                 1232.54
20210106 21:28:44                      1.06                   50.22                  1287.7
20210106 21:29:44                      2.06                   31.16                 1516.66
20210106 21:30:43                      1.21                   67.67                 1750.49
20210106 21:31:43                      2.52                   67.19                  1398.3
20210106 21:32:43                      1.68                   38.94                 1831.17
20210106 21:33:44                      1.46                    9.81                 1366.68
20210106 21:34:44                      1.61                   17.64                 1447.77
20210106 21:35:44                      1.52                   15.25                 1860.36
20210106 21:36:44                      1.61                   26.07                 2350.26
20210106 21:37:43                      2.18                   11.01                 1161.19
20210106 21:38:43                      1.38                   16.08                 1438.71
20210106 21:39:44                      1.56                   10.44                 1005.47
20210106 21:40:44                      1.23                   15.76                 1202.61
20210106 21:41:44                      2.21                    8.56                 1374.73
20210106 21:42:44                      1.71                    19.9                 1298.54
20210106 21:43:44                      1.49                    9.08                 1196.41
20210106 21:44:43                      1.79                   18.07                 1715.96
20210106 21:45:43                      1.86                   11.46                 1055.36
20210106 21:46:44                      1.36                   22.71                  1960.6
20210106 21:47:44                      1.13                    27.1                 1589.31
20210106 21:48:44                      1.39                   18.62                 1142.78
20210106 21:49:44                      1.88                    6.48                  904.06
20210106 21:50:44                      1.22                   20.12                  1420.4
20210106 21:51:43                      1.79                    7.54                 1054.08
20210106 21:52:44                      1.32                   16.79                 1246.04
20210106 21:53:44                       1.5                   12.89                 1509.54
20210106 21:54:44                      1.59                   14.58                  961.99
20210106 21:55:44                      1.75                    8.41                 1114.03
20210106 21:56:44                      1.42                   29.02                 2388.62
20210106 21:57:44                       1.7                    6.22                  815.38
20210106 21:58:43                      1.36                   14.27                 1024.69
20210106 21:59:44                      1.89                   10.66                 1133.77
20210106 22:00:44                      1.02                   52.87                 3232.29
20210106 22:01:44                       .71                   94.45                 4846.43
20210106 22:02:44                      5.28                   83.54                 2627.49
20210106 22:03:44                      7.04                   69.19                 2067.08
20210106 22:04:44                      7.07                   74.68                 2382.61
20210106 22:05:43                      4.87                   79.73                 2654.56
20210106 22:06:44                      5.94                   90.77                 3937.21
20210106 22:07:44                      8.01                   31.11                 1074.18
20210106 22:08:44                      6.16                   26.27                 1639.99
20210106 22:09:44                      2.71                    31.5                 1797.32
20210106 22:10:44                      5.12                   37.47                 1533.45
20210106 22:11:44                      5.04                   62.63                 1520.07
20210106 22:12:44                      3.81                   35.91                 1402.06
20210106 22:13:44                      3.66                   18.25                 1626.73
20210106 22:14:44                      3.01                   61.43                  2179.6
20210106 22:15:44                      2.59                   75.41                 1789.91
20210106 22:16:44                      3.13                    91.9                 2745.88
20210106 22:17:44                      2.97                   86.56                  1798.5
20210106 22:18:45                      2.33                   84.64                 1505.69
20210106 22:19:44                      1.74                    72.1                 1378.42
20210106 22:20:44                      1.84                   91.02                 1957.69
20210106 22:21:44                      2.72                   68.14                 1447.02
20210106 22:22:44                      2.18                   80.76                 1649.19
20210106 22:23:44                      2.75                   75.58                 1676.43
20210106 22:24:44                       2.2                   36.45                 1502.78
20210106 22:25:45                      2.21                   21.77                 1429.71
20210106 22:26:44                      2.61                   40.56                 2667.25
20210106 22:27:44                      2.09                   19.95                 1068.11
20210106 22:28:44                      1.39                   57.66                 1419.02
20210106 22:29:44                      1.61                   44.66                 1701.81
20210106 22:30:44                       1.2                   74.61                 2328.65
20210106 22:31:45                      1.29                   83.01                 2020.88
20210106 22:32:45                       .76                   94.96                 2706.07
20210106 22:33:44                      1.02                   22.84                 2032.87
20210106 22:34:44                       .74                   58.67                 2297.62
20210106 22:35:44                      1.76                   81.66                 1727.17
20210106 22:36:44                       .58                    66.2                 4839.24
20210106 22:37:44                       .87                   29.04                 1617.19
20210106 22:38:45                      1.54                   53.16                 1539.99
20210106 22:39:45                      1.21                    51.9                  1420.5
20210106 22:40:44                         1                   49.76                 1646.52
20210106 22:41:44                      2.23                   74.05                 1761.78
20210106 22:42:44                      1.17                  146.94                 1505.77
20210106 22:43:44                      1.39                   75.94                 1620.12
20210106 22:44:45                      1.07                   73.43                 2045.32
20210106 22:45:45                       .44                   82.36                 2572.26
20210106 22:46:44                         2                   54.02                 1909.32
20210106 22:47:44                      1.61                   43.08                 1479.45
20210106 22:48:44                      1.29                   47.81                 1296.04
20210106 22:49:44                      1.39                    50.6                 1337.25
20210106 22:50:44                       1.3                   55.93                 1497.06
20210106 22:51:45                      1.85                   43.28                 1074.38
20210106 22:52:45                      1.06                   93.48                 1559.25
20210106 22:53:44                      1.17                   39.43                 2132.45
20210106 22:54:44                       .54                   50.37                 2259.39
20210106 22:55:44                      1.35                   47.12                 1347.34
20210106 22:56:44                      2.09                   57.55                 2647.21
20210106 22:57:45                      1.33                   46.67                  980.51
20210106 22:58:45                       .68                   74.52                 1480.33
20210106 22:59:45                      1.19                    51.5                 1871.55

可以从上述三个指标中观察，Single Block Read Latency高的时候，IO请求量并不匹配，并非因为IO请求量导致IO效率下降，延时变高。
延时指标高，IO量并不大
继续阅读 →

关于QB_NAME的hint

发表于由

近期，在优化一个SQL时用到了QB_NAME的HINT，此HINT我经常使用的原因目的是让子查询单独作为一个整体，与其他表关联时可以进行调整驱动顺序，举例：

SELECT b.owner,
       b.object_name,
       b.created,
       b.status
FROM albert.fc b
WHERE 1=1
  AND b.object_id IN
    (SELECT c.object_id
     FROM albert.P c
     WHERE c.owner='NFS_SN')
执行计划如下：
Plan hash value: 3977992979

--------------------------------------------------------------------------------------------------------------------------
| Id  | Operation		     | Name    | Starts | E-Rows | Cost (%CPU)| E-Time	 | A-Rows |   A-Time   | Buffers |
--------------------------------------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT	     |	       |      1 |	 |   569 (100)| 	 |    119 |00:00:00.05 |    1445 |
|*  1 |  HASH JOIN RIGHT SEMI	     |	       |      1 |  64830 |   569  (11)| 00:00:07 |    119 |00:00:00.05 |    1445 |
|   2 |   TABLE ACCESS BY INDEX ROWID| P       |      1 |   2192 |   116   (0)| 00:00:02 |    119 |00:00:00.01 |      17 |
|*  3 |    INDEX RANGE SCAN	     | P_IDX01 |      1 |   2192 |     6   (0)| 00:00:01 |    119 |00:00:00.01 |       2 |
|   4 |   TABLE ACCESS FULL	     | FC      |      1 |   3000K|   439  (11)| 00:00:06 |    100K|00:00:00.02 |    1428 |
--------------------------------------------------------------------------------------------------------------------------

Query Block Name / Object Alias (identified by operation id):
-------------------------------------------------------------

   1 - SEL$5DA710D3
   2 - SEL$5DA710D3 / C@SEL$2
   3 - SEL$5DA710D3 / C@SEL$2
   4 - SEL$5DA710D3 / B@SEL$1

Outline Data
-------------

  /*+
      BEGIN_OUTLINE_DATA
      IGNORE_OPTIM_EMBEDDED_HINTS
      OPTIMIZER_FEATURES_ENABLE('11.2.0.4')
      DB_VERSION('11.2.0.4')
      OPT_PARAM('_optim_peek_user_binds' 'false')
      OPT_PARAM('_optimizer_use_feedback' 'false')
      ALL_ROWS
      OUTLINE_LEAF(@"SEL$5DA710D3")
      UNNEST(@"SEL$2")
      OUTLINE(@"SEL$1")
      OUTLINE(@"SEL$2")
      FULL(@"SEL$5DA710D3" "B"@"SEL$1")
      INDEX_RS_ASC(@"SEL$5DA710D3" "C"@"SEL$2" ("P"."OWNER"))
      LEADING(@"SEL$5DA710D3" "B"@"SEL$1" "C"@"SEL$2")
      USE_HASH(@"SEL$5DA710D3" "C"@"SEL$2")
      SWAP_JOIN_INPUTS(@"SEL$5DA710D3" "C"@"SEL$2")
      END_OUTLINE_DATA
  */

Predicate Information (identified by operation id):
---------------------------------------------------

   1 - access("B"."OBJECT_ID"="C"."OBJECT_ID")
   3 - access("C"."OWNER"='NFS_SN')
继续阅读 →

诡异的ORA-27090: Unable to reserve kernel resources for asynchronous disk I/O

发表于由

今年以来，公司多套RAC数据库（版本：11.2.0.4）ASM实例频繁报出ORA-27090: Unable to reserve kernel resources for asynchronous disk I/O错误。这些数据库早在2016年时印象中便出现了此类报错，并且报错并非单个数据库偶发现象，而是大面积爆发，从3月至今仍然有些许数据库会抛出零星错误出现。

什么是ORA-27090？<参考 Doc ID 579108.1 >文中提到，此类报错的原因是操作系统异步IO请求参数 aio-max-nr 过低并且需要调整并发未完成的异步请求数目，避免异步IO请求失败的情况， Oracle官方文档中的建议值如下：

The "aio-max-nr" kernel limit is too low.
io_setup(4096, 0x66e1588) = -1 EAGAIN (Resource temporarily unavailable),

但是很诡异的是，我们的数据库早在2016年左右（第一次触发此问题）时，已经将该参数调整至4194304，理论上是不应该触发异步IO不足的问题。并且此报错风险性较高，ASM实例异步IO失败会导致数据库面临crash问风险，例如DBWR将脏块落盘（数据文件）时，如果此时DBWR进程无法进行时，数据库崩溃等其他异常行为会有极大可能性的。虽然可以将systcl.conf中的aio-max-nr一直调大，但是总归不是长久之计，并且在某年某月时会再次“爆发”。

最可怕的是，通过分析alert中的trace文件时，并没有发现任何有价值信息，所有的线索就是异步IO请求超过最大限制，导致某些IO请求失败抛出错误。。。

通过查看cat /proc/sys/fs/aio-nr查看当前的异步IO请求数量，此值偶尔下降但总量一直处于增长态势， 此时严重怀疑是否数据库中有某些进程执行异步IO请求后并没有释放IO描述符？造成异步IO描述符泄露？

我们数据库集群后发现异步IO请求变回归到正常范围内,但是态势仍然处于上升趋势:

ora11g@travelskydba-rac$ cat /proc/sys/fs/aio-nr 
22784
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ORA-00704: bootstrap process failure故障修复

发表于由

近日，同事反馈一套测试测试数据库宕机，进行重启数据库操作时发现数据库无法open，抛出ORA-00704: bootstrap process failure错误，版本为11.2.0.4

SQL> startup;
ORACLE instance started.

Total System Global Area 1068937216 bytes
Fixed Size		    2260088 bytes
Variable Size		  671089544 bytes
Database Buffers	  390070272 bytes
Redo Buffers		    5517312 bytes
Database mounted.
ORA-01092: ORACLE instance terminated. Disconnection forced
ORA-00704: bootstrap process failure
ORA-00604: error occurred at recursive SQL level 1
ORA-00942: table or view does not exist
Process ID: 57338
Session ID: 96 Serial number: 3

错误一并抛出了ORA-00942: table or view does not exist错误，应该是系统表丢失导致的bootstrap失败，并且alert日志中没有任何其他日志输出。

将数据库启动到nomount与mount状态，利用10046 event跟踪bootstrap过程：
SQL> oradebug setmypid
Statement processed.
SQL> oradebug tracefile_name
/opt/app/ora11g/albert/diag/rdbms/prod3/PROD3/trace/PROD3_ora_57585.trc
SQL> oradebug event 10046 trace name context forever,level 12;
Statement processed.
SQL> alter database mount;

Database altered.

SQL> alter database open;
alter database open
*
ERROR at line 1:
ORA-01092: ORACLE instance terminated. Disconnection forced
ORA-00704: bootstrap process failure
ORA-00604: error occurred at recursive SQL level 1
ORA-00942: table or view does not exist
Process ID: 57585
Session ID: 96 Serial number: 3

访问/opt/app/ora11g/albert/diag/rdbms/prod3/PROD3/trace/PROD3_ora_57585.trc发现访问access$表时抛出异常：

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