一次SQL分页的优化
来源：未知 责任编辑：智问网络 发表时间:2013-11-10 20:24 点击:次
今天优化了一个分页的SQL，以前虽然做了上千个SQL的优化，不过都是一些OLAP的，虽然也有OLTP的不过从来没做过分页优化，所以这里记录一下。
SQL和执行计划如下：
SQL> SELECT A.ROWNO,EMS_EVENT_VIEW.* FROM EMS_EVENT_VIEW,
2 (SELECT * FROM (SELECT ROW_NUMBER() OVER(ORDER BY first_occurrence_time DESC) AS ROWNO,EVENT_ID
3 FROM EMS_EVENT_VIEW
WHERE (first_occurrence_time>to_date('2012-02-22 00:00:00','yyyy-mm-dd hh24:mi:ss')
4 5 and first_occurrence_time<to_date('2012-02-29 09:42:35','yyyy-mm-dd hh24:mi:ss'))
or (last_occurrence_time>to_date('2012-02-22 00:00:00','yyyy-mm-dd hh24:mi:ss')
and last_occurrence_time<to_date('2012-02-29 09:42:35','yyyy-mm-dd hh24:mi:ss')))
6 7 8 WHERE ROWNO>=0 AND ROWNO<=20) A
9 WHERE EMS_EVENT_VIEW.EVENT_ID=A.EVENT_ID;
Plan hash value: 2052413575
-------------------------------------------------------------------------------------------------------------------------------------------------------
PLAN_TABLE_OUTPUT
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | OMem | 1Mem | Used-Mem |
-------------------------------------------------------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | | 20 |00:00:53.37 | 757K| | | |
|* 1 | HASH JOIN | | 1 | 81G| 20 |00:00:53.37 | 757K| 1179K| 1179K| 6598K (0)|
|* 2 | VIEW | | 1 | 2104K| 20 |00:00:30.83 | 101K| | | |
|* 3 | WINDOW SORT PUSHED RANK | | 1 | 2104K| 21 |00:00:30.83 | 101K| 4096 | 4096 | 4096 (0)|
|* 4 | FILTER | | 1 | | 1255K|00:00:30.10 | 101K| | | |
| 5 | VIEW | EMS_EVENT_VIEW | 1 | 2104K| 1255K|00:00:28.85 | 101K| | | |
| 6 | UNION-ALL | | 1 | | 1255K|00:00:28.85 | 101K| | | |
| 7 | CONCATENATION | | 1 | | 0 |00:00:00.01 | 335 | | | |
| 8 | TABLE ACCESS BY INDEX ROWID| EMS_EVENT | 1 | 1 | 0 |00:00:00.01 | 63 | | | |
|* 9 | INDEX RANGE SCAN | LAST_OCCURRENCE_TIME_INDEX | 1 | 1 | 0 |00:00:00.01 | 63 | | | |
|* 10 | TABLE ACCESS BY INDEX ROWID| EMS_EVENT | 1 | 1 | 0 |00:00:00.01 | 272 | | | |
|* 11 | INDEX RANGE SCAN | FIRST_OCCURRENCE_INDEX | 1 | 1 | 0 |00:00:00.01 | 272 | | | |
|* 12 | VIEW | index_join_006 | 1 | 2104K| 1255K|00:00:28.84 | 100K| | | |
|* 13 | HASH JOIN | | 1 | | 3863K|00:00:26.50 | 100K| 195M| 9M| 248M (0)|
|* 14 | HASH JOIN | | 1 | | 3863K|00:00:13.87 | 63020 | 160M| 10M| 214M (0)|
| 15 | PARTITION RANGE ALL | | 1 | 2104K| 3863K|00:00:00.01 | 31419 | | | |
| 16 | INDEX FAST FULL SCAN | IDX_FIRSTTIME_201202 | 338 | 2104K| 3863K|00:00:00.07 | 31419 | | | |
| 17 | PARTITION RANGE ALL | | 1 | 2104K| 3863K|00:00:00.01 | 31601 | | | |
| 18 | INDEX FAST FULL SCAN | IDX_LASTOCCURRENCE_201202 | 338 | 2104K| 3863K|00:00:00.06 | 31601 | | | |
| 19 | INDEX FAST FULL SCAN | PK_EMS_EVENT_HISTORY_201202 | 1 | 2104K| 3863K|00:00:00.01 | 37894 | | | |
| 20 | VIEW | EMS_EVENT_VIEW | 1 | 3864K| 3867K|00:00:19.34 | 656K| | | |
| 21 | UNION-ALL | | 1 | | 3867K|00:00:15.47 | 656K| | | |
| 22 | TABLE ACCESS FULL | EMS_EVENT | 1 | 3867 | 3950 |00:00:00.02 | 2046 | | | |
| 23 | PARTITION RANGE ALL | | 1 | 3860K| 3863K|00:00:07.73 | 654K| | | |
| 24 | TABLE ACCESS FULL | EMS_EVENT_HISTORY | 338 | 3860K| 3863K|00:00:09.51 | 654K| | | |
-------------------------------------------------------------------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
1 - access("EMS_EVENT_VIEW"."EVENT_ID"="from_subquery_003"."EVENT_ID")
2 - filter(("ROWNO">=:SYS_B_8 AND "ROWNO"<=:SYS_B_9))
3 - filter(ROW_NUMBER() OVER ( ORDER BY INTERNAL_FUNCTION("FIRST_OCCURRENCE_TIME") DESC )<=:SYS_B_9)
4 - filter(:SYS_B_8<=:SYS_B_9)
9 - access("A"."LAST_OCCURRENCE_TIME">TO_DATE(:SYS_B_4,:SYS_B_5) AND "A"."LAST_OCCURRENCE_TIME"<TO_DATE(:SYS_B_6,:SYS_B_7))
10 - filter((LNNVL("A"."LAST_OCCURRENCE_TIME"<TO_DATE(:SYS_B_6,:SYS_B_7)) OR LNNVL("A"."LAST_OCCURRENCE_TIME">TO_DATE(:SYS_B_4,:SYS_B_5))))
11 - access("A"."FIRST_OCCURRENCE_TIME">TO_DATE(:SYS_B_0,:SYS_B_1) AND "A"."FIRST_OCCURRENCE_TIME"<TO_DATE(:SYS_B_2,:SYS_B_3))
12 - filter((("B"."FIRST_OCCURRENCE_TIME">TO_DATE(:SYS_B_0,:SYS_B_1) AND "B"."FIRST_OCCURRENCE_TIME"<TO_DATE(:SYS_B_2,:SYS_B_3)) OR
("B"."LAST_OCCURRENCE_TIME">TO_DATE(:SYS_B_4,:SYS_B_5) AND "B"."LAST_OCCURRENCE_TIME"<TO_DATE(:SYS_B_6,:SYS_B_7))))
13 - access(ROWIDROWID=ROWID)
14 - access(ROWIDROWID=ROWID)
如果你看不清楚SQL，我在这里再贴一下：
SELECT A.ROWNO, EMS_EVENT_VIEW.*
FROM EMS_EVENT_VIEW,
(SELECT *
FROM (SELECT ROW_NUMBER() OVER(ORDER BY first_occurrence_time DESC) AS ROWNO,
EVENT_ID
FROM EMS_EVENT_VIEW
WHERE (first_occurrence_time >
to_date('2012-02-22 00:00:00',
'yyyy-mm-dd hh24:mi:ss') and
first_occurrence_time <
to_date('2012-02-29 09:42:35',
'yyyy-mm-dd hh24:mi:ss'))
))
WHERE ROWNO >= 0
AND ROWNO <= 20) A
WHERE EMS_EVENT_VIEW.EVENT_ID = A.EVENT_ID;
这个SQL其实就是一个分页SQL，利用row_number over 做分页，EMS_EVENT_VIEW是一个视图。这个SQL确实写得很坑爹，它要扫描EMS_EVENT_VIEW两次，其实我们可以改写它，让它扫描一次，而不是自己和自己利用event_id 做自连接。
EMS_EVENT_VIEW的定义就不贴出来了，涉及保密 。它的大概意思就是select * from a union all select * from b; 无where 过滤条件。
因为这个SQL是朋友给我的，我无法连接到他的DB，所以我只有自己做测试了，测试代码如下：
create table a as select * from dba_objects;
create table b as select * from dba_objects;
create view test_view as select * from a
union all select * from b;
create index idx_a on a(created ,last_ddl_time);
create index idx_b on b(created ,last_ddl_time);
BEGIN
DBMS_STATS.GATHER_TABLE_STATS(ownname => 'SCOTT',
tabname => 'B',
estimate_percent => 100,
method_opt => 'for all columns size auto',
no_invalidate => FALSE,
degree => 4,
cascade => TRUE);
END;
/
BEGIN
DBMS_STATS.GATHER_TABLE_STATS(ownname => 'SCOTT',
tabname => 'B',
estimate_percent => 100,
method_opt => 'for all columns size auto',
no_invalidate => FALSE,
degree => 4,
cascade => TRUE);
END;
/
要优化的SQL可以改写成如下代码，只访问一次视图：
select * from
(
select t.*,rownum rn from
(select /*+ INDEX(TEST_VIEW.A idx_a) INDEX(TEST_VIEW.b idx_b) */ *
from test_view
where created > to_date('2010-01-01', 'yyyy-mm-dd') or
LAST_DDL_TIME < to_date('2007-0101', 'yyyy-mm-dd')
order by created desc
) t where rownum<=20
) where rn>=0;
现在来看它的执行计划
SQL> select * from
2 (
3 select t.*,rownum rn from
4 (select /*+ INDEX(TEST_VIEW.A idx_a) INDEX(TEST_VIEW.b idx_b) */ *
5 from test_view
6 where created > to_date('2010-01-01', 'yyyy-mm-dd') or
7 LAST_DDL_TIME < to_date('2007-0101', 'yyyy-mm-dd')
8 order by created desc
9 ) t where rownum<=20
10 ) where rn>=0;
已选择20行。
已用时间: 00: 00: 00.10
执行计划
----------------------------------------------------------
Plan hash value: 1808710389
-------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes |TempSpc| Cost (%CPU)| Time |
-------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 20 | 3800 | | 1898 (2)| 00:00:23 |
|* 1 | VIEW | | 20 | 3800 | | 1898 (2)| 00:00:23 |
|* 2 | COUNT STOPKEY | | | | | | |
| 3 | VIEW | | 70304 | 11M| | 1898 (2)| 00:00:23 |
|* 4 | SORT ORDER BY STOPKEY | | 70304 | 6659K| 17M| 1898 (2)| 00:00:23 |
| 5 | VIEW | TEST_VIEW | 70304 | 6659K| | 329 (5)| 00:00:04 |
| 6 | UNION-ALL PARTITION | | | | | | |
| 7 | TABLE ACCESS BY INDEX ROWID| A | 1650 | 156K| | 238 (3)| 00:00:03 |
|* 8 | INDEX FULL SCAN | IDX_A | 1650 | | | 199 (4)| 00:00:03 |
| 9 | TABLE ACCESS BY INDEX ROWID| B | 1650 | 156K| | 238 (3)| 00:00:03 |
|* 10 | INDEX FULL SCAN | IDX_B | 1650 | | | 199 (4)| 00:00:03 |
-------------------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
1 - filter("RN">=0)
2 - filter(ROWNUM<=20)
4 - filter(ROWNUM<=20)
8 - filter("CREATED">TO_DATE('2010-01-01 00:00:00', 'yyyy-mm-dd hh24:mi:ss') OR
"LAST_DDL_TIME"<TO_DATE('2007-0101','yyyy-mm-dd'))
10 - filter("CREATED">TO_DATE('2010-01-01 00:00:00', 'yyyy-mm-dd hh24:mi:ss') OR
"LAST_DDL_TIME"<TO_DATE('2007-0101','yyyy-mm-dd'))
统计信息
----------------------------------------------------------
8 recursive calls
0 db block gets
566 consistent gets
9 physical reads
0 redo size
2621 bytes sent via SQL*Net to client
411 bytes received via SQL*Net from client
3 SQL*Net roundtrips to/from client
1 sorts (memory)
0 sorts (disk)
20 rows processed
逻辑读566，那么这样改写是不是最优化的呢？显然不是，因为索引IDX_A,IDX_B 都是走的index full scan,会扫描整个索引block，原始的SQL这个索引里面有3863K 条数据，性能肯定是很低的。 所以进一步的 改写SQL 如下： www.2cto.com
select * from
(
select t.*,rownum rn from
(
select * from
(select * from
(
select /*+ index_desc(a) */ *
from a
where created > to_date('2010-01-01', 'yyyy-mm-dd') or
LAST_DDL_TIME < to_date('2007-0101', 'yyyy-mm-dd')
order by created desc
) where rownum<=20
union all
select * from
(
select /*+ index_desc(b) */ *
from b
where created > to_date('2010-01-01', 'yyyy-mm-dd') or
LAST_DDL_TIME < to_date('2007-0101', 'yyyy-mm-dd')
order by created desc
) where rownum<=20
) order by created desc
) t where rownum<=20
) where rn>=0
执行计划和逻辑读如下：
SQL> select * from
2 (
3 select t.*,rownum rn from
4 (
5 select * from
6 (select * from
7 (
8 select /*+ index_desc(a) */ *
9 from a
10 where created > to_date('2010-01-01', 'yyyy-mm-dd') or
11 LAST_DDL_TIME < to_date('2007-0101', 'yyyy-mm-dd')
12 order by created desc
13 ) where rownum<=20
14 union all
15 select * from
16 (
17 select /*+ index_desc(b) */ *
18 from b
19 where created > to_date('2010-01-01', 'yyyy-mm-dd') or
20 LAST_DDL_TIME < to_date('2007-0101', 'yyyy-mm-dd')
21 order by created desc
22 ) where rownum<=20
23 ) order by created desc
24 ) t where rownum<=20
25 ) where rn>=0;
已选择20行。
已用时间: 00: 00: 00.04
执行计划
----------------------------------------------------------
Plan hash value: 3460309830
---------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
---------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 20 | 3800 | 244 (4)| 00:00:03 |
|* 1 | VIEW | | 20 | 3800 | 244 (4)| 00:00:03 |
|* 2 | COUNT STOPKEY | | | | | |
| 3 | VIEW | | 40 | 7080 | 244 (4)| 00:00:03 |
|* 4 | SORT ORDER BY STOPKEY | | 40 | 7080 | 244 (4)| 00:00:03 |
| 5 | VIEW | | 40 | 7080 | 243 (3)| 00:00:03 |
| 6 | UNION-ALL | | | | | |
|* 7 | COUNT STOPKEY | | | | | |
| 8 | VIEW | | 1650 | 285K| 238 (3)| 00:00:03 |
| 9 | TABLE ACCESS BY INDEX ROWID| A | 1650 | 156K| 238 (3)| 00:00:03 |
|* 10 | INDEX FULL SCAN DESCENDING| IDX_A | 1650 | | 199 (4)| 00:00:03 |
|* 11 | COUNT STOPKEY | | | | | |
| 12 | VIEW | | 20 | 3540 | 5 (0)| 00:00:01 |
| 13 | TABLE ACCESS BY INDEX ROWID| B | 20 | 1940 | 5 (0)| 00:00:01 |
|* 14 | INDEX FULL SCAN DESCENDING| IDX_B | 1650 | | 4 (0)| 00:00:01 |
---------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
1 - filter("RN">=0)
2 - filter(ROWNUM<=20)
4 - filter(ROWNUM<=20)
7 - filter(ROWNUM<=20)
10 - filter("CREATED">TO_DATE('2010-01-01 00:00:00', 'yyyy-mm-dd hh24:mi:ss') OR
"LAST_DDL_TIME"<TO_DATE('2007-0101','yyyy-mm-dd'))
11 - filter(ROWNUM<=20)
14 - filter("CREATED">TO_DATE('2010-01-01 00:00:00', 'yyyy-mm-dd hh24:mi:ss') OR
"LAST_DDL_TIME"<TO_DATE('2007-0101','yyyy-mm-dd'))
统计信息
----------------------------------------------------------
1 recursive calls
0 db block gets
10 consistent gets
0 physical reads
0 redo size
2457 bytes sent via SQL*Net to client
411 bytes received via SQL*Net from client
3 SQL*Net roundtrips to/from client
1 sorts (memory)
0 sorts (disk)
20 rows processed
逻辑读整整下降了60倍。
现在根据这个案例来谈谈SQL分页的优化思路，SQL分页通常要进行排序，比如select xxxx from t where 条件order by ......
优化分页SQL可以重点关注order by 这个条件，写SQL的时候要让ORACLE 对order by 列 上的索引进行有序的扫描，然后根据stopkey 停止，也就是不要把索引的block全都给扫描了，应该扫描一部分block就停止
摘自 落落的专栏 专注SQL调优 性能调优
SQL和执行计划如下：
SQL> SELECT A.ROWNO,EMS_EVENT_VIEW.* FROM EMS_EVENT_VIEW,
2 (SELECT * FROM (SELECT ROW_NUMBER() OVER(ORDER BY first_occurrence_time DESC) AS ROWNO,EVENT_ID
3 FROM EMS_EVENT_VIEW
WHERE (first_occurrence_time>to_date('2012-02-22 00:00:00','yyyy-mm-dd hh24:mi:ss')
4 5 and first_occurrence_time<to_date('2012-02-29 09:42:35','yyyy-mm-dd hh24:mi:ss'))
or (last_occurrence_time>to_date('2012-02-22 00:00:00','yyyy-mm-dd hh24:mi:ss')
and last_occurrence_time<to_date('2012-02-29 09:42:35','yyyy-mm-dd hh24:mi:ss')))
6 7 8 WHERE ROWNO>=0 AND ROWNO<=20) A
9 WHERE EMS_EVENT_VIEW.EVENT_ID=A.EVENT_ID;
Plan hash value: 2052413575
-------------------------------------------------------------------------------------------------------------------------------------------------------
PLAN_TABLE_OUTPUT
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | OMem | 1Mem | Used-Mem |
-------------------------------------------------------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 1 | | 20 |00:00:53.37 | 757K| | | |
|* 1 | HASH JOIN | | 1 | 81G| 20 |00:00:53.37 | 757K| 1179K| 1179K| 6598K (0)|
|* 2 | VIEW | | 1 | 2104K| 20 |00:00:30.83 | 101K| | | |
|* 3 | WINDOW SORT PUSHED RANK | | 1 | 2104K| 21 |00:00:30.83 | 101K| 4096 | 4096 | 4096 (0)|
|* 4 | FILTER | | 1 | | 1255K|00:00:30.10 | 101K| | | |
| 5 | VIEW | EMS_EVENT_VIEW | 1 | 2104K| 1255K|00:00:28.85 | 101K| | | |
| 6 | UNION-ALL | | 1 | | 1255K|00:00:28.85 | 101K| | | |
| 7 | CONCATENATION | | 1 | | 0 |00:00:00.01 | 335 | | | |
| 8 | TABLE ACCESS BY INDEX ROWID| EMS_EVENT | 1 | 1 | 0 |00:00:00.01 | 63 | | | |
|* 9 | INDEX RANGE SCAN | LAST_OCCURRENCE_TIME_INDEX | 1 | 1 | 0 |00:00:00.01 | 63 | | | |
|* 10 | TABLE ACCESS BY INDEX ROWID| EMS_EVENT | 1 | 1 | 0 |00:00:00.01 | 272 | | | |
|* 11 | INDEX RANGE SCAN | FIRST_OCCURRENCE_INDEX | 1 | 1 | 0 |00:00:00.01 | 272 | | | |
|* 12 | VIEW | index_join_006 | 1 | 2104K| 1255K|00:00:28.84 | 100K| | | |
|* 13 | HASH JOIN | | 1 | | 3863K|00:00:26.50 | 100K| 195M| 9M| 248M (0)|
|* 14 | HASH JOIN | | 1 | | 3863K|00:00:13.87 | 63020 | 160M| 10M| 214M (0)|
| 15 | PARTITION RANGE ALL | | 1 | 2104K| 3863K|00:00:00.01 | 31419 | | | |
| 16 | INDEX FAST FULL SCAN | IDX_FIRSTTIME_201202 | 338 | 2104K| 3863K|00:00:00.07 | 31419 | | | |
| 17 | PARTITION RANGE ALL | | 1 | 2104K| 3863K|00:00:00.01 | 31601 | | | |
| 18 | INDEX FAST FULL SCAN | IDX_LASTOCCURRENCE_201202 | 338 | 2104K| 3863K|00:00:00.06 | 31601 | | | |
| 19 | INDEX FAST FULL SCAN | PK_EMS_EVENT_HISTORY_201202 | 1 | 2104K| 3863K|00:00:00.01 | 37894 | | | |
| 20 | VIEW | EMS_EVENT_VIEW | 1 | 3864K| 3867K|00:00:19.34 | 656K| | | |
| 21 | UNION-ALL | | 1 | | 3867K|00:00:15.47 | 656K| | | |
| 22 | TABLE ACCESS FULL | EMS_EVENT | 1 | 3867 | 3950 |00:00:00.02 | 2046 | | | |
| 23 | PARTITION RANGE ALL | | 1 | 3860K| 3863K|00:00:07.73 | 654K| | | |
| 24 | TABLE ACCESS FULL | EMS_EVENT_HISTORY | 338 | 3860K| 3863K|00:00:09.51 | 654K| | | |
-------------------------------------------------------------------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
1 - access("EMS_EVENT_VIEW"."EVENT_ID"="from_subquery_003"."EVENT_ID")
2 - filter(("ROWNO">=:SYS_B_8 AND "ROWNO"<=:SYS_B_9))
3 - filter(ROW_NUMBER() OVER ( ORDER BY INTERNAL_FUNCTION("FIRST_OCCURRENCE_TIME") DESC )<=:SYS_B_9)
4 - filter(:SYS_B_8<=:SYS_B_9)
9 - access("A"."LAST_OCCURRENCE_TIME">TO_DATE(:SYS_B_4,:SYS_B_5) AND "A"."LAST_OCCURRENCE_TIME"<TO_DATE(:SYS_B_6,:SYS_B_7))
10 - filter((LNNVL("A"."LAST_OCCURRENCE_TIME"<TO_DATE(:SYS_B_6,:SYS_B_7)) OR LNNVL("A"."LAST_OCCURRENCE_TIME">TO_DATE(:SYS_B_4,:SYS_B_5))))
11 - access("A"."FIRST_OCCURRENCE_TIME">TO_DATE(:SYS_B_0,:SYS_B_1) AND "A"."FIRST_OCCURRENCE_TIME"<TO_DATE(:SYS_B_2,:SYS_B_3))
12 - filter((("B"."FIRST_OCCURRENCE_TIME">TO_DATE(:SYS_B_0,:SYS_B_1) AND "B"."FIRST_OCCURRENCE_TIME"<TO_DATE(:SYS_B_2,:SYS_B_3)) OR
("B"."LAST_OCCURRENCE_TIME">TO_DATE(:SYS_B_4,:SYS_B_5) AND "B"."LAST_OCCURRENCE_TIME"<TO_DATE(:SYS_B_6,:SYS_B_7))))
13 - access(ROWIDROWID=ROWID)
14 - access(ROWIDROWID=ROWID)
如果你看不清楚SQL，我在这里再贴一下：
SELECT A.ROWNO, EMS_EVENT_VIEW.*
FROM EMS_EVENT_VIEW,
(SELECT *
FROM (SELECT ROW_NUMBER() OVER(ORDER BY first_occurrence_time DESC) AS ROWNO,
EVENT_ID
FROM EMS_EVENT_VIEW
WHERE (first_occurrence_time >
to_date('2012-02-22 00:00:00',
'yyyy-mm-dd hh24:mi:ss') and
first_occurrence_time <
to_date('2012-02-29 09:42:35',
'yyyy-mm-dd hh24:mi:ss'))
))
WHERE ROWNO >= 0
AND ROWNO <= 20) A
WHERE EMS_EVENT_VIEW.EVENT_ID = A.EVENT_ID;
这个SQL其实就是一个分页SQL，利用row_number over 做分页，EMS_EVENT_VIEW是一个视图。这个SQL确实写得很坑爹，它要扫描EMS_EVENT_VIEW两次，其实我们可以改写它，让它扫描一次，而不是自己和自己利用event_id 做自连接。
EMS_EVENT_VIEW的定义就不贴出来了，涉及保密 。它的大概意思就是select * from a union all select * from b; 无where 过滤条件。
因为这个SQL是朋友给我的，我无法连接到他的DB，所以我只有自己做测试了，测试代码如下：
create table a as select * from dba_objects;
create table b as select * from dba_objects;
create view test_view as select * from a
union all select * from b;
create index idx_a on a(created ,last_ddl_time);
create index idx_b on b(created ,last_ddl_time);
BEGIN
DBMS_STATS.GATHER_TABLE_STATS(ownname => 'SCOTT',
tabname => 'B',
estimate_percent => 100,
method_opt => 'for all columns size auto',
no_invalidate => FALSE,
degree => 4,
cascade => TRUE);
END;
/
BEGIN
DBMS_STATS.GATHER_TABLE_STATS(ownname => 'SCOTT',
tabname => 'B',
estimate_percent => 100,
method_opt => 'for all columns size auto',
no_invalidate => FALSE,
degree => 4,
cascade => TRUE);
END;
/
要优化的SQL可以改写成如下代码，只访问一次视图：
select * from
(
select t.*,rownum rn from
(select /*+ INDEX(TEST_VIEW.A idx_a) INDEX(TEST_VIEW.b idx_b) */ *
from test_view
where created > to_date('2010-01-01', 'yyyy-mm-dd') or
LAST_DDL_TIME < to_date('2007-0101', 'yyyy-mm-dd')
order by created desc
) t where rownum<=20
) where rn>=0;
现在来看它的执行计划
SQL> select * from
2 (
3 select t.*,rownum rn from
4 (select /*+ INDEX(TEST_VIEW.A idx_a) INDEX(TEST_VIEW.b idx_b) */ *
5 from test_view
6 where created > to_date('2010-01-01', 'yyyy-mm-dd') or
7 LAST_DDL_TIME < to_date('2007-0101', 'yyyy-mm-dd')
8 order by created desc
9 ) t where rownum<=20
10 ) where rn>=0;
已选择20行。
已用时间: 00: 00: 00.10
执行计划
----------------------------------------------------------
Plan hash value: 1808710389
-------------------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes |TempSpc| Cost (%CPU)| Time |
-------------------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 20 | 3800 | | 1898 (2)| 00:00:23 |
|* 1 | VIEW | | 20 | 3800 | | 1898 (2)| 00:00:23 |
|* 2 | COUNT STOPKEY | | | | | | |
| 3 | VIEW | | 70304 | 11M| | 1898 (2)| 00:00:23 |
|* 4 | SORT ORDER BY STOPKEY | | 70304 | 6659K| 17M| 1898 (2)| 00:00:23 |
| 5 | VIEW | TEST_VIEW | 70304 | 6659K| | 329 (5)| 00:00:04 |
| 6 | UNION-ALL PARTITION | | | | | | |
| 7 | TABLE ACCESS BY INDEX ROWID| A | 1650 | 156K| | 238 (3)| 00:00:03 |
|* 8 | INDEX FULL SCAN | IDX_A | 1650 | | | 199 (4)| 00:00:03 |
| 9 | TABLE ACCESS BY INDEX ROWID| B | 1650 | 156K| | 238 (3)| 00:00:03 |
|* 10 | INDEX FULL SCAN | IDX_B | 1650 | | | 199 (4)| 00:00:03 |
-------------------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
1 - filter("RN">=0)
2 - filter(ROWNUM<=20)
4 - filter(ROWNUM<=20)
8 - filter("CREATED">TO_DATE('2010-01-01 00:00:00', 'yyyy-mm-dd hh24:mi:ss') OR
"LAST_DDL_TIME"<TO_DATE('2007-0101','yyyy-mm-dd'))
10 - filter("CREATED">TO_DATE('2010-01-01 00:00:00', 'yyyy-mm-dd hh24:mi:ss') OR
"LAST_DDL_TIME"<TO_DATE('2007-0101','yyyy-mm-dd'))
统计信息
----------------------------------------------------------
8 recursive calls
0 db block gets
566 consistent gets
9 physical reads
0 redo size
2621 bytes sent via SQL*Net to client
411 bytes received via SQL*Net from client
3 SQL*Net roundtrips to/from client
1 sorts (memory)
0 sorts (disk)
20 rows processed
逻辑读566，那么这样改写是不是最优化的呢？显然不是，因为索引IDX_A,IDX_B 都是走的index full scan,会扫描整个索引block，原始的SQL这个索引里面有3863K 条数据，性能肯定是很低的。 所以进一步的 改写SQL 如下： www.2cto.com
select * from
(
select t.*,rownum rn from
(
select * from
(select * from
(
select /*+ index_desc(a) */ *
from a
where created > to_date('2010-01-01', 'yyyy-mm-dd') or
LAST_DDL_TIME < to_date('2007-0101', 'yyyy-mm-dd')
order by created desc
) where rownum<=20
union all
select * from
(
select /*+ index_desc(b) */ *
from b
where created > to_date('2010-01-01', 'yyyy-mm-dd') or
LAST_DDL_TIME < to_date('2007-0101', 'yyyy-mm-dd')
order by created desc
) where rownum<=20
) order by created desc
) t where rownum<=20
) where rn>=0
执行计划和逻辑读如下：
SQL> select * from
2 (
3 select t.*,rownum rn from
4 (
5 select * from
6 (select * from
7 (
8 select /*+ index_desc(a) */ *
9 from a
10 where created > to_date('2010-01-01', 'yyyy-mm-dd') or
11 LAST_DDL_TIME < to_date('2007-0101', 'yyyy-mm-dd')
12 order by created desc
13 ) where rownum<=20
14 union all
15 select * from
16 (
17 select /*+ index_desc(b) */ *
18 from b
19 where created > to_date('2010-01-01', 'yyyy-mm-dd') or
20 LAST_DDL_TIME < to_date('2007-0101', 'yyyy-mm-dd')
21 order by created desc
22 ) where rownum<=20
23 ) order by created desc
24 ) t where rownum<=20
25 ) where rn>=0;
已选择20行。
已用时间: 00: 00: 00.04
执行计划
----------------------------------------------------------
Plan hash value: 3460309830
---------------------------------------------------------------------------------------------
| Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time |
---------------------------------------------------------------------------------------------
| 0 | SELECT STATEMENT | | 20 | 3800 | 244 (4)| 00:00:03 |
|* 1 | VIEW | | 20 | 3800 | 244 (4)| 00:00:03 |
|* 2 | COUNT STOPKEY | | | | | |
| 3 | VIEW | | 40 | 7080 | 244 (4)| 00:00:03 |
|* 4 | SORT ORDER BY STOPKEY | | 40 | 7080 | 244 (4)| 00:00:03 |
| 5 | VIEW | | 40 | 7080 | 243 (3)| 00:00:03 |
| 6 | UNION-ALL | | | | | |
|* 7 | COUNT STOPKEY | | | | | |
| 8 | VIEW | | 1650 | 285K| 238 (3)| 00:00:03 |
| 9 | TABLE ACCESS BY INDEX ROWID| A | 1650 | 156K| 238 (3)| 00:00:03 |
|* 10 | INDEX FULL SCAN DESCENDING| IDX_A | 1650 | | 199 (4)| 00:00:03 |
|* 11 | COUNT STOPKEY | | | | | |
| 12 | VIEW | | 20 | 3540 | 5 (0)| 00:00:01 |
| 13 | TABLE ACCESS BY INDEX ROWID| B | 20 | 1940 | 5 (0)| 00:00:01 |
|* 14 | INDEX FULL SCAN DESCENDING| IDX_B | 1650 | | 4 (0)| 00:00:01 |
---------------------------------------------------------------------------------------------
Predicate Information (identified by operation id):
---------------------------------------------------
1 - filter("RN">=0)
2 - filter(ROWNUM<=20)
4 - filter(ROWNUM<=20)
7 - filter(ROWNUM<=20)
10 - filter("CREATED">TO_DATE('2010-01-01 00:00:00', 'yyyy-mm-dd hh24:mi:ss') OR
"LAST_DDL_TIME"<TO_DATE('2007-0101','yyyy-mm-dd'))
11 - filter(ROWNUM<=20)
14 - filter("CREATED">TO_DATE('2010-01-01 00:00:00', 'yyyy-mm-dd hh24:mi:ss') OR
"LAST_DDL_TIME"<TO_DATE('2007-0101','yyyy-mm-dd'))
统计信息
----------------------------------------------------------
1 recursive calls
0 db block gets
10 consistent gets
0 physical reads
0 redo size
2457 bytes sent via SQL*Net to client
411 bytes received via SQL*Net from client
3 SQL*Net roundtrips to/from client
1 sorts (memory)
0 sorts (disk)
20 rows processed
逻辑读整整下降了60倍。
现在根据这个案例来谈谈SQL分页的优化思路，SQL分页通常要进行排序，比如select xxxx from t where 条件order by ......
优化分页SQL可以重点关注order by 这个条件，写SQL的时候要让ORACLE 对order by 列 上的索引进行有序的扫描，然后根据stopkey 停止，也就是不要把索引的block全都给扫描了，应该扫描一部分block就停止
摘自 落落的专栏 专注SQL调优 性能调优
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