Oracle学习笔记（五）

如何查询硬解析问题：

--捕获出需要使用绑定变量的SQL

drop table t_bind_sql purge;

create table t_bind_sql as select sql_text,module from v$sqlarea;
alter table t_bind_sql add sql_text_wo_constants varchar2(1000);
create or replace function
remove_constants( p_query in varchar2 ) return varchar2
as
    l_query long;
    l_char  varchar2(10);
    l_in_quotes boolean default FALSE;
begin
    for i in 1 .. length( p_query )
    loop
        l_char := substr(p_query,i,1);
        if ( l_char = '''' and l_in_quotes )
        then
            l_in_quotes := FALSE;
        elsif ( l_char = '''' and NOT l_in_quotes )
        then
            l_in_quotes := TRUE;
            l_query := l_query || '''#';
        end if;
        if ( NOT l_in_quotes ) then
            l_query := l_query || l_char;
        end if;
    end loop;
    l_query := translate( l_query, '0123456789', '@@@@@@@@@@' );
    for i in 0 .. 8 loop
        l_query := replace( l_query, lpad('@',10-i,'@'), '@' );
        l_query := replace( l_query, lpad(' ',10-i,' '), ' ' );
    end loop;
    return upper(l_query);
end;
/
update t_bind_sql set sql_text_wo_constants = remove_constants(sql_text);
commit;

---执行完上述动作后，以下SQL语句可以完成未绑定变量语句的统计
set linesize 266
col  sql_text_wo_constants format a30
col  module format  a30
col  CNT format  999999

select sql_text_wo_constants, module,count(*) CNT
  from t_bind_sql
 group by sql_text_wo_constants,module
having count(*) > 100
 order by 3 desc;

--注：可以考虑试验如下脚本
drop table t purge;
create table t(x int);

select * from v$mystat where rownum=1;
begin
    for i in 1 .. 100000
    loop
        execute immediate
        'insert into t values ( '||i||')';
    end loop;
    commit;
end;
/

附：贴出部分执行结果
------------------------------------------------------------------------------------------------------
SQL> ---执行完上述动作后，以下SQL语句可以完成未绑定变量语句的统计
SQL> set linesize 266
SQL> col  sql_text_wo_constants format a30
SQL> col  module format  a30
SQL> col  CNT format  999999
SQL> select sql_text_wo_constants, module,count(*) CNT
  2    from t_bind_sql
  3   group by sql_text_wo_constants,module
  4  having count(*) > 100
  5   order by 3 desc;

SQL_TEXT_WO_CONSTANTS          MODULE                             CNT
------------------------------ ------------------------------ -------
INSERT INTO T VALUES ( @)      SQL*Plus                          7366

　　绑定变量的不适合场景：

---1.构建T表，数据，及主键
VARIABLE id NUMBER
COLUMN sql_id NEW_VALUE sql_id
DROP TABLE t;
CREATE TABLE t
AS
SELECT rownum AS id, rpad('*',100,'*') AS pad
FROM dual
CONNECT BY level <= 1000;
ALTER TABLE t ADD CONSTRAINT t_pk PRIMARY KEY (id);
---2.收集统计信息
BEGIN
  dbms_stats.gather_table_stats(
    ownname          => user,
    tabname          => 't',
    estimate_percent => 100,
    method_opt       => 'for all columns size skewonly'
  );
END;
/
---3.查询T表当前的分布情况
SELECT count(id), count(DISTINCT id), min(id), max(id) FROM t;
---4.发现当前情况下，可以区分出数据分布情况而正确使用执行计划
set linesize 1000
set autotrace traceonly explain
SELECT count(pad) FROM t WHERE id < 990;
SELECT count(pad) FROM t WHERE id < 10;

---5.现在将id的值该为变量实验一下绑定变量的SQL是否能使用直方图
--首先代入990，发现执行计划是走全表扫描，很正确
EXECUTE :id := 990;
SELECT count(pad) FROM t WHERE id < :id;
---6.接着代入10，发现仍然走全表扫描
EXECUTE :id := 10;
SELECT count(pad) FROM t WHERE id < :id;

---7.把共享池清空，很重要的一步，保证硬解析
ALTER SYSTEM FLUSH SHARED_POOL;
---8.代入10,发现可以使用直方图，执行计划为索引读，很正常
EXECUTE :id := 10;
SELECT count(pad) FROM t WHERE id < :id;
---9.代入990后，发现异常，仍然走索引读，这个时候由于返回大部分数据，应该全表扫描才对。
EXECUTE :id := 990;
SELECT count(pad) FROM t WHERE id < :id;
---明白了，这个就是传说中的绑定变量窥视！

附：贴出部分执行结果
------------------------------------------------------------------------------------------------------
SQL> SELECT count(pad) FROM t WHERE id < 990;
---------------------------------------------------------------------------
|   0 | SELECT STATEMENT   |      |     1 |   105 |     7   (0)| 00:00:01 |
|   1 |  SORT AGGREGATE    |      |     1 |   105 |            |          |
|*  2 |   TABLE ACCESS FULL| T    |   990 |   101K|     7   (0)| 00:00:01 |
---------------------------------------------------------------------------
SQL> SELECT count(pad) FROM t WHERE id < 10;
-------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT             |      |     1 |   105 |     3   (0)| 00:00:01 |
|   1 |  SORT AGGREGATE              |      |     1 |   105 |            |          |
|   2 |   TABLE ACCESS BY INDEX ROWID| T    |     9 |   945 |     3   (0)| 00:00:01 |
|*  3 |    INDEX RANGE SCAN          | T_PK |     9 |       |     2   (0)| 00:00:01 |
-------------------------------------------------------------------------------------

SQL> EXECUTE :id := 990;
PL/SQL 过程已成功完成。
SQL> SELECT count(pad) FROM t WHERE id < :id;
-------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT             |      |     1 |   105 |     3   (0)| 00:00:01 |
|   1 |  SORT AGGREGATE              |      |     1 |   105 |            |          |
|   2 |   TABLE ACCESS BY INDEX ROWID| T    |    50 |  5250 |     3   (0)| 00:00:01 |
|*  3 |    INDEX RANGE SCAN          | T_PK |     9 |       |     2   (0)| 00:00:01 |
-------------------------------------------------------------------------------------
SQL> EXECUTE :id := 10;
SQL> SELECT count(pad) FROM t WHERE id < :id;
-------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT             |      |     1 |   105 |     3   (0)| 00:00:01 |
|   1 |  SORT AGGREGATE              |      |     1 |   105 |            |          |
|   2 |   TABLE ACCESS BY INDEX ROWID| T    |    50 |  5250 |     3   (0)| 00:00:01 |
|*  3 |    INDEX RANGE SCAN          | T_PK |     9 |       |     2   (0)| 00:00:01 |
-------------------------------------------------------------------------------------

　　

sql的逻辑读变零：

drop table t purge;
create table t as select * from dba_objects;
insert into t  select * from t;
commit;
set autotrace  on
set timing on
set linesize 1000
select /*+ result_cache */ count(*) from t;

---接下来再次执行(居然发现逻辑读为0）：
set autotrace on
select /*+ result_cache */ count(*) from t;

附：贴出部分执行结果
------------------------------------------------------------------------------------------------------
SQL> ---接下来再次执行(居然发现逻辑读为0）：
SQL> set autotrace on
SQL> select /*+ result_cache */ count(*) from t;
  COUNT(*)
----------
    145762
已用时间:  00: 00: 00.01
执行计划
------------------------------------------------------------------------------------------
| Id  | Operation           | Name                       | Rows  | Cost (%CPU)| Time     |
------------------------------------------------------------------------------------------
|   0 | SELECT STATEMENT    |                            |     1 |   589   (1)| 00:00:08 |
|   1 |  RESULT CACHE       | d827qx1jmwjc86yqynrp1kvpny |       |            |          |
|   2 |   SORT AGGREGATE    |                            |     1 |            |          |
|   3 |    TABLE ACCESS FULL| T                          |   277K|   589   (1)| 00:00:08 |
------------------------------------------------------------------------------------------
统计信息
----------------------------------------------------------
          0  recursive calls
          0  db block gets
          0  consistent gets
          0  physical reads
          0  redo size
        425  bytes sent via SQL*Net to client
        416  bytes received via SQL*Net from client
          2  SQL*Net roundtrips to/from client
          0  sorts (memory)
          0  sorts (disk)
          1  rows processed

函数的逻辑读变成零：

drop table t;
CREATE TABLE T AS SELECT * FROM DBA_OBJECTS;

CREATE OR REPLACE FUNCTION F_NO_RESULT_CACHE RETURN NUMBER AS
V_RETURN NUMBER;
BEGIN
SELECT COUNT(*) INTO V_RETURN FROM T;
RETURN V_RETURN;
END;
/

set autotrace on statistics

SELECT F_NO_RESULT_CACHE FROM DUAL;
--看调用F_NO_RESULT_CACHE执行第2次后的结果
SELECT F_NO_RESULT_CACHE FROM DUAL;

CREATE OR REPLACE FUNCTION F_RESULT_CACHE RETURN NUMBER RESULT_CACHE AS
 V_RETURN NUMBER;
 BEGIN
 SELECT COUNT(*) INTO V_RETURN FROM T;
 RETURN V_RETURN;
 END;
/

SELECT F_RESULT_CACHE FROM DUAL;
--看调用F_RESULT_CACHE执行第2次后的结果
SELECT F_RESULT_CACHE FROM DUAL;

--以下细节是探讨关于如何保证在数据变化后，结果的正确性
SELECT COUNT(*) FROM T;
SELECT F_RESULT_CACHE(1) FROM DUAL;
DELETE T WHERE ROWNUM = 1;
SELECT COUNT(*) FROM T;
SELECT F_RESULT_CACHE(1) FROM DUAL;
COMMIT;
SELECT F_RESULT_CACHE(1) FROM DUAL;

EXEC DBMS_RESULT_CACHE.FLUSH
CREATE OR REPLACE FUNCTION F_RESULT_CACHE(P_IN NUMBER)
 RETURN NUMBER RESULT_CACHE RELIES_ON (T) AS
 V_RETURN NUMBER;
 BEGIN
 SELECT COUNT(*) INTO V_RETURN FROM T;
 RETURN V_RETURN;
 END;
/

SELECT COUNT(*) FROM T;
SELECT F_RESULT_CACHE(1) FROM DUAL;
SELECT F_RESULT_CACHE(1) FROM DUAL;
DELETE T WHERE ROWNUM = 1;
SELECT COUNT(*) FROM T;
SELECT F_RESULT_CACHE(1) FROM DUAL;

---添加了RELIES_ON语句后，Oracle会根据依赖对象自动INVALIDATE结果集，从而保证RESULT CACHE的正确性。

 附：贴出部分执行结果
------------------------------------------------------------------------------------------------------
SQL> --看调用F_NO_RESULT_CACHE执行第2次后的结果
SQL> SELECT F_NO_RESULT_CACHE FROM DUAL;

F_NO_RESULT_CACHE
-----------------
            72883
统计信息
---------------------------------------------------
          1  recursive calls
          0  db block gets
       1043  consistent gets
          0  physical reads
          0  redo size
        434  bytes sent via SQL*Net to client
        415  bytes received via SQL*Net from client
          2  SQL*Net roundtrips to/from client
          0  sorts (memory)
          0  sorts (disk)
          1  rows processed

SQL> --看调用F_RESULT_CACHE执行第2次后的结果
SQL> SELECT F_RESULT_CACHE FROM DUAL;

F_RESULT_CACHE
--------------
         72883
统计信息
---------------------------------------------------
          0  recursive calls
          0  db block gets
          0  consistent gets
          0  physical reads
          0  redo size
        431  bytes sent via SQL*Net to client
        415  bytes received via SQL*Net from client
          2  SQL*Net roundtrips to/from client
          0  sorts (memory)
          0  sorts (disk)
          1  rows processed          

keep让sql跑的更快：

--前提：必须保证db_keep_cache_size值不为0，所以首先有如下操作：
--设置100M这么大。
alter system set db_keep_cache_size=100M;
drop table t;
create table t as select * from dba_objects;
create index idx_object_id on t(object_id);

--未执行KEEP命令，通过如下查询出BUFFER_POOL列值为DEFAULT，表示未KEEP。

select BUFFER_POOL from user_tables where  TABLE_NAME='T';
select BUFFER_POOL from user_indexes where INDEX_NAME='IDX_OBJECT_ID';

alter index idx_object_id storage(buffer_pool keep);
--以下将索引全部读进内存
select /*+index(t,idx_object_id)*/ count(*) from t where object_id is not null;　
--以下将数据全部读进内存
alter table t storage(buffer_pool keep);
select /*+full(t)*/ count(*) from  t;

--执行KEEP操作后，通过如下查询出BUFFER_POOL列值为KEEP,表示已经KEEP成功了

select BUFFER_POOL from user_tables where  TABLE_NAME='T';
select BUFFER_POOL from user_indexes where INDEX_NAME='IDX_OBJECT_ID';

附：贴出部分执行结果
------------------------------------------------------------------------------------------------------

--未执行KEEP命令，通过如下查询出BUFFER_POOL列值为DEFAULT，表示未KEEP。
select BUFFER_POOL from user_tables where  TABLE_NAME='T';
BUFFER_POOL
-------------------
   DEFAULT

select BUFFER_POOL from user_indexes where INDEX_NAME='IDX_OBJECT_ID';

BUFFER_POOL
-------------------
  DEFAULT

--执行KEEP操作后，通过如下查询出BUFFER_POOL列值为KEEP,表示已经KEEP成功了
select BUFFER_POOL from user_tables where  TABLE_NAME='T';

BUFFER_POOL
-------------------
   KEEP

select BUFFER_POOL from user_indexes where INDEX_NAME='IDX_OBJECT_ID';

BUFFER_POOL
-------------------
   KEEP

查看系统各维度规律：

select s.snap_date,
       decode(s.redosize, null, '--shutdown or end--', s.currtime) "TIME",
       to_char(round(s.seconds/60,2)) "elapse(min)",
       round(t.db_time / 1000000 / 60, 2) "DB time(min)",
       s.redosize redo,
       round(s.redosize / s.seconds, 2) "redo/s",
       s.logicalreads logical,
       round(s.logicalreads / s.seconds, 2) "logical/s",
       physicalreads physical,
       round(s.physicalreads / s.seconds, 2) "phy/s",
       s.executes execs,
       round(s.executes / s.seconds, 2) "execs/s",
       s.parse,
       round(s.parse / s.seconds, 2) "parse/s",
       s.hardparse,
       round(s.hardparse / s.seconds, 2) "hardparse/s",
       s.transactions trans,
       round(s.transactions / s.seconds, 2) "trans/s"
  from (select curr_redo - last_redo redosize,
               curr_logicalreads - last_logicalreads logicalreads,
               curr_physicalreads - last_physicalreads physicalreads,
               curr_executes - last_executes executes,
               curr_parse - last_parse parse,
               curr_hardparse - last_hardparse hardparse,
               curr_transactions - last_transactions transactions,
               round(((currtime + 0) - (lasttime + 0)) * 3600 * 24, 0) seconds,
               to_char(currtime, 'yy/mm/dd') snap_date,
               to_char(currtime, 'hh24:mi') currtime,
               currsnap_id endsnap_id,
               to_char(startup_time, 'yyyy-mm-dd hh24:mi:ss') startup_time
          from (select a.redo last_redo,
                       a.logicalreads last_logicalreads,
                       a.physicalreads last_physicalreads,
                       a.executes last_executes,
                       a.parse last_parse,
                       a.hardparse last_hardparse,
                       a.transactions last_transactions,
                       lead(a.redo, 1, null) over(partition by b.startup_time order by b.end_interval_time) curr_redo,
                       lead(a.logicalreads, 1, null) over(partition by b.startup_time order by b.end_interval_time) curr_logicalreads,
                       lead(a.physicalreads, 1, null) over(partition by b.startup_time order by b.end_interval_time) curr_physicalreads,
                       lead(a.executes, 1, null) over(partition by b.startup_time order by b.end_interval_time) curr_executes,
                       lead(a.parse, 1, null) over(partition by b.startup_time order by b.end_interval_time) curr_parse,
                       lead(a.hardparse, 1, null) over(partition by b.startup_time order by b.end_interval_time) curr_hardparse,
                       lead(a.transactions, 1, null) over(partition by b.startup_time order by b.end_interval_time) curr_transactions,
                       b.end_interval_time lasttime,
                       lead(b.end_interval_time, 1, null) over(partition by b.startup_time order by b.end_interval_time) currtime,
                       lead(b.snap_id, 1, null) over(partition by b.startup_time order by b.end_interval_time) currsnap_id,
                       b.startup_time
                  from (select snap_id,
                               dbid,
                               instance_number,
                               sum(decode(stat_name, 'redo size', value, 0)) redo,
                               sum(decode(stat_name,
                                          'session logical reads',
                                          value,
                                          0)) logicalreads,
                               sum(decode(stat_name,
                                          'physical reads',
                                          value,
                                          0)) physicalreads,
                               sum(decode(stat_name, 'execute count', value, 0)) executes,
                               sum(decode(stat_name,
                                          'parse count (total)',
                                          value,
                                          0)) parse,
                               sum(decode(stat_name,
                                          'parse count (hard)',
                                          value,
                                          0)) hardparse,
                               sum(decode(stat_name,
                                          'user rollbacks',
                                          value,
                                          'user commits',
                                          value,
                                          0)) transactions
                          from dba_hist_sysstat
                         where stat_name in
                               ('redo size',
                                'session logical reads',
                                'physical reads',
                                'execute count',
                                'user rollbacks',
                                'user commits',
                                'parse count (hard)',
                                'parse count (total)')
                         group by snap_id, dbid, instance_number) a,
                       dba_hist_snapshot b
                 where a.snap_id = b.snap_id
                   and a.dbid = b.dbid
                   and a.instance_number = b.instance_number
                 order by end_interval_time)) s,
       (select lead(a.value, 1, null) over(partition by b.startup_time order by b.end_interval_time) - a.value db_time,
               lead(b.snap_id, 1, null) over(partition by b.startup_time order by b.end_interval_time) endsnap_id
          from dba_hist_sys_time_model a, dba_hist_snapshot b
         where a.snap_id = b.snap_id
           and a.dbid = b.dbid
           and a.instance_number = b.instance_number
           and a.stat_name = 'DB time') t
 where s.endsnap_id = t.endsnap_id
 order by  s.snap_date ,time desc;

　　找到提交过频繁的语句：

--检查是否有过分提交的语句(关键是得到sid就好办了，代入V$SESSION就可知道是什么进程，接下来还可以知道V$SQL)
set linesize 1000
column sid             format 99999
column program         format a20
column machine         format a20
column logon_time      format date
column wait_class      format a10
column event           format a32
column sql_id          format 9999
column prev_sql_id     format 9999
column WAIT_TIME       format 9999
column SECONDS_IN_WAIT format 9999
--提交次数最多的SESSION

 select t1.sid, t1.value, t2.name
   from v$sesstat t1, v$statname t2
  where t2.name like '%user commits%'
    and t1.STATISTIC# = t2.STATISTIC#
    and value >= 10000
  order by value desc;

--取得SID既可以代入到V$SESSION 和V$SQL中去分析
 --得出SQL_ID
  select t.SID,
         t.PROGRAM,
     t.EVENT,
         t.LOGON_TIME,
         t.WAIT_TIME,
         t.SECONDS_IN_WAIT,
         t.SQL_ID,
         t.PREV_SQL_ID
   from v$session t
  where sid in(194) ;  

 --根据sql_id或prev_sql_id代入得到SQL
  select t.sql_id,
         t.sql_text,
         t.EXECUTIONS,
         t.FIRST_LOAD_TIME,
         t.LAST_LOAD_TIME
  from v$sqlarea t
 where sql_id in ('ccpn5c32bmfmf');

--也请关注一下这个：
 select * from v$active_session_history where session_id=194

--在别的session先执行如下试验脚本
drop table t purge;
create table t(x int);

select * from v$mystat where rownum=1;
begin
    for i in 1 .. 100000 loop
       insert into t values (i);
      commit;
    end loop;
end;
/

附：贴出部分执行结果
------------------------------------------------------------------------------------------------------
SQL>  select t1.sid, t1.value, t2.name
  2     from v$sesstat t1, v$statname t2
  3    where t2.name like '%user commits%'
  4      and t1.STATISTIC# = t2.STATISTIC#
  5      and value >= 10000
  6    order by value desc;
   SID      VALUE NAME
------ ---------- -------------------------
   132     100003 user commits

SQL>   select t.SID,
  2           t.PROGRAM,
  3              t.EVENT,
  4           t.LOGON_TIME,
  5           t.WAIT_TIME,
  6           t.SECONDS_IN_WAIT,
  7           t.SQL_ID,
  8           t.PREV_SQL_ID
  9     from v$session t
 10    where sid in(132);

   SID PROGRAM              EVENT                            LOGON_TIME     WAIT_TIME SECONDS_IN_WAIT SQL_ID    PREV_SQL_ID
------ -------------------- ---------------------------------------------------------------------- --------------------------
   132 sqlplus.exe          SQL*Net message from client      13-11月-13             0              77           ccpn5c32bmfmf

SQL>   select t.sql_id,
  2           t.sql_text,
  3           t.EXECUTIONS,
  4           t.FIRST_LOAD_TIME,
  5           t.LAST_LOAD_TIME
  6    from v$sqlarea t
  7   where sql_id in ('ccpn5c32bmfmf');
SQL_ID                 SQL_TEXT                          EXECUTIONS            FIRST_LOAD_TIME        LAST_LOAD_TIME
------------------------------------------------------------------------------------------------------------------------------------
ccpn5c32bmfmfbegin     for i in 1 .. 100000 loop             1                 2013-11-13/16:13:56       13-11月-13
                         insert into t values (i);
             commit;
            end loop;
             end;  

日志归档相关案例：

--1、redo大量产生必然是由于大量产生"块改变"。从awr视图中找出"块改变"最多的segments
select * from (
SELECT to_char(begin_interval_time, 'YYYY_MM_DD HH24:MI') snap_time,
       dhsso.object_name,
       SUM(db_block_changes_delta)
  FROM dba_hist_seg_stat     dhss,
       dba_hist_seg_stat_obj dhsso,
       dba_hist_snapshot     dhs
 WHERE dhs.snap_id = dhss. snap_id
   AND dhs.instance_number = dhss. instance_number
   AND dhss.obj# = dhsso. obj#
   AND dhss.dataobj# = dhsso.dataobj#
   AND begin_interval_time> sysdate - 60/1440
 GROUP BY to_char(begin_interval_time, 'YYYY_MM_DD HH24:MI'),
          dhsso.object_name
 order by 3 desc)
 where rownum<=5;

--2、从awr视图中找出步骤1中排序靠前的对象涉及到的SQL
SELECT to_char(begin_interval_time, 'YYYY_MM_DD HH24:MI'),
       dbms_lob.substr(sql_text, 4000, 1),
       dhss.instance_number,
       dhss.sql_id,
       executions_delta,
       rows_processed_delta
  FROM dba_hist_sqlstat dhss, dba_hist_snapshot dhs, dba_hist_sqltext dhst
 WHERE UPPER(dhst.sql_text) LIKE '%这里写对象名大写%'
   AND dhss.snap_id = dhs.snap_id
   AND dhss.instance_Number = dhs.instance_number
   AND dhss.sql_id = dhst.sql_id;

--3、从ASH相关视图中找出执行这些SQL的session、module、machine
select * from dba_hist_active_sess_history WHERE sql_id = '';
select * from v$active_session_history where sql_Id = '';

--4. dba_source 看看是否有存储过程包含这个SQL

--以下操作产生大量的redo,可以用上述的方法进行跟踪
drop table   test_redo  purge;
create table test_redo as select * from dba_objects;
insert into  test_redo select * from test_redo;
insert into  test_redo select * from test_redo;
insert into  test_redo select * from test_redo;
insert into  test_redo select * from test_redo;
insert into  test_redo select * from test_redo;
exec dbms_workload_repository.create_snapshot();