emp表有如下数据。
SQL> select ename,deptno from emp; ENAME DEPTNO ------------------------------ ---------- SMITH 20 ALLEN 30 WARD 30 JONES 20 MARTIN 30 BLAKE 30 CLARK 10 SCOTT 20 KING 10 TURNER 30 ADAMS 20 JAMES 30 FORD 20 MILLER 10 14 rows selected.
假设我们有如下简单的查询
select ename,deptno from emp where ename=‘RICH‘ and deptno=10;
那么Oracle在执行查询的时候，是先比较ename字段呢？还是先比较deptno字段呢？
显然先比较deptno再比较ename字段的效率明显低于先比较ename，再比较deptno。 那Oracle究竟如何去判断呢？
我们先查询一张表
SQL> COL COLUMN_NAME FOR A30 SQL> SELECT column_name, num_distinct, density FROM dba_tab_columns WHERE owner = ‘SCOTT‘ AND table_name = ‘EMP‘; COLUMN_NAME NUM_DISTINCT DENSITY ------------------------------ ------------ ---------- EMPNO 14 .071428571 ENAME 14 .071428571 JOB 5 .2 MGR 6 .166666667 HIREDATE 13 .076923077 SAL 12 .083333333 COMM 4 .25 DEPTNO 3 .333333333 8 rows selected.
Oracle其实知道，你的表中存放数据的一些特征，上面语句显示的只是凤毛麟角。通过这些特征，Oracle优化器就能知道如何去查询，使得执行的效率最高。
以上这些信息，我们称之为对象的统计信息。那么如何收集统计信息呢？
一、 analyze 命令
使用analyze命令可以收集统计信息，如：
- 收集或删除对象的统计信息
- 验证对象的结构
- 确定table 或cluster的migrated 和chained rows。
示例：
SQL> create user anal identified by anal ; User created. SQL> grant resource,connect to anal; Grant succeeded. SQL> grant select any dictionary to anal; Grant succeeded. SQL> conn anal/anal Connected. SQL> create table t1 as select * from dba_objects; SQL> create table t2 as select * from dba_objects; SQL> create table t3 as select * from dba_objects; SQL> create table t4 as select * from dba_objects; SQL> create table t5 as select * from dba_objects; SQL> create table t6 as select * from dba_objects; SQL> create unique index pk_t1_idx on t1(object_id); SQL> create unique index pk_t2_idx on t2(object_id); SQL> create unique index pk_t3_idx on t3(object_id); SQL> create unique index pk_t4_idx on t4(object_id); SQL> create unique index pk_t5_idx on t5(object_id); SQL> create unique index pk_t6_idx on t6(object_id);
我们先查看一下统计信息是否存在
查看表的统计信息
SQL> select table_name, num_rows, blocks, empty_blocks from user_tables where table_name in (‘T1‘, ‘T2‘, ‘T3‘, ‘T4‘, ‘T5‘,‘T6‘);
查看字段统计信息
select table_name, column_name, num_distinct, low_value, high_value, density from user_tab_columns where table_name in (‘T1‘, ‘T2‘, ‘T3‘, ‘T4‘,‘T5‘,‘T6‘);
查看索引统计信息
SQL> col table_name for a30 SQL> col index_name for a30 SELECT table_name, index_name, blevel, leaf_blocks, distinct_keys, avg_leaf_blocks_per_key avg_leaf_blocks, avg_data_blocks_per_key avg_data_blocks, clustering_factor, num_rows FROM user_indexes TABLE_NAME INDEX_NAME BLEVEL LEAF_BLOCKS DISTINCT_KEYS AVG_LEAF_BLOCKS AVG_DATA_BLOCKS CLUSTERING_FACTOR NUM_ROWS ------------------------------ ------------------------------ ---------- ----------- ------------- --------------- --------------- ----------------- ---------- T6 PK_T6_IDX 1 155 74564 1 1 1174 74564 T5 PK_T5_IDX 1 155 74563 1 1 1174 74563 T4 PK_T4_IDX 1 155 74562 1 1 1174 74562 T3 PK_T3_IDX 1 155 74561 1 1 1174 74561 T2 PK_T2_IDX 1 155 74560 1 1 1174 74560 T1 PK_T1_IDX 1 155 74559 1 1 1174 74559 6 rows selected.
表没有任何统计数据，但是索引已经有统计信息，可见在建立表的时候会默认收集统计信息。
先将索引的统计信息删除
SQL> analyze table t1 delete statistics; analyze table t2 delete statistics; analyze table t3 delete statistics; analyze table t4 delete statistics; analyze table t5 delete statistics; analyze table t6 delete statistics;
验证索引上是否还存在统计信息
SELECT table_name, index_name, blevel, leaf_blocks, distinct_keys, avg_leaf_blocks_per_key avg_leaf_blocks, avg_data_blocks_per_key avg_data_blocks, clustering_factor, num_rows FROM user_indexes
执行统计信息命令，并查看统计信息有无变化
analyze table t1 compute statistics for table;
--针对表收集信息，查看user_tables
analyze table t2 compute statistics for all columns;
--针对表字段收集信息，查看user_tab_columns
analyze table t3 compute statistics for all indexed columns;
--收集索引字段信息
analyze table t4 compute statistics;
--收集表，表字段，索引信息
analyze table t5 compute statistics for all indexes;
--收集索引信息
analyze table t6 compute statistics for table for all indexes for all columns;
--收集表，表字段，索引信息
二、DBMS_STATS包
Oracle推荐使用DBMS_STATS这个包来收集统计信息。这个包的功能非常多。可以收集数据库级别、schema级别及表级别的统计信息。还可以对统计信息删除、锁定、导出、导入等。我们以最常用的表级别统计为例说明DBMS_STATS该如何使用。
收集的统计信存储在dba_tab_statistics、dba_ind_statistics和dba_tab_col_statistics表中。
DBMS_STATS.GATHER_TABLE_STATS ( ownname VARCHAR2, tabname VARCHAR2, partname VARCHAR2 DEFAULT NULL, estimate_percent NUMBER DEFAULT to_estimate_percent_type (get_param(‘ESTIMATE_PERCENT‘)), block_sample BOOLEAN DEFAULT FALSE, method_opt VARCHAR2 DEFAULT get_param(‘METHOD_OPT‘), degree NUMBER DEFAULT to_degree_type(get_param(‘DEGREE‘)), granularity VARCHAR2 DEFAULT GET_PARAM(‘GRANULARITY‘), cascade BOOLEAN DEFAULT to_cascade_type(get_param(‘CASCADE‘)), stattab VARCHAR2 DEFAULT NULL, statid VARCHAR2 DEFAULT NULL, statown VARCHAR2 DEFAULT NULL, no_invalidate BOOLEAN DEFAULT to_no_invalidate_type ( get_param(‘NO_INVALIDATE‘)), stattype VARCHAR2 DEFAULT ‘DATA‘, force BOOLEAN DEFAULT FALSE);
参数说明如下：
示例：
SQL> col table_name for a30 SQL> SELECT table_name, num_rows, blocks, empty_blocks, avg_row_len FROM user_tab_statistics; TABLE_NAME NUM_ROWS BLOCKS EMPTY_BLOCKS AVG_ROW_LEN ------------------------------ ---------- ---------- ------------ ----------- T1 74559 1088 0 98 T2 T3 T4 T5 T6 6 rows selected.
删除统计信息
DBMS_STATS.DELETE_TABLE_STATS ( ownname VARCHAR2, tabname VARCHAR2, partname VARCHAR2 DEFAULT NULL, stattab VARCHAR2 DEFAULT NULL, statid VARCHAR2 DEFAULT NULL, cascade_parts BOOLEAN DEFAULT TRUE, cascade_columns BOOLEAN DEFAULT TRUE, cascade_indexes BOOLEAN DEFAULT TRUE, statown VARCHAR2 DEFAULT NULL, no_invalidate BOOLEAN DEFAULT to_no_invalidate_type ( get_param(‘NO_INVALIDATE‘)), force BOOLEAN DEFAULT FALSE);
锁定统计信息
DBMS_STATS.LOCK_TABLE_STATS ( ownname VARCHAR2, tabname VARCHAR2);
锁定以后就不能再执行统计信息
SQL> exec dbms_stats.lock_table_stats(user,‘T1‘); PL/SQL procedure successfully completed. SQL> exec dbms_stats.gather_table_stats(user,‘t1‘,cascade=>true); BEGIN dbms_stats.gather_table_stats(user,‘t1‘,cascade=>true); END; * ERROR at line 1: ORA-20005: object statistics are locked (stattype = ALL) ORA-06512: at "SYS.DBMS_STATS", line 23829 ORA-06512: at "SYS.DBMS_STATS", line 23880 ORA-06512: at line 1
导出、导入统计信息
- 要导出统计信息首先要建立一个统计表
语法：
DBMS_STATS.CREATE_STAT_TABLE ( ownname VARCHAR2, stattab VARCHAR2, tblspace VARCHAR2 DEFAULT NULL);
SQL> exec DBMS_STATS.CREATE_STAT_TABLE (user,‘STAT_TMP‘,‘SYSAUX‘); PL/SQL procedure successfully completed.
2. 将表t1统计信息导出
DBMS_STATS.EXPORT_TABLE_STATS ( ownname VARCHAR2, tabname VARCHAR2, partname VARCHAR2 DEFAULT NULL, stattab VARCHAR2, statid VARCHAR2 DEFAULT NULL, cascade BOOLEAN DEFAULT TRUE, statown VARCHAR2 DEFAULT NULL, stat_category VARCHAR2 DEFAULT DEFAULT_STAT_CATEGORY);
SQL> EXEC DBMS_STATS.EXPORT_TABLE_STATS (ownname=>USER,tabname=>‘T1‘,stattab=>‘STAT_TMP‘); PL/SQL procedure successfully completed.
3. 导入统计信息
语法：
DBMS_STATS.IMPORT_TABLE_STATS ( ownname VARCHAR2, tabname VARCHAR2, partname VARCHAR2 DEFAULT NULL, stattab VARCHAR2, statid VARCHAR2 DEFAULT NULL, cascade BOOLEAN DEFAULT TRUE, statown VARCHAR2 DEFAULT NULL, no_invalidate BOOLEAN DEFAULT to_no_invalidate_type( get_param(‘NO_INVALIDATE‘)), force BOOLEAN DEFAULT FALSE, stat_category VARCHAR2 DEFAULT DEFAULT_STAT_CATEGORY);
SQL> exec dbms_stats.UNlock_table_stats(user,‘T1‘); PL/SQL procedure successfully completed. SQL> exec dbms_stats.delete_table_stats(user,‘T1‘); PL/SQL procedure successfully completed. SQL> EXEC DBMS_STATS.IMPORT_TABLE_STATS (ownname=>USER,tabname=>‘T1‘,stattab=>‘STAT_TMP‘); PL/SQL procedure successfully completed. SQL> SELECT table_name, num_rows, blocks, empty_blocks, avg_row_len FROM user_tab_statistics; 2 3 4 5 6 TABLE_NAME NUM_ROWS BLOCKS EMPTY_BLOCKS AVG_ROW_LEN ------------------------------ ---------- ---------- ------------ ----------- T1 74559 1088 0 98 T2 T3 T4 T5 T6 STAT_TMP 7 rows selected.
如果是分区表，新的分区来不及收集统计系统，可以使用其它的分区统计信息来生成新分区的统计信息
DBMS_STATS.COPY_TABLE_STATS ( ownname VARCHAR2, tabname VARCHAR2, srcpartname VARCHAR2, dstpartname VARCHAR2, scale_factor VARCHAR2 DEFAULT 1, force BOOLEAN DEFAULT FALSE);
如果表还没有统计信息，那么在执行sql语句时，Oracle会动态的采样表中的一部分数据，生成统计信息。
SQL> show parameter optimizer_dynamic_sampling ; NAME TYPE VALUE ------------------------------------ --------------------------------- ------------------------------ optimizer_dynamic_sampling integer 2
时间： 2024-10-19 07:47:09