Oracle analyze table的作用

oracle的联机文档描述了analyze的作用：

use the analyze statement to collect non-optimizer statistics, for example, to:

collect or delete statistics about an index or index partition, table or table partition, index-organized table, cluster, or scalar object attribute.

validate the structure of an index or index partition, table or table partition, index-organized table, cluster, or object reference (ref).

identify migrated and chained rows of a table or cluster.

dbms_stats的作用主要是替代analyze的收集统计信息这一块的功能，且在这一方面做了相当大程度上的增强。

以你的analyze table abc compute statistics;

这条为例，生成的统计信息会存在于user_tables这个视图，查看一下select * from user_tables where table_name=’abc’;

观察一下num_rows,blocks,avg_space,avg_row_len几列你就会明白，这就是变化。

收集统计信息的目的是为了使基于cbo的执行计划更加准确。

对于oracle analyze table的使用总结 . 对于oracle analyze table的使用总结 .
analyze table 一般可以指定分析： 表，所有字段，所有索引字段，所有索引。 若不指定则全部都分析。
sql> analyze table my_table compute statistics;  
sql> analyze table my_table compute statistics for table for all indexes for all columns;   
sql> analyze table my_table compute statistics for table for all indexes for all indexed columns;  
其中：
sql> analyze table my_table compute statistics;  
等价于：
sql> analyze table my_table compute statistics for table for all indexes for all columns;   
sample:
analyze table t1 compute statistics for table;
analyze table t2 compute statistics for all columns;
analyze table t3 compute statistics for all indexed columns;
analyze table t5 compute statistics for all indexes; 
analyze table t4 compute statistics;     (不指定）
另外，可以删除分析数据：
sql> analyze table my_table delete statistics;
sql> analyze table my_table delete statistics for table for all indexes for all indexed columns;  
https://wfly2004.blog.163.com/blog/static/1176427201042891042233/
首先创建四个临时表t1,t2,t3,t4,和他们相对应的索引 
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代码:
create table t1 as select * from user_objects;
create table t2 as select * from user_objects;
create table t3 as select * from user_objects;
create table t4 as select * from user_objects;
create unique index pk_t1_idx on t1(object_id);
create unique index pk_t2_idx on t2(object_id);
create unique index pk_t3_idx on t3(object_id);
create unique index pk_t4_idx on t4(object_id);
查看这个时候各个表对应的数据库统计信息(表,字段,索引) 
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代码:
--查看表的统计信息
select table_name,num_rows,blocks,empty_blocks from user_table where table_names in ('t1','t2','t3','t4');
table_name        num_rows        blocks        empty_blocks
t1                        
t2                        
t3                        
t4                       
--查看字段的统计信息
select table_name,column_name,num_distinct,low_value,high_value,density from user_tab_columns where table_name in ('t1','t2','t3','t4');
table_name        column_name        num_distinct        low_value        high_value        density
t1        object_name                                
t1        subobject_name                                
t1        object_id                                
t1        data_object_id                                
t1        object_type                                
t1        created                                
t1        last_ddl_time                                
t1        timestamp                                
t1        status                                
t1        temporary                                
t1        generated                                
t1        secondary                                
t2        object_name                                
t2        subobject_name                                
t2        object_id                                
t2        data_object_id                                
t2        object_type                                
t2        created                                
t2        last_ddl_time                                
t2        timestamp                                
t2        status                                
t2        temporary                                
t2        generated                                
t2        secondary                                
t3        object_name                                
t3        subobject_name                                
t3        object_id                                
t3        data_object_id                                
t3        object_type                                
t3        created                                
t3        last_ddl_time                                
t3        timestamp                                
t3        status                                
t3        temporary                                
t3        generated                                
t3        secondary                                
t4        object_name                                
t4        subobject_name                                
t4        object_id                                
t4        data_object_id                                
t4        object_type                                
t4        created                                
t4        last_ddl_time                                
t4        timestamp                                
t4        status                                
t4        temporary                                
t4        generated                                
t4        secondary                               
--查看索引的统计信息
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 where table_name in ('t1','t2','t3','t4');
table_name        index_name        blevel        leaf_blocks        distinct_keys        avg_leaf_blocks        avg_data_blocks        clustering_factor        num_rows
t1        pk_t1_idx                                                        
t2        pk_t2_idx                                                        
t3        pk_t3_idx                                                        
t4        pk_t4_idx          
现在我们分别对这个表做不同形式的analyze table处理 
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代码:
analyze table t1 compute statistics for table;
analyze table t2 compute statistics for all columns;
analyze table t3 compute statistics for all indexed columns;
analyze table t4 compute statistics;
我们再回头看看这是的oracle数据库对于各种统计信息 
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代码:
--这是对于表的统计信息
select table_name,num_rows,blocks,empty_blocks from user_tables where table_name in ('t1','t2','t3','t4');
table_name        num_rows        blocks        empty_blocks
t1        3930        55        1
t2                        
t3                        
t4        3933        55        1
--我们可以据此得出结论,只有我们在analyze table命令中指定了for table或者不指定任何参数的时候,oracle数据库才会给我们统计基于表的统计信息
--这是对于表中字段的统计信息
select table_name,column_name,num_distinct,low_value,high_value,density from user_tab_columns where table_name in ('t1','t2','t3','t4');
table_name        column_name        num_distinct        low_value        high_value        density
t1        object_name                                
t1        subobject_name                                
t1        object_id                                
t1        data_object_id                                
t1        object_type                                
t1        created                                
t1        last_ddl_time                                
t1        timestamp                                
t1        status                                
t1        temporary                                
t1        generated                                
t1        secondary                                
t2        object_name        3823        41423030        d3f1bbb736d4c2b7ddcffabba7c7e5b5a5        .000270447891062615
t2        subobject_name        77        503031        52455354        .012987012987013
t2        object_id        3930        c304062d        c30f4619        .000254452926208651
t2        data_object_id        3662        c304062d        c30f4619        .000273074822501365
t2        object_type        15        4441544142415345204c494e4b        56494557        .000127194098193844
t2        created        3684        7867081e111f33        7868071211152f        .000547559423988464
t2        last_ddl_time        3574        7867081e11251b        7868071211152f        .000565522924083892
t2        timestamp        3649        323030332d30382d33303a31363a33303a3530        323030342d30372d31383a31363a32303a3436        .000559822349362313
t2        status        2        494e56414c4944        56414c4944        .000127194098193844
t2        temporary        2        4e        59        .000127194098193844
t2        generated        2        4e        59        .000127194098193844
t2        secondary        2        4e        59        .000127194098193844
t3        object_name                                
t3        subobject_name                                
t3        object_id        3931        c304062d        c30f461a        .000254388196387688
t3        data_object_id                                
t3        object_type                                
t3        created                                
t3        last_ddl_time                                
t3        timestamp                                
t3        status                                
t3        temporary                                
t3        generated                                
t3        secondary                                
t4        object_name        3825        41423030        d3f1bbb736d4c2b7ddcffabba7c7e5b5a5        .000261437908496732
t4        subobject_name        77        503031        52455354        .012987012987013
t4        object_id        3932        c304062d        c30f461b        .000254323499491353
t4        data_object_id        3664        c304062d        c30f461b        .00027292576419214
t4        object_type        15        4441544142415345204c494e4b        56494557        .0666666666666667
t4        created        3685        7867081e111f33        78680712111530        .000271370420624152
t4        last_ddl_time        3575        7867081e11251b        78680712111530        .00027972027972028
t4        timestamp        3650        323030332d30382d33303a31363a33303a3530        323030342d30372d31383a31363a32303a3437        .000273972602739726
t4        status        2        494e56414c4944        56414c4944        .5
t4        temporary        2        4e        59        .5
t4        generated        2        4e        59        .5
t4        secondary        2        4e        59        .5
/*
在这个结果中我们可以看到,oracle数据库给t2,t4的所有字段都做了统计信息.
对表t3的object_id(索引字段)做了统计信息.
由此得出结论,
在指定for all columns 和不指定任何参数的时候oracle会给所有字段做统计信息,在指定for indexed columns时,oracle只给[b]有索引的字段进行字段信息统计[/b],如果我们别有必要给所有字段统计信息时,这个属性就很有用了.
*/
--这里是对于索引的统计信息
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 where table_name in ('t1','t2','t3','t4');
table_name        index_name        blevel        leaf_blocks        distinct_keys        avg_leaf_blocks        avg_data_blocks        clustering_factor        num_rows
t1        pk_t1_idx                                                        
t2        pk_t2_idx                                                        
t3        pk_t3_idx                                                        
t4        pk_t4_idx        1        9        3932        1        1        2143        3932
--从这里我们可以看出,只有表t4有索引统计信息.
--再综合前面的我们就会发现,如果在运行analyze table是我们不指定参数,oracle将收集对于特定表的所有统计信息(表,索引,表字段的统计信息)
补充,truncate命令不修改以上统计信息
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代码:
truncate table t1;
truncate table t2;
truncate table t3;
truncate table t4;
--我们在查看表和索引的统计信息
select table_name,num_rows,blocks,empty_blocks from user_tables where table_name in ('t1','t2','t3','t4');
table_name        num_rows        blocks        empty_blocks
t1        3930        55        1
t2                        
t3                        
t4        3933        55        1
--索引的统计信息
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 where table_name in ('t1','t2','t3','t4');
table_name        index_name        blevel        leaf_blocks        distinct_keys        avg_leaf_blocks        avg_data_blocks        clustering_factor        num_rows
t1        pk_t1_idx                                                        
t2        pk_t2_idx                                                        
t3        pk_t3_idx                                                        
t4        pk_t4_idx        1        9        3932        1        1        2143        3932
--我们再对以上各表做一次分析
analyze table t1 compute statistics for table;
analyze table t2 compute statistics for all columns;
analyze table t3 compute statistics for all indexed columns;
analyze table t4 compute statistics;
--现在再来查看表和索引的统计信息
select table_name,num_rows,blocks,empty_blocks,initial_extent,'8192' block_size from user_tables where table_name in ('t1','t2','t3','t4');
table_name        num_rows        blocks        empty_blocks        initial_extent        block_size
t1        0        0        8        65536        8192
t2                                65536        8192
t3                                65536        8192
t4        0        0        8        65536        8192
--索引的统计信息
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 where table_name in ('t1','t2','t3','t4');
table_name        index_name        blevel        leaf_blocks        distinct_keys        avg_leaf_blocks        avg_data_blocks        clustering_factor        num_rows
t1        pk_t1_idx                                                        
t2        pk_t2_idx                                                        
t3        pk_t3_idx                                                        
t4        pk_t4_idx        0        0        0        0        0        0        0
--由此得出结论,truncate命令不会修改数据的统计信息,
--也就是如果我们想让cbo利用合理利用数据的统计信息的时候,需要我们及时的使用analyze命令或者dbms_stats重新统计数据的统计信息
分类: oralcerac