Analyze 和dbms_stats.gather_table_stats区别

Analyze Statement
The ANALYZE statement can be used to gather statistics for a specific table, index or cluster. The statistics can be computed exactly, or estimated based on a specific number of rows, or a percentage of rows:

ANALYZE TABLE employees COMPUTE STATISTICS;
ANALYZE INDEX employees_pk COMPUTE STATISTICS;

ANALYZE TABLE employees ESTIMATE STATISTICS SAMPLE 100 ROWS;
ANALYZE TABLE employees ESTIMATE STATISTICS SAMPLE 15 PERCENT;
DBMS_UTILITY
The DBMS_UTILITY package can be used to gather statistics for a whole schema or database. Both methods follow the same format as the analyze statement:

EXEC DBMS_UTILITY.analyze_schema('SCOTT','COMPUTE');
EXEC DBMS_UTILITY.analyze_schema('SCOTT','ESTIMATE', estimate_rows => 100);
EXEC DBMS_UTILITY.analyze_schema('SCOTT','ESTIMATE', estimate_percent => 15);

EXEC DBMS_UTILITY.analyze_database('COMPUTE');
EXEC DBMS_UTILITY.analyze_database('ESTIMATE', estimate_rows => 100);
EXEC DBMS_UTILITY.analyze_database('ESTIMATE', estimate_percent => 15);
DBMS_STATS
The DBMS_STATS package was introduced in Oracle 8i and is Oracles preferred method of gathering object statistics. Oracle list a number of benefits to using it including parallel execution, long term storage of statistics and transfer of statistics between servers. Once again, it follows a similar format to the other methods:

EXEC DBMS_STATS.gather_database_stats;
EXEC DBMS_STATS.gather_database_stats(estimate_percent => 15);

EXEC DBMS_STATS.gather_schema_stats('SCOTT');
EXEC DBMS_STATS.gather_schema_stats('SCOTT', estimate_percent => 15);

EXEC DBMS_STATS.gather_table_stats('SCOTT', 'EMPLOYEES');
EXEC DBMS_STATS.gather_table_stats('SCOTT', 'EMPLOYEES', estimate_percent => 15);

EXEC DBMS_STATS.gather_index_stats('SCOTT', 'EMPLOYEES_PK');
EXEC DBMS_STATS.gather_index_stats('SCOTT', 'EMPLOYEES_PK', estimate_percent => 15);
This package also gives you the ability to delete statistics:

EXEC DBMS_STATS.delete_database_stats;
EXEC DBMS_STATS.delete_schema_stats('SCOTT');
EXEC DBMS_STATS.delete_table_stats('SCOTT', 'EMPLOYEES');
EXEC DBMS_STATS.delete_index_stats('SCOTT', 'EMPLOYEES_PK');

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自从Oracle8.1.5引入dbms_stats包，Experts们便推荐使用dbms_stats取代analyze。 理由如下

dbms_stats可以并行分析
dbms_stats有自动分析的功能(alter table monitor )
analyze 分析统计信息的不准确some times


1,2好理解，且第2点实际上在VLDB中是最吸引人的；3以前比较模糊，看了metalink236935.1 解释，analyze在分析Partition表的时候，有时候会计算出不准确的Global statistics .

原因是，dbms_stats会实在的去分析表全局统计信息（当指定参数）；而analyze是将表分区（局部）的statistics 汇总计算成表全局statistics ,可能导致误差。

如果想分析整个用户或数据库，还可以采用工具包，可以并行分析
Dbms_utility(8i以前的工具包)
Dbms_stats(8i以后提供的工具包)
如
dbms_stats.gather_schema_stats(User,estimate_percent=>100,cascade=> TRUE);
dbms_stats.gather_table_stats(User,TableName,degree => 4,cascade => true);

这是对命令与工具包的一些总结

1、对于分区表，建议使用DBMS_STATS，而不是使用Analyze语句。
a) 可以并行进行，对多个用户，多个Table
b) 可以得到整个分区表的数据和单个分区的数据。
c) 可以在不同级别上Compute Statistics：单个分区，子分区，全表，所有分区
d) 可以倒出统计信息
e) 可以用户自动收集统计信息

2、DBMS_STATS的缺点
a) 不能Validate Structure
b) 不能收集CHAINED ROWS, 不能收集CLUSTER TABLE的信息，这两个仍旧需要使用Analyze语句。
c) DBMS_STATS 默认不对索引进行Analyze，因为默认Cascade是False，需要手工指定为True

3、对于oracle 9里面的External Table，Analyze不能使用，只能使用DBMS_STATS来收集信息。

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10G的文档是这么说的：
Do not use the COMPUTE and ESTIMATE clauses of ANALYZE to collect optimizer statistics. These clauses are supported for backward compatibility. Instead, use the DBMS_STATS package, which lets you collect statistics in parallel, collect global statistics for partitioned objects, and fine tune your statistics collection in other ways. The cost-based optimizer, which depends upon statistics, will eventually use only statistics that have been collected by DBMS_STATS

analyze的功能已经明确：
Use the ANALYZE statement (rather than DBMS_STATS) for statistics collection not related to the cost-based optimizer :

To use the VALIDATE or LIST CHAINED ROWS clauses

To collect information on freelist blocks

在收集与CBO优化器不相关的统计信息的时候ANALYZE语句要优于DBMS_STATS包

-----------------------------------
EX:
begin
        for owner in (select username from dba_users where username not in ('SYS','SYSTEM'))
        loop
         dbms_output.disable;
         dbms_output.enable(1000000);
         dbms_output.put_line('Schema: '||owner.username);
         select sysdate into start_time from dual;
         dbms_output.put_line('Analyze start from : '||start_time);
         dbms_stats.gather_schema_stats(ownname => owner.username, estimate_percent => 20, block_sample=> true, cascade=>true);
         select sysdate into end_time from dual;
         dbms_output.put_line('Analyze complete at : '||end_time);
         dbms_output.put_line('---------------------------');
        end loop;


dbms_stats.gather_table_stats(ownname          =>,
                                tabname          =>,
                                partname         =>,
                                estimate_percent =>,
                                block_sample     =>,
                                method_opt       =>,
                                degree           =>,parallel degree(并行收集维度)　看CPU个数
                                granularity      =>,
                                cascade          =>,true is also gather columns and index’s statistics;
                                no_invalidate    =>);