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概念描述

ORACLE 11g 之后的自动统计信息的阈值默认是10%，也就是表变化超过10%才会进行搜集。如果分区表的某个分区的数据变化超过了10%，但是没有超过整个表的10%，默认情况下会不会进行自动的统计信息搜集呢。

测试验证

  1. 完了方便测试，这里修改当前的 NLS_DATE_FORMAT 显示时分秒。
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SQL> ALTER SESSION SET NLS_DATE_FORMAT = 'YYYY-MM-DD HH24:MI:SS';

Session altered.

  1. 创建分区表

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SQL>  CREATE TABLE TEST_PARTITION2
(
    id NUMBER,
    name VARCHAR2(50),
    register_date DATE
)
PARTITION BY RANGE (register_date)
(
    PARTITION p_2019 VALUES LESS THAN (TO_DATE('01-01-2020', 'dd-mm-yyyy')),
    PARTITION p_2020 VALUES LESS THAN (TO_DATE('01-01-2021', 'dd-mm-yyyy')),
    PARTITION p_2021 VALUES LESS THAN (TO_DATE('01-01-2022', 'dd-mm-yyyy'))
);   
Table created.
  1. 每个分区插入100000 条数据
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SQL> INSERT /*+ APPEND */ INTO TEST_PARTITION2
SELECT rownum, 'name_'||rownum, DATE '2019-01-01' + MOD(rownum, 365)
FROM dual CONNECT BY LEVEL <= 100000;  2    3

100000 rows created.

SQL> commit;

Commit complete.

SQL>  INSERT /*+ APPEND */ INTO TEST_PARTITION2
SELECT rownum+100000, 'name_'||(rownum+100000), DATE '2020-01-01' + MOD(rownum, 365)
FROM dual CONNECT BY LEVEL <= 100000;  2    3

100000 rows created.

SQL> commit;

Commit complete.

SQL>  INSERT /*+ APPEND */ INTO TEST_PARTITION2
SELECT rownum+100000, 'name_'||(rownum+100000), DATE '2021-01-01' + MOD(rownum, 365)
FROM dual CONNECT BY LEVEL <= 100000;  2    3

100000 rows created.

SQL> commit;

Commit complete.

SQL> SELECT COUNT(*) FROM TEST_PARTITION2;

  COUNT(*)
----------
    300000
  1. 验证数据各个分区的数据分布

总共 300000 条数据，每个分区100000 条数据

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SQL> SELECT 'p_2019' as parted, COUNT(*) FROM TEST_PARTITION2 PARTITION(p_2019)
UNION ALL
SELECT 'p_2020' as parted, COUNT(*) FROM TEST_PARTITION2 PARTITION(p_2020)
UNION ALL
SELECT 'p_2021' as parted, COUNT(*) FROM TEST_PARTITION2 PARTITION(p_2021); 
PARTED	       COUNT(*)
------------ ----------
p_2019		 100000
p_2020		 100000
p_2021		 100000
  1. 搜集统计信息并查看
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SQL> EXEC DBMS_STATS.GATHER_TABLE_STATS('SYS','TEST_PARTITION2',estimate_percent=>100,method_opt=>'FOR ALL COLUMNS SIZE AUTO',cascade=>TRUE);

PL/SQL procedure successfully completed.

SQL> set lines 200
col PARTITION_NAME for a40
select partition_name,object_type,num_rows,to_char(last_analyzed,'yyyy-mm-dd hh24:mi:ss') last_analyzed  from dba_tab_statistics where table_name=upper('TEST_PARTITION2');SQL> SQL>

PARTITION_NAME				 OBJECT_TYPE		    NUM_ROWS LAST_ANALYZED
-------------------------------- ------------------------ 
			      		 TABLE			        300000 2023-08-04 11:49:28
P_2019					 PARTITION		      100000 2023-08-04 11:49:27
P_2020					 PARTITION		      100000 2023-08-04 11:49:28
P_2021					 PARTITION		      100000 2023-08-04 11:49:28

统计信息是11:49分搜集的

  1. 分区p_2019 插入16000条数据，超过了当前分区的10%，不超过当前表的总数据看的10%
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SQL> INSERT /*+ APPEND */ INTO TEST_PARTITION2
SELECT rownum, 'name_'||rownum, DATE '2019-01-01' + MOD(rownum, 365)
FROM dual CONNECT BY LEVEL <= 16000;   2    3

16000 rows created.

SQL> commit;

Commit complete.
  1. 分区p_2020 插入 6000 条数据，数据不超过当前分区的10%，变化的总数据也不超过当前表总数据的10%
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SQL> INSERT /*+ APPEND */ INTO TEST_PARTITION2
SELECT rownum+100000, 'name_'||(rownum+100000), DATE '2020-01-01' + MOD(rownum, 365)
FROM dual CONNECT BY LEVEL <= 6000;
commit;  2    3
6000 rows created.

SQL>

Commit complete.
  1. 确认当前数据和统计信息
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SQL>  SELECT 'p_2019' as parted, COUNT(*) FROM TEST_PARTITION2 PARTITION(p_2019)
UNION ALL
SELECT 'p_2020' as parted, COUNT(*) FROM TEST_PARTITION2 PARTITION(p_2020)
UNION ALL
SELECT 'p_2021' as parted, COUNT(*) FROM TEST_PARTITION2 PARTITION(p_2021);  
      
      PARTED	       COUNT(*)
      ------------ ----------
      p_2019		 116000
      p_2020		 106000
      p_2021		 100000
      SQL>  set lines 200
      col PARTITION_NAME for a20
      select partition_name,object_type,num_rows,to_char(last_analyzed,'yyyy-mm-dd hh24:mi:ss') last_analyzed  from dba_tab_statistics where table_name=upper('TEST_PARTITION2');SQL> SQL>
      
      PARTITION_NAME	     OBJECT_TYPE		NUM_ROWS LAST_ANALYZED
      ---------------- ------------------------ ---------- ---------------
      		           TABLE			      300000 2023-08-04 11:49:28
      P_2019		     PARTITION			  100000 2023-08-04 11:49:27
      P_2020		     PARTITION			  100000 2023-08-04 11:49:28
      P_2021		     PARTITION			  100000 2023-08-04 11:49:28
  1. 调整自动统计信息的任务运行时间为12:10
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BEGIN
  DBMS_SCHEDULER.SET_ATTRIBUTE(
                 name       => '"SYS"."THURSDAY_WINDOW"',
                 attribute  => 'REPEAT_INTERVAL',
                 VALUE      => 'freq=daily;byday=THU;byhour=12;byminute=10; bysecond=0');
END;
/
  1. 等自动统计信息的任务执行之后，检查统计信息如下
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SQL>set lines 200
col PARTITION_NAME for a20
select partition_name,object_type,num_rows,to_char(last_analyzed,'yyyy-mm-dd hh24:mi:ss') last_analyzed  from dba_tab_statistics where table_name=upper('TEST_PARTITION2');SQL> SQL>
   
   PARTITION_NAME	 OBJECT_TYPE		NUM_ROWS LAST_ANALYZED
   
   -------------  --------------- ---------- ----------------------
   		           TABLE			      300000 2023-08-04 11:49:28
   P_2019		     PARTITION			  116000 2023-08-04 12:10:38
   P_2020		     PARTITION			  100000 2023-08-04 11:49:28
   P_2021		     PARTITION			  100000 2023-08-04 11:49:28

– 可以看到分区 P_2019 的统计信息在12:10进行了重新搜集

知识总结

经过以上验证，自动搜集统计信息任务的分区表 10% 的阈值，是基于当前分区的。

也就是如果分区表的某个分区的数据变化超过当前分区的10%，而不超过当前表总数据的10%，自动搜集统计信息任务会搜集当前分区的统计信息。

参考文档

原文作者: liups.com

原文链接: http://www.liups.com/posts/aa64b78/

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