如何在亿级记录表中创建索引

1. 查看表的具体情况

查看是不是分区表，有多少个分区、分区字段：

SQL> col table_name for a20

SQL> col column_name for a20

SQL> select a.table_name,a.partitioned,b.partition_count,c.column_name

2 from user_tables a, user_part_tables b, user_part_key_columns c

3 where a.table_name='STAT_SUBMIT_CENTER'

4 and b.table_name='STAT_SUBMIT_CENTER'

5 and c.name='STAT_SUBMIT_CENTER';

TABLE_NAME PAR PARTITION_COUNT COLUMN_NAME

-------------------- --- --------------- --------------------

STAT_SUBMIT_CENTER YES 50 MSGDATE

查看已使用的每个分区的大小：

SQL> select segment_name,partition_name,round(bytes/1024/1024) from user_segments

where segment_name ='STAT_SUBMIT_CENTER' and bytes/1024/1024>0.25 order by 3 desc;

SEGMENT_NAME PARTITION_NAME

SEGMENT_NAME PARTITION_NAME ROUND(BYTES/1024/1024)

-------------------------- ------------------------------ ----------------------

STAT_SUBMIT_CENTER STAT_SUBMIT_CENTER_20051101 1722

STAT_SUBMIT_CENTER STAT_SUBMIT_CENTER_20051021 1488

STAT_SUBMIT_CENTER STAT_SUBMIT_CENTER_20051111 1440

STAT_SUBMIT_CENTER STAT_SUBMIT_CENTER_20051121 1355

STAT_SUBMIT_CENTER STAT_SUBMIT_CENTER_20051221 1335

STAT_SUBMIT_CENTER STAT_SUBMIT_CENTER_20050911 1309

STAT_SUBMIT_CENTER STAT_SUBMIT_CENTER_20051211 1253

STAT_SUBMIT_CENTER STAT_SUBMIT_CENTER_20051201 1247

STAT_SUBMIT_CENTER STAT_SUBMIT_CENTER_20050921 1198

STAT_SUBMIT_CENTER STAT_SUBMIT_CENTER_20060101 1151

STAT_SUBMIT_CENTER STAT_SUBMIT_CENTER_20060111 1068

STAT_SUBMIT_CENTER STAT_SUBMIT_CENTER_20051001 1018

STAT_SUBMIT_CENTER STAT_SUBMIT_CENTER_20051011 865

STAT_SUBMIT_CENTER STAT_SUBMIT_CENTER_20060121 796

14 rows selected.

查看整个表的大小：

SQL> select segment_name,sum(bytes/1024/1024) from user_segments

where segment_name ='STAT_SUBMIT_CENTER' group by segment_name;

SEGMENT_NAME

SEGMENT_NAME SUM(BYTES/1024/1024)

-------------------------------- --------------------

STAT_SUBMIT_CENTER 17234

查看表的记录数：

SQL> set timing on

SQL> select count(*) from STAT_SUBMIT_CENTER;

COUNT(*)

----------

170341007

Elapsed: 00:14:18.60

查看这个表上的索引情况如下：

table STAT_SUBMIT_CENTER 17234 M

index IDX_SUBCEN_ADDRUSER 5155 M ADDRUSER

PK_STAT_SUBMIT_CENTER 10653 M MSGDATE,ADDRUSER,MSGID

然后，查看一些数据库参数情况：

SQL> show parameter work

NAME TYPE VALUE

NAME TYPE VALUE

------------------------------------ ----------- ------------------------------

workarea_size_policy string AUTO

SQL> show parameter pga

NAME TYPE VALUE

------------------------------------ ----------- ------------------------------

pga_aggregate_target big integer 209715200

SQL> select * from dba_temp_files;

FILE_NAME

------------------------------------------------------------------------------------------------------------------------

FILE_ID TABLESPACE_NAME BYTES BLOCKS STATUS RELATIVE_FNO AUT MAXBYTES MAXBLOCKS

---------- ------------------------------ ---------- ---------- --------- ------------ --- ---------- ----------

INCREMENT_BY USER_BYTES USER_BLOCKS

------------ ---------- -----------

/bgdata/oracle/temp01.dbf

1 TEMP 3563061248 434944 AVAILABLE 1 YES 4294967296 5242886400 3562012672 434816

2. 需要考虑的几个方面

1）创建的索引需要几个G的磁盘空间。

2）创建索引需要排序，使用pga_aggregate_target，要把这个值从200M加大到2G。

3）如果内存不够，需要temp表空间，则要把temp表空间加大到8G——itpub上有一个帖子说过，15亿条记录用了34G空间。

4）在线创建，时间会比较长。讨论后，停止这个表的操作，非online创建。

3. 实际操作过程

1）数据文件够，不扩展；temp数据文件扩展：

alter database tempfile '/bgdata/oracle/temp01.dbf' resize 8192m;

2）在workarea_size_policy=AUTO的情况下，改pga_aggregate_target=2048m。对于串行操作，一个session能使用的pga=MIN(5%PGA_AGGREGATE_TARGET,100MB)，这样可以使得pga用到最大的值：

alter system set pga_aggregate_target=2048m;

3）因为这是一个比较长的过程，所以写脚本让后台运行：

nohup time createind.sh &

vi createind.sh

#!/bin/sh

sqlplus user/password <create index IDX_SUBMIT_RECORDTIME on STAT_SUBMIT_CENTER(RECORDTIME) local;

exit

EOF

4）创建过程中可以观察v$sort_segment，v$sort_usage看排序情况：

nohup time createind.sh &

vi createind.sh

#!/bin/sh

sqlplus user/password <create index IDX_SUBMIT_RECORDTIME on STAT_SUBMIT_CENTER(RECORDTIME) local;

exit

EOF

5）创建完成后，把tempfile和pga_aggregate_target改回原值：

alter database tempfile '/bgdata/oracle/temp01.dbf' resize 4096m;

alter system set pga_aggregate_target=500m;

4. 实际创建过程中观察到的情况

1）开始之前：

SQL> select tablespace_name,current_users,total_blocks,used_blocks,free_blocks from v$sort_segment;

TABLESPACE_NAME CURRENT_USERS TOTAL_BLOCKS USED_BLOCKS FREE_BLOCKS

------------------------------- ------------- ------------ ----------- -----------

TEMP 0 431360 0 431360

SQL> select * from v$sort_usage;

no rows selected

2）创建之初，抓到这么一条sql：

insert into obj$(owner#,name,namespace,obj#,type#,ctime,mtime,st

ime,status,remoteowner,linkname,subname,dataobj#,flags,oid$,spar

e1,spare2)values(:1,:2,:3,:4,:5,:6,:7,:8,:9,:10,:11,:12,:13,:14,

:15,:16, :17)

3）然后v$sort_segment.USED_BLOCKS变大，v$sort_usage.BLOCKS变大，一直增长到：

SQL> select tablespace_name,current_users,total_blocks,used_blocks,free_blocks from v$sort_segment;

TABLESPACE_NAME CURRENT_USERS TOTAL_BLOCKS USED_BLOCKS FREE_BLOCKS

------------------------------- ------------- ------------ ----------- -----------

TEMP 1 431360 46720 384640

SQL> select * from v$sort_usage;

USERNAME USER SESSION_ADDR SESSION_NUM SQLADDR SQLHASH

------------------------------ ------------------------------ ---------------- ----------- ---------------- ----------

TABLESPACE CONTENTS SEGTYPE SEGFILE# SEGBLK# EXTENTS BLOCKS SEGRFNO#

------------------------------- --------- --------- ---------- ---------- ---------- ---------- ----------

DPC DPC 00000003974CFFB0 6134 0000000399CAB288 1254950678

TEMP TEMPORARY SORT 201 431113 365 46720 1

这个过程中抓到的sql为：

select file# from file$ where ts#=:1

4）v$sort_segment.USED_BLOCKS变为0，v$sort_usage.BLOCKS变为0。

5）重复3，4两步，估计这个是创建一个分区的索引。

需要解释一下的是，上面的sql只是我随机抓到的运行时间比较长的，整个create index过程会复杂很多，具体怎么样可以用sqltrace跟踪。这里主要看的是temp表空间的使用情况。

同时，在创建的过程中：

SQL> select segment_name,partition_name from user_segments where segment_name='IDX_SUBMIT_RECORDTIME';

no rows selected

SQL> select index_name,partition_name from user_ind_partitions where INDEX_NAME='IDX_SUBMIT_RECORDTIME';

no rows selected

当时忘了查user_segments中其实是有一个segment_name为一串数字的记录，那个才是正在创建的索引；如果这个事务失败了，将回滚。

最后耗时99分钟完成。

5. 创建完成后分析索引

但是接下来还有一件事。创建完成后要分析索引，否则就是走了索引，查询速度也会很慢。

SQL> explain plan for select count(*) from stat_submit_center where recordtime>trunc(sysdate);

Explained.

SQL> @?/rdbms/admin/utlxplp.sql

PLAN_TABLE_OUTPUT

------------------------------------------------------------------------------------------------------------------------

-------------------------------------------------------------------------------------------------

| Id | Operation | Name | Rows | Bytes | Cost | Pstart| Pstop |

-------------------------------------------------------------------------------------------------

| 0 | SELECT STATEMENT | | 1 | 9 | 4 | | |

| 1 | SORT AGGREGATE | | 1 | 9 | | | |

| 2 | PARTITION RANGE ALL | | | | | 1 | 50 |

|* 3 | INDEX FAST FULL SCAN| IDX_SUBMIT_RECORDTIME | 8878K| 76M| 4 | 1 | 50 |

-------------------------------------------------------------------------------------------------

Predicate Information (identified by operation id):

---------------------------------------------------

3 - filter("STAT_SUBMIT_CENTER"."RECORDTIME">TRUNC(SYSDATE@!))

Note: cpu costing is off

16 rows selected.

SQL> set autotrace on explain

SQL> set timing on

SQL> select count(*) from stat_submit_center where recordtime>trunc(sysdate);

aa^Cselect count(*) from stat_submit_center where recordtime>trunc(sysdate)

*

ERROR at line 1:

ORA-01013: user requested cancel of current operation

Elapsed: 00:11:49.85

SQL>

SQL> set autotrace off

上面可以看到，因为没有分析索引，虽然它走的是新建的IDX_SUBMIT_RECORDTIME索引，但是查询速度很慢，10分钟后也没有结果。下面我们分析一下：

SQL> Analyze index IDX_SUBMIT_RECORDTIME estimate statistics;

Index analyzed.

Elapsed: 00:00:06.84

SQL> set autotrace on explain

SQL> select count(*) from stat_submit_center where recordtime>trunc(sysdate);

COUNT(*)

----------

926736

Elapsed: 00:00:05.37

Execution Plan

----------------------------------------------------------

0 SELECT STATEMENT Optimizer=CHOOSE (Cost=4360 Card=1 Bytes=9)

1 0 SORT (AGGREGATE)

2 1 PARTITION RANGE (ALL)

3 2 INDEX (RANGE SCAN) OF 'IDX_SUBMIT_RECORDTIME' (NON-UNI

QUE) (Cost=4360 Card=8878740 Bytes=79908660)

SQL> set autotrace off

索引分析之后，查询时间为5分钟左右，效率大大提高。

至此，完成全部操作。