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 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 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。