大数据量下的DML操作 bulk collect into limit forall commit;

如果有个大数据量的DML操作事务,在OLAP报表等低并发库里. 并且强制归档模式中.

采用BULK 和FORALL 会比较快!

open cur_COLUMN_USER;  loop   fetch cur_COLUMN_USER bulk collect   into           l_ARY_statedate,                              l_ARY_form,          l_ARY_columnid,                     l_ARY_usernumber,                             l_ARY_new_user,                         l_ARY_exit_use       limit g_batch_size_n;      forall i in 1..l_ARY_statedate.count    insert into content_lst_day    (......)    values(l_ary_statedate(i),....); commit;end loop;

 

相对使用普通游标循环提取数据出来处理的话 会快很多.

原因 1 bulk collect into 到数组  可以一次型把数据提取出来,减少了循环当中PL/SQL和SQL引撑的切换时间

原因 2 forall in ..... 也是一次型提交数据到某个地方 也同样减少了循环当中PL/SQL和SQL引撑的切换时间

注意 1 数据太大 要设置合理的LIMIT 否则提取到数组的数据会爆了PGA的回话内存

原因 3 bulk 内部操作 对insert delete 做了优化 采用批量方法.极大减少了redo 和Undo 使用量.

原因 4 为证明 当一个大数据量的insert 会超级慢,如果分批插入的总时间 比一次插入省很多时间.

 

An ORA-22813 when using BULK COLLECT is typically expected behavior indicating that you have exceeded the amount of free memory in the PGA.  As collections are processed by PL/SQL they use the PGA to store their memory structures.  Depending on the LIMIT size of the BULK COLLECT and additional processing of the collected data you may exceed the free memory of the PGA.  While intuitively you may think that increasing the PGA memory and increasing the LIMIT size will increase performance, the following example shows you that this is not true in this case.  So, by reviewing this example you should be able to strike a balance between a reasonable LIMIT size and the size of the PGA while maintaining a high level of performance using BULK COLLECT.