--将项目中的总监,经理,等的邮箱合并为一行 SELECT GROUP_CONCAT(t.USER_EMAIL SEPARATOR ' ') mail_address FROM portal.t_acl_userinfo AS t WHERE t.username IN (SELECT DISTINCT a FROM ( SELECT * FROM ( SELECT XM_MANAGER a FROM xm_main WHERE xm_code='p20190132') A UNION ALL
关联表更新字段 UPDATE tmp369faa3f7d224b0595670425008 as t1 SET FStatus=-1 where exists(select 1 from t_BD_Supplier where FUseOrgId = t1.FDestOrgID and FMasterId = t1.FMasterId) UPDATE 后面使用别名必须加AS: 另一种写法: update t_pm_otherowner set fcontrolunitid=(select fco
----查询所有的表 SELECT * FROM SYSOBJECTS WHERE TYPE='U' ----根据表名查询所有的字段名及其注释 SELECT A.NAME,B.VALUE FROM SYSCOLUMNS A LEFT JOIN SYS.EXTENDED_PROPERTIES B ON A.ID=B.MAJOR_ID AND A.COLID=B.MINOR_ID INNER JOIN SYSOBJECTS C ON A.ID=C.ID AND UPPER(C.NAME)='tb_n
假设有A.B两表 A表中有个字段column_aa B表中有个字段column_bb 如果需要查询出B表中字段column_bb like A表中column_aa字段的纪录,可以使用如下语句 select A.* from A left join B on column_aa like concat("%",column_bb,"%") ; 通过concat拼接like的值.
最近要查询一些数据库的基本情况,由于以前用oracle数据库比较多,现在换了MySQL数据库,就整理了一部分语句记录下来. 1.查询数据库表数量 #查询MySQL服务中数据库表数据量 SELECT COUNT(*) TABLES, table_schema FROM information_schema.TABLES GROUP BY table_schema; #查询指定数据库表数量 SELECT COUNT(*) TABLES, table_schema FROM information_s
表太多,只记得这个表有一个mygame的字段,但是并不知道这张表在那个数据库下,只能根据这个字段查找对应的表和所在数据库 select table_schema,table_name from information_schema.columns where column_name = '字段名' 演例: mysql> select table_schema,table_name from information_schema.columns where column_name = 'gname
基本格式: DELETE t1 FROM t1,t2 WHERE t1.id=t2.id 或 DELETE FROM t1 USING t1,t2 WHERE t1.id=t2.id 示例应用: DELETE coupon FROM coupon,member WHERE coupon.mem_no=member.reg_no AND coupon.`status`=0 AND coupon.`batch_no`='yaoqingpengyou001' AND member.`mobile`
UPDATE T_ASN_DTL ad1 SET ad1.cf03=( SELECT ac.TH003 FROM "T_ASN_DTL_copy" ac WHERE ac.udf06=ad1.INSPECTER_NAME and ac.udf05=ad1.LINE_ITEM_NO ) FROM "T_ASN_DTL_copy" ac WHERE ac.udf06=ad1.INSPECTER_NAME and ac.udf05=ad1.LINE_ITEM_NO) UP
转至:https://stackoverflow.com/questions/12113699/get-top-n-records-for-each-group-of-grouped-results 通过分组的排序及序号获取条数信息,可以使用到索引,没测试性能,不知道和mssql的cross apply性能差异性为多少,只是能实现相应的效果. #MySQL #please drop objects you've created at the end of the script #or check