=======================================================================

SQL语句:

SELECT wave_no,
SUM(IF(picking_qty IS NULL, 0, picking_qty)) AS PICKED_QTY,
SUM(IF(differ_qty IS NULL, 0, differ_qty)) AS PICKED_DIFFER_QTY,
SUM(IF(relocate_qty IS NULL, 0, relocate_qty)) AS PICKED_RELOCATE_QTY FROM picking_locate_d
WHERE yn = 0
AND wave_no IN
(
'BC76361213164811',
'BC76361213164810',
'BC76361213154684',
'BC76361213155125'
)
AND org_No= '661'
AND distribute_No = '763'
AND warehouse_No = '612'
GROUP BY wave_no;

执行计划:

+----+-------------+------------------+------------+-------+---------------+-------------+---------+------+-------+----------+------------------------------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+------------------+------------+-------+---------------+-------------+---------+------+-------+----------+------------------------------------+
| 1 | SIMPLE | picking_locate_d | NULL | range | idx_wave_no | idx_wave_no | 153 | NULL | 16000 | 0.10 | Using index condition; Using where |
+----+-------------+------------------+------------+-------+---------------+-------------+---------+------+-------+----------+------------------------------------+

执行计划JOSN:

EXPLAIN: {
"query_block": {
"select_id": 1,
"cost_info": {
"query_cost": "9548371.80"
},
"grouping_operation": {
"using_filesort": false,
"table": {
"table_name": "picking_locate_d",
"access_type": "index",
"possible_keys": [
"idx_wave_no"
],
"key": "idx_wave_no",
"used_key_parts": [
"wave_no"
],
"key_length": "153",
"rows_examined_per_scan": 37518548,
"rows_produced_per_join": 1875,
"filtered": "0.01",
"cost_info": {
"read_cost": "9547996.61",
"eval_cost": "375.19",
"prefix_cost": "9548371.80",
"data_read_per_join": "11M"
},
"used_columns": [
"id",
"wave_no",
"picking_qty",
"differ_qty",
"relocate_qty",
"org_no",
"distribute_no",
"warehouse_no",
"yn"
],
"attached_condition": "(
(`report`.`picking_locate_d`.`yn` = 0)
and (`report`.`picking_locate_d`.`wave_no` in ('BC76361213164811','BC76361213164810','BC76361213155124','BC76361213154684','BC76361213155125'))
and (`report`.`picking_locate_d`.`org_no` = '661')
and (`report`.`picking_locate_d`.`distribute_no` = '763')
and (`report`.`picking_locate_d`.`warehouse_no` = '612')
)"
}
}
}
}

=======================================================================

将wave_no IN修改为CONCAT(wave_no,'') IN进行测试

SQL语句:

SELECT wave_no,
SUM(IF(picking_qty IS NULL, , picking_qty)) AS PICKED_QTY,
SUM(IF(differ_qty IS NULL, , differ_qty)) AS PICKED_DIFFER_QTY,
SUM(IF(relocate_qty IS NULL, , relocate_qty)) AS PICKED_RELOCATE_QTY FROM picking_locate_d
WHERE yn =
AND CONCAT(wave_no,'') IN
(
'BC76361213164811',
'BC76361213164810',
'BC76361213154684',
'BC76361213155125'
)
AND org_No= ''
AND distribute_No = ''
AND warehouse_No = ''
GROUP BY wave_no

执行计划:

+----+-------------+------------------+------------+-------+---------------+-------------+---------+------+----------+----------+-------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+------------------+------------+-------+---------------+-------------+---------+------+----------+----------+-------------+
| | SIMPLE | picking_locate_d | NULL | index | idx_wave_no | idx_wave_no | | NULL | | 0.01 | Using where |
+----+-------------+------------------+------------+-------+---------------+-------------+---------+------+----------+----------+-------------+

执行计划JSON:

EXPLAIN: {
"query_block": {
"select_id": ,
"cost_info": {
"query_cost": "9549155.40"
},
"grouping_operation": {
"using_filesort": false,
"table": {
"table_name": "picking_locate_d",
"access_type": "index",
"possible_keys": [
"idx_wave_no"
],
"key": "idx_wave_no",
"used_key_parts": [
"wave_no"
],
"key_length": "",
"rows_examined_per_scan": ,
"rows_produced_per_join": ,
"filtered": "0.01",
"cost_info": {
"read_cost": "9548404.95",
"eval_cost": "750.45",
"prefix_cost": "9549155.40",
"data_read_per_join": "22M"
},
"used_columns": [
"id",
"wave_no",
"picking_qty",
"differ_qty",
"relocate_qty",
"org_no",
"distribute_no",
"warehouse_no",
"yn"
],
"attached_condition": "(
(`report`.`picking_locate_d`.`yn` = )
and (concat(`report`.`picking_locate_d`.`wave_no`,'') in ('BC76361213164811','BC76361213164810','BC76361213154684','BC76361213155125'))
and (`report`.`picking_locate_d`.`org_no` = '')
and (`report`.`picking_locate_d`.`distribute_no` = '')
and (`report`.`picking_locate_d`.`warehouse_no` = '')
)"
}
}
}
}

=======================================================================

去除org_No/distribute_No/warehouse_No任意列的过滤条件,如去除AND org_No= '661'

SQL语句

SELECT wave_no,
SUM(IF(picking_qty IS NULL, , picking_qty)) AS PICKED_QTY,
SUM(IF(differ_qty IS NULL, , differ_qty)) AS PICKED_DIFFER_QTY,
SUM(IF(relocate_qty IS NULL, , relocate_qty)) AS PICKED_RELOCATE_QTY FROM picking_locate_d
WHERE yn =
AND wave_no IN
(
'BC76361213164811',
'BC76361213164810',
'BC76361213154684',
'BC76361213155125'
)
## AND org_No= ''
AND distribute_No = ''
AND warehouse_No = ''
GROUP BY wave_no;

执行计划:

+----+-------------+------------------+------------+-------+---------------+-------------+---------+------+----------+----------+-------------+
| id | select_type | table | partitions | type | possible_keys | key | key_len | ref | rows | filtered | Extra |
+----+-------------+------------------+------------+-------+---------------+-------------+---------+------+----------+----------+-------------+
| | SIMPLE | picking_locate_d | NULL | index | idx_wave_no | idx_wave_no | | NULL | | 0.01 | Using where |
+----+-------------+------------------+------------+-------+---------------+-------------+---------+------+----------+----------+-------------+

执行计划JSON

EXPLAIN: {
"query_block": {
"select_id": ,
"cost_info": {
"query_cost": "38400.01"
},
"grouping_operation": {
"using_filesort": false,
"table": {
"table_name": "picking_locate_d",
"access_type": "range",
"possible_keys": [
"idx_wave_no"
],
"key": "idx_wave_no",
"used_key_parts": [
"wave_no"
],
"key_length": "",
"rows_examined_per_scan": ,
"rows_produced_per_join": ,
"filtered": "0.10",
"index_condition": "(
(`report`.`picking_locate_d`.`wave_no` in ('BC76361213164811','BC76361213164810','BC76361213154684','BC76361213155125'))
and (`report`.`picking_locate_d`.`distribute_no` = '')
and (`report`.`picking_locate_d`.`warehouse_no` = '')
)",
"cost_info": {
"read_cost": "38396.81",
"eval_cost": "3.20",
"prefix_cost": "38400.01",
"data_read_per_join": "98K"
},
"used_columns": [
"id",
"wave_no",
"picking_qty",
"differ_qty",
"relocate_qty",
"org_no",
"distribute_no",
"warehouse_no",
"yn"
],
"attached_condition": "(`report`.`picking_locate_d`.`yn` = 0)"
}
}
}
}

MySQL Execution Plan--IN子查询包含超多值引发的查询异常1的更多相关文章

  1. MySQL Execution Plan--IN子查询包含超多值引发的查询异常

    问题描述 版本:MySQL 5.7.24 SQL语句: SELECT wave_no, SUM(IF(picking_qty IS NULL, 0, picking_qty)) AS PICKED_Q ...

  2. MySQL Execution Plan--NOT EXISTS子查询优化

    在很多业务场景中,会使用NOT EXISTS语句来确保返回数据不存在于特定集合,部分场景下NOT EXISTS语句性能较差,网上甚至存在谣言"NOT EXISTS无法走索引". 首 ...

  3. query_string查询支持全部的Apache Lucene查询语法 低频词划分依据 模糊查询 Disjunction Max

    3.3 基本查询3.3.1词条查询 词条查询是未经分析的,要跟索引文档中的词条完全匹配注意:在输入数据中,title字段含有Crime and Punishment,但我们使用小写开头的crime来搜 ...

  4. Mysql查询优化器之关于子查询的优化

    下面这些sql都含有子查询: mysql> select * from t1 where a in (select a from t2); mysql> select * from (se ...

  5. MySQL(八)子查询和分组查询

    一.子查询 1.子查询(subquery):嵌套在其他查询中的查询. 例如:select user_id from usertable where mobile_no in (select mobil ...

  6. MySQL之多表查询一 介绍 二 多表连接查询 三 符合条件连接查询 四 子查询 五 综合练习

    MySQL之多表查询 阅读目录 一 介绍 二 多表连接查询 三 符合条件连接查询 四 子查询 五 综合练习 一 介绍 本节主题 多表连接查询 复合条件连接查询 子查询 首先说一下,我们写项目一般都会建 ...

  7. 为什么MySQL不推荐使用子查询和join

    前言: 1.对于mysql,不推荐使用子查询和join是因为本身join的效率就是硬伤,一旦数据量很大效率就很难保证,强烈推荐分别根据索引单表取数据,然后在程序里面做join,merge数据. 2.子 ...

  8. MySQL中 如何查询表名中包含某字段的表 ,查询MySql数据库架构信息:数据库,表,表字段

    --查询tablename 数据库中 以"_copy" 结尾的表 select table_name from information_schema.tables where ta ...

  9. mysql update不支持子查询更新

    先看示例: SELECT uin,account,password,create_user_uin_tree FROM sys_user 结果: 表中的create_user_uin_tree标识该条 ...

随机推荐

  1. 第一个jQuery

    第一个jQuery <script src = "jquery.js"> $(document).ready(function){ alert("Hello ...

  2. pyCharm中BeautifulSoup应用

    BeautifulSoup 是第三方库的工具,它包含在一个名为bs4的文件包中,需要额外安装,安装方式 非常简单,进入python的安装目录,再进入scripts子目录,找到pip程序, pip in ...

  3. PCA降维—降维后样本维度大小

    之前对PCA的原理挺熟悉,但一直没有真正使用过.最近在做降维,实际用到了PCA方法对样本特征进行降维,但在实践过程中遇到了降维后样本维数大小限制问题. MATLAB自带PCA函数:[coeff, sc ...

  4. Vue语法学习第四课(1)——组件简单示例

    在 Vue 里,一个组件本质上是一个拥有预定义选项的一个 Vue 实例. 设法将应用分割成了两个更小的单元.子单元通过 prop 接口与父单元进行了良好的解耦. <div id="ap ...

  5. [Paper][Link note]

    http://ieeexplore.ieee.org/document/6974670/

  6. python并发_线程

    关于进程的复习: # 管道 # 数据的共享 Manager dict list # 进程池 # cpu个数+1 # ret = map(func,iterable) # 异步 自带close和join ...

  7. db.properties是干什么用的

    连接池配置文件db.properties是java中采用数据库连接池技术完成应用对数据库的操作的配置文件信息的文件.具体配置项目如下:drivers=com.microsoft.sqlserver.j ...

  8. double 四舍五入保留一定的位数

    /** * double 类型的 四舍五入 保留一定的位数 * @param value * @param decimal 保留的位数 * @return * @throws Exception */ ...

  9. tp5 删除服务器文件

    public function test(){ //ROOT_PATH . 'public' . DS . 'uploads' $filename = ROOT_PATH . 'public' . D ...

  10. C# 记录日志

    public static void WriteLogs(string fileName, string type, string content) { string path = AppDomain ...