MariaDB10.2.X支持分析函数

前言:前段时间看到MariaDB10.2出测试版本了,心想有什么新特性玩玩,大家都知道MySQL不支持分析函数,但是MariaDB10.2.X支持分析函数了,

1.表结构

CREATE TABLE `t1` (

`id` int(11) NOT NULL AUTO_INCREMENT,

`userId` varchar(30) NOT NULL COMMENT ‘用户ID‘,

`orderId` varchar(60) NOT NULL DEFAULT ‘‘ COMMENT ‘订单ID‘,

`channerId` varchar(60) NOT NULL DEFAULT ‘‘ COMMENT ‘充值渠道‘,

`amount` int(11) DEFAULT NULL COMMENT ‘充值金额‘,

PRIMARY KEY (`id`),

KEY `idx_userid` (`userId`),

KEY `idx_channerId` (`channerId`)

) ENGINE=InnoDB  DEFAULT CHARSET=utf8

2.插入测试数据

insert into t1 (userId, orderId, channerId, amount) values(‘张3‘,‘2016060101‘,‘支付宝‘,100);

insert into t1 (userId, orderId, channerId, amount) values(‘李4‘,‘2016060102‘,‘支付宝‘,98);

insert into t1 (userId, orderId, channerId, amount) values(‘张3‘,‘2016060103‘,‘易票联‘,60);

insert into t1 (userId, orderId, channerId, amount) values(‘张3‘,‘2016060104‘,‘银联‘,120);

insert into t1 (userId, orderId, channerId, amount) values(‘王5‘,‘2016060105‘,‘微信‘,170);

insert into t1 (userId, orderId, channerId, amount) values(‘张3‘,‘2016060106‘,‘微信‘,40);

insert into t1 (userId, orderId, channerId, amount) values(‘张3‘,‘2016060107‘,‘支付宝‘,200);

insert into t1 (userId, orderId, channerId, amount) values(‘张3‘,‘2016060108‘,‘易支付‘,10);

insert into t1 (userId, orderId, channerId, amount) values(‘张3‘,‘2016060109‘,‘微信‘,‘80);

insert into t1 (userId, orderId, channerId, amount) values(‘李4‘,‘2016060110‘,‘支付宝‘,300);

insert into t1 (userId, orderId, channerId, amount) values(‘李4‘,‘2016060111‘,‘银联‘,40);

insert into t1 (userId, orderId, channerId, amount) values(‘李4‘,‘2016060112‘,‘钱包‘,72);

insert into t1 (userId, orderId, channerId, amount) values(‘赵6‘,‘2016060113‘,‘闪付‘,20);

insert into t1 (userId, orderId, channerId, amount) values(‘田7‘,‘2016060114‘,‘钱包‘,80);

insert into t1 (userId, orderId, channerId, amount) values(‘刘1‘,‘2016060115‘,‘微信‘,60);

insert into t1 (userId, orderId, channerId, amount) values(‘哈2‘,‘2016060116‘,‘易支付‘,82);

3.查询每个充值渠道的总金额

MariaDB [test11]> select channerId,sum(amount) over(partition by channerId) from t1;

+-----------+------------------------------------------+

| channerId | sum(amount) over(partition by channerId) |

+-----------+------------------------------------------+

| 支付宝    |                                      698 |

| 支付宝    |                                      698 |

| 易票联    |                                       60 |

| 银联      |                                      160 |

| 微信      |                                      350 |

| 微信      |                                      350 |

| 支付宝    |                                      698 |

| 易支付    |                                       92 |

| 微信      |                                      350 |

| 支付宝    |                                      698 |

| 银联      |                                      160 |

| 钱包      |                                      152 |

| 闪付      |                                       20 |

| 钱包      |                                      152 |

| 微信      |                                      350 |

| 易支付    |                                       92 |

+-----------+------------------------------------------+

16 rows in set (0.02 sec)

MariaDB [test11]> select * from (

-> select channerId,sum(amount) over(partition by channerId) from t1) a

->  GROUP BY channerId;

+-----------+------------------------------------------+

| channerId | sum(amount) over(partition by channerId) |

+-----------+------------------------------------------+

| 微信      |                                      350 |

| 支付宝    |                                      698 |

| 易支付    |                                       92 |

| 易票联    |                                       60 |

| 钱包      |                                      152 |

| 银联      |                                      160 |

| 闪付      |                                       20 |

+-----------+------------------------------------------+

7 rows in set (0.02 sec)

4.查询每个渠道平均充值金额

MariaDB [test11]> select channerId,avg(amount) over(partition by channerId) from t1

-> ;

+-----------+------------------------------------------+

| channerId | avg(amount) over(partition by channerId) |

+-----------+------------------------------------------+

| 支付宝    |                                 174.5000 |

| 支付宝    |                                 174.5000 |

| 易票联    |                                  60.0000 |

| 银联      |                                  80.0000 |

| 微信      |                                  87.5000 |

| 微信      |                                  87.5000 |

| 支付宝    |                                 174.5000 |

| 易支付    |                                  46.0000 |

| 微信      |                                  87.5000 |

| 支付宝    |                                 174.5000 |

| 银联      |                                  80.0000 |

| 钱包      |                                  76.0000 |

| 闪付      |                                  20.0000 |

| 钱包      |                                  76.0000 |

| 微信      |                                  87.5000 |

| 易支付    |                                  46.0000 |

+-----------+------------------------------------------+

16 rows in set (0.01 sec)

MariaDB [test11]> select * from (

-> select channerId,avg(amount) over(partition by channerId) from t1) a

-> GROUP BY channerId;

+-----------+------------------------------------------+

| channerId | avg(amount) over(partition by channerId) |

+-----------+------------------------------------------+

| 微信      |                                  87.5000 |

| 支付宝    |                                 174.5000 |

| 易支付    |                                  46.0000 |

| 易票联    |                                  60.0000 |

| 钱包      |                                  76.0000 |

| 银联      |                                  80.0000 |

| 闪付      |                                  20.0000 |

+-----------+------------------------------------------+

7 rows in set (0.00 sec)

5.查询每个渠道最小充值金额

MariaDB [test11]> select * from ( select channerId,min(amount) over(partition by channerId) from t1) a   GROUP BY channerId;

ERROR 1235 (42000): This version of MariaDB doesn‘t yet support ‘This aggregate as window function‘

可惜不支持

6.查询每个驱动最大充值金额

MariaDB [test11]> select * from ( select channerId,max(amount) over(partition by channerId) from t1) a   GROUP BY channerId;

ERROR 1235 (42000): This version of MariaDB doesn‘t yet support ‘This aggregate as window function‘

MariaDB [test11]>

聪明的你,一下子猜测到不支持

#7.根据每个充值渠道,根据充值金额排名

MariaDB [test11]> SELECT RANK() OVER (PARTITION BY channerId ORDER BY amount desc ) AS rank,     DENSE_RANK() OVER (PARTITION BY channerId ORDER BY amount desc ) AS dense_rank,     ROW_NUMBER() OVER (PARTITION BY channerId ORDER BY amount desc) AS row_num, userId,channerId,amount    from t1 ;

+------+------------+---------+--------+-----------+--------+

| rank | dense_rank | row_num | userId | channerId | amount |

+------+------------+---------+--------+-----------+--------+

|    3 |          3 |       3 | 张3    | 支付宝    |    100 |

|    4 |          4 |       4 | 李4    | 支付宝    |     98 |

|    1 |          1 |       1 | 张3    | 易票联    |     60 |

|    1 |          1 |       1 | 张3    | 银联      |    120 |

|    1 |          1 |       1 | 王5    | 微信      |    170 |

|    4 |          4 |       4 | 张3    | 微信      |     40 |

|    2 |          2 |       2 | 张3    | 支付宝    |    200 |

|    2 |          2 |       2 | 张3    | 易支付    |     10 |

|    2 |          2 |       2 | 张3    | 微信      |     80 |

|    1 |          1 |       1 | 李4    | 支付宝    |    300 |

|    2 |          2 |       2 | 李4    | 银联      |     40 |

|    2 |          2 |       2 | 李4    | 钱包      |     72 |

|    1 |          1 |       1 | 赵6    | 闪付      |     20 |

|    1 |          1 |       1 | 田7    | 钱包      |     80 |

|    3 |          3 |       3 | 刘1    | 微信      |     60 |

|    1 |          1 |       1 | 哈2    | 易支付    |     82 |

+------+------------+---------+--------+-----------+--------+

16 rows in set (0.00 sec)

MariaDB [test11]>

小结

跟Oracle,PostgreSQL, SQL SERVER还是有差距,不过已经很不错了。希望官方版本也引进这个新特性

时间: 2024-08-24 17:04:10

MariaDB10.2.X支持分析函数的相关文章

MariaDB10.2.X-新特性2-支持check约束and with as

前几天写了一篇MariaDB10.2支持分析函数,大家印象中MySQL不支持with as ,check约束,那么MariaDB10.2也同样给你惊喜 1.with as MariaDB [test11]> with a as ( select * from t1 where channerId ='支付宝' )  select * from a; +----+--------+------------+-----------+--------+ | id | userId | orderId 

Oracle Lead(),Lag()

Lead()就是取当前顺序的下一条记录,相对Lag()就是取当前顺序的上一行记录 语法结构: lead(value_expr [,offset][,default]) over([query_partition_clause] order by Order_by_clause) 参数说明: value_expr 值表达式,通常是字段,也可是是表达式.value_expr本身不支持分析函数,也就是lead不支持多层调用. offset 偏移,应该是很熟悉的数学概念了,或者是相对偏移,表格来开当前行

mysql 累计值计算

由于mysql没有很好的支持分析函数,现在以SUM分析函数为例,做一下mysql的按日累计值计算 mysql 累计计算 select DateID TRAN_DT, REGI_CH REGI_CH, TRAN_CH TRAN_CH, IFNULL(DRAW_CT, 0) DRAW_CT, round(IFNULL(DRAW_AMT, 0),2) DRAW_AMT, ALL_DRAW_CT, round(ALL_DRAW_AMT, 2) ALL_DRAW_AMT from (select d.Da

视频直播的发展趋势分析

视频直播的分析与发展 在讲视频直播之前,先讲一讲直播.直播是怎么来的呢?从传播消息的角度上来说,视频和文字.图片.音乐一样都是传播消息的手段,古时以文字传播消息,之后出现了图片和音乐,再之后视频开始流行.出现这种演变的原因是什么呢?我想主要是由于读者的需求日益提高和传播技术的不断发展.读者不满足于当前的文字阅读,由此出现了图片与音乐,到后来图片与音乐也无法满足日益增长的需求,则出现了视频.视频具有文字.图片.音乐不具有的优势:传递的信息多,更让人有代入感,给观众更综合的体验.虽然视频有着无可比拟

mariadb10.xGTID复制方式

常用的master_log_file,master_log_pos复制方式,当主库宕机时会造成数据不一致问题: mariadb10.x默认就是支持GTID的复制方式  1.不支持的参数 gtid-mode=on enforce-gtid-consistency=true 2.修改的参数 slave-parallel-workers参数修改为slave-parallel-threads 3.连接至主服务使用的命令 增加:master_use_gtid= current_pos | slave_po

安装配置mariadb-10.1.19

本文参考:http://chenzehe.iteye.com/blog/1266260  感谢原作者的分享! 首先安装/更新一些编译时会用到的基础包 [[email protected] local]# yum -y install gcc gcc-c++ make cmake ncurses ncurses-devel libxml2 libxml2-devel openssl-devel bison bison-devel mariadb下载: ftp://mirrors.fe.up.pt/

mariadb-10.1.22mariadb编译安装

官方下载地址: https://mirrors.tuna.tsinghua.edu.cn/mariadb//mariadb-10.1.22/source/mariadb-10.1.22.tar.gz 1.首先查询下是否安装了mysql或者旧版本mariadb rpm -qa | grep mysql 删除rm -rf /etc/my.cnf 2.安装依赖包 #  yum install  -y  libevent # yum groupinstall -y Development Tools #

mariadb-10.0.13安装+ mysql(一)

安装环境 [[email protected] ~]# yum install cmake -y [[email protected] ~]# !268 yum groupinstall "Development Tools" "Server Platform Development" -y 创建用户 [[email protected] ~]# groupadd -r -g 306 mysql [[email protected] ~]# useradd -r -

Oracle 分析函数的使用(主要是rollup用法)

分析函数是oracle 8.1.6中就引入的一个全新的概念,为我们分析数据提供了一种简单高效的处理方式.在分析函数出现以前,我们必须使用自联查询,子查询或者内联视图,甚至复杂的存储过程实现的语句,现在只要一条简单的sql语句就可以实现了,而且在执行效率方面也有相当大的提高. 分析函数参考手册:http://xsb.itpub.net/post/419/33028 分析函数的使用方法1. 自动汇总函数rollup,cube,2. rank 函数, rank,dense_rank,row_numbe