mysql中数据统计的技巧备忘录
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2023-11-04 16:29:58
mysql 作为常用数据库,操作贼六是必须的,对于数字操作相关的东西,那是相当方便,本节就来拎几个统计案例出来供参考!
order订单表,样例如下:
creat...
mysql 作为常用数据库,操作贼六是必须的,对于数字操作相关的东西,那是相当方便,本节就来拎几个统计案例出来供参考!
order订单表,样例如下:
create table `yyd_order` ( `id` bigint(20) unsigned not null auto_increment, `user_id` int(11) not null, `order_nid` varchar(50) not null, `status` varchar(50) not null default '0', `money` decimal(20,2) not null default '0.00', `create_time` timestamp not null default current_timestamp, `update_time` timestamp not null default current_timestamp on update current_timestamp, primary key (`id`), key `userid` (`user_id`), key `createtime` (`create_time`), key `updatetime` (`update_time`) ) engine=innodb;
1. 按天统计进单量,date_format
select date_format(t.`create_time`, '%y-%m-%d') t_date, count(1) t_count from t_order t where t.`create_time` > '2018-05-11' group by date_format(t.`create_time`, '%y-%m-%d');
2. 按小时统计进单量
select date_format(t.`create_time`, '%y-%m-%d %h') t_hour, count(1) t_count from t_order t where t.`create_time` > '2018-05-11' group by date_format(t.`create_time`, '%y-%m-%d %h');
3. 同比昨天进单量对比,order by h, date
select date_format(t.`create_time`, '%y-%m-%d %h') t_date, count(1) t_count from yyd_order t where t.`create_time` > '2018-05-11' group by date_format(t.`create_time`, '%y-%m-%d %h') order by date_format(t.`create_time`, '%h'),date_format(t.`create_time`, '%y-%m-%d %h');
4. 环比上周同小时进单,date in ,order by
select date_format(t.`create_time`, '%y-%m-%d %h') t_date, count(1) t_count from yyd_order t where date_format(t.`create_time`,'%y-%m-%d') in ('2018-05-03','2018-05-11') group by date_format(t.`create_time`, '%y-%m-%d %h') order by date_format(t.`create_time`, '%h'),date_format(t.`create_time`, '%y-%m-%d %h');
5. 按照remark字段中的返回值进行统计,group by remark like ...
select date_format(t.`create_time`, '%y-%m-%d') t_date, count(1) t_count, substring_index(substring_index(t.`msg`, '{', -1), '}', 1) t_rsp_msg from cmoo_tab t where t.`create_time` > '2018-05-17' and t.`rsp_msg` like '%nextprocesscode%c9000%' group by date_format(t.`create_time`, '%y-%m-%d'),substring_index(substring_index(t.`rsp_msg`, '{', -1), '}', 1);
6. 统计每小时的各金额的区间数统计,sum if 1 0,各自统计
select date_format(t.create_time,'%y-%m-%d') t_date, sum(if(t.`amount`>0 and t.`amount`<1000, 1, 0)) t_0_1000, sum(if(t.`amount`>1000 and t.`amount`<5000, 1, 0)) t_1_5000, sum(if(t.`amount`>5000, 1, 0)) t_5000m from mobp2p.`yyd_order` t where t.`create_time` > '2018-05-11' group by date_format(t.`create_time`, '%y-%m-%d');
7. 按半小时统计进单量,floor h / 30,同理10分钟,20分钟
select concat(date_format(create_time, '%y-%m-%d %h:' ),if(floor(date_format(create_time, '%i') / 30 ) = 0, '00','30')) as time_scope, count(*) from yyd_order where create_time>'2018-05-11' group by time_scope order by date_format(create_time, '%h:%i'), date_format(create_time, '%y-%m-%d') desc ;
8. 成功率,失败率,临时表 join on hour
select * from (select date_format(t.`create_time`, '%y-%m-%d') t_date,count(1) '成功数' from yyd_order t where t.`create_time` > '2018-05-17' and t.`status` = 'repay_yes' group by date_format(t.`create_time`, '%y-%m-%d')) t1 right join (select date_format(t.`create_time`, '%y-%m-%d') t_date,count(1) '总数' from yyd_order t where t.`create_time` > '2018-05-11' group by date_format(t.`create_time`, '%y-%m-%d')) t2 on t1.t_date=t2.t_date;
9. 更新日志表中最后条一条日志状态值到信息表中状态,update a join b on xx set a.status=b.status where tmp group by userid tmp2,注意索引
update t_order t0 left join (select * from (select * from t_order_log t where t.create_time>'2018-05-11' order by id desc) t1 group by t1.user_id ) on t.user_id=t2.user_id set t0.`status`=t2.status where t0.`create_time`>'2018-05-11' and t0.`status`=10;
10. 备份表,create table as select xxx where xxx
create table t_m as select * from t_order;
11. 纯改备注不锁表,快,类型全一致
总结
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