Hive函数:SUM,AVG,MIN,MAX
转自:http://lxw1234.com/archives/2015/04/176.htm,Hive分析窗口函数(一) SUM,AVG,MIN,MAX
之前看到大数据田地有关于max()over(partition by)的用法,今天恰好工作中用到了它,但是使用中遇到了一个问题:在max(rsrp)over(partition by buildingid,height) as max_rsrp返回的结果不是分组中的最大值。最中找到了问题的原因:max_rsrp数据类型为string而不是double类型,导致的一个bug问题。
再处理的过程中也再次把大数据田地的中关于sum,avg,max,min的函数用法做了demo,因此有了该参考后的文章。
数据准备:
echo ''>data_file.txt
vim data_file.txt
cookie1,2015-04-10,1
cookie1,2015-04-11,5
cookie1,2015-04-12,7
cookie1,2015-04-13,3
cookie1,2015-04-14,2
cookie1,2015-04-15,4
cookie1,2015-04-16,4
cookie2,2015-04-10,6
cookie2,2015-04-11,5
cookie2,2015-04-12,7
cookie2,2015-04-13,4
cookie2,2015-04-14,3
cookie2,2015-04-15,5
cookie2,2015-04-16,5
hadoop fs -rm -r /user/jrf/test_data
hadoop fs -mkdir /user/jrf/test_data
hadoop fs -copyFromLocal data_file.txt /user/jrf/test_data/
drop table if exists test_data;
create EXTERNAL TABLE test_data (
cookieid string,
createtime string, --day
pv INT
) ROW FORMAT DELIMITED
FIELDS TERMINATED BY ','
stored as textfile location '/user/jrf/test_data/';
select * from test_data;
+---------------------+-----------------------+---------------+--+
| test_data.cookieid | test_data.createtime | test_data.pv |
+---------------------+-----------------------+---------------+--+
| cookie1 | 2015-04-10 | 1 |
| cookie1 | 2015-04-11 | 5 |
| cookie1 | 2015-04-12 | 7 |
| cookie1 | 2015-04-13 | 3 |
| cookie1 | 2015-04-14 | 2 |
| cookie1 | 2015-04-15 | 4 |
| cookie1 | 2015-04-16 | 4 |
| cookie2 | 2015-04-10 | 6 |
| cookie2 | 2015-04-11 | 5 |
| cookie2 | 2015-04-12 | 7 |
| cookie2 | 2015-04-13 | 4 |
| cookie2 | 2015-04-14 | 3 |
| cookie2 | 2015-04-15 | 5 |
| cookie2 | 2015-04-16 | 5 |
+---------------------+-----------------------+---------------+--+
SUM — 注意,结果和ORDER BY相关,默认为升序
SELECT cookieid,createtime,pv,
SUM(pv) OVER(PARTITION BY cookieid ORDER BY createtime) AS pv1, -- 默认为从起点到当前行
SUM(pv) OVER(PARTITION BY cookieid ORDER BY createtime ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS pv2, --从起点到当前行,结果同pv1
SUM(pv) OVER(PARTITION BY cookieid) AS pv3,--分组内所有行
SUM(pv) OVER(PARTITION BY cookieid ORDER BY createtime ROWS BETWEEN 3 PRECEDING AND CURRENT ROW) AS pv4,--当前行+往前3行
SUM(pv) OVER(PARTITION BY cookieid ORDER BY createtime ROWS BETWEEN 3 PRECEDING AND 1 FOLLOWING) AS pv5,--当前行+往前3行+往后1行
SUM(pv) OVER(PARTITION BY cookieid ORDER BY createtime ROWS BETWEEN CURRENT ROW AND UNBOUNDED FOLLOWING) AS pv6 --当前行+往后所有行
FROM test_data order by cookieid,createtime;
+-----------+-------------+-----+------+------+------+------+------+------+--+
| cookieid | createtime | pv | pv1 | pv2 | pv3 | pv4 | pv5 | pv6 |
+-----------+-------------+-----+------+------+------+------+------+------+--+
| cookie1 | 2015-04-10 | 1 | 1 | 1 | 26 | 1 | 6 | 26 |
| cookie1 | 2015-04-11 | 5 | 6 | 6 | 26 | 6 | 13 | 25 |
| cookie1 | 2015-04-12 | 7 | 13 | 13 | 26 | 13 | 16 | 20 |
| cookie1 | 2015-04-13 | 3 | 16 | 16 | 26 | 16 | 18 | 13 |
| cookie1 | 2015-04-14 | 2 | 18 | 18 | 26 | 17 | 21 | 10 |
| cookie1 | 2015-04-15 | 4 | 22 | 22 | 26 | 16 | 20 | 8 |
| cookie1 | 2015-04-16 | 4 | 26 | 26 | 26 | 13 | 13 | 4 |
| cookie2 | 2015-04-10 | 6 | 6 | 6 | 35 | 6 | 11 | 35 |
| cookie2 | 2015-04-11 | 5 | 11 | 11 | 35 | 11 | 18 | 29 |
| cookie2 | 2015-04-12 | 7 | 18 | 18 | 35 | 18 | 22 | 24 |
| cookie2 | 2015-04-13 | 4 | 22 | 22 | 35 | 22 | 25 | 17 |
| cookie2 | 2015-04-14 | 3 | 25 | 25 | 35 | 19 | 24 | 13 |
| cookie2 | 2015-04-15 | 5 | 30 | 30 | 35 | 19 | 24 | 10 |
| cookie2 | 2015-04-16 | 5 | 35 | 35 | 35 | 17 | 17 | 5 |
+-----------+-------------+-----+------+------+------+------+------+------+--+
pv1: 分组内从起点到当前行的pv累积,如,11号的pv1=10号的pv+11号的pv, 12号=10号+11号+12号
pv2: 同pv1
pv3: 分组内(cookie1)所有的pv累加
pv4: 分组内当前行+往前3行,如,11号=10号+11号, 12号=10号+11号+12号, 13号=10号+11号+12号+13号, 14号=11号+12号+13号+14号
pv5: 分组内当前行+往前3行+往后1行,如,14号=11号+12号+13号+14号+15号=5+7+3+2+4=21
pv6: 分组内当前行+往后所有行,如,13号=13号+14号+15号+16号=3+2+4+4=13,14号=14号+15号+16号=2+4+4=10
如果不指定ROWS BETWEEN,默认为从起点到当前行;
如果不指定ORDER BY,则将分组内所有值累加;
关键是理解ROWS BETWEEN含义,也叫做WINDOW子句:
PRECEDING:往前
FOLLOWING:往后
CURRENT ROW:当前行
UNBOUNDED:起点,UNBOUNDED PRECEDING 表示从前面的起点, UNBOUNDED FOLLOWING:表示到后面的终点
–其他AVG,MIN,MAX,和SUM用法一样。
--AVG
SELECT cookieid,createtime,pv,
AVG(pv) OVER(PARTITION BY cookieid ORDER BY createtime) AS pv1, -- 默认为从起点到当前行
AVG(pv) OVER(PARTITION BY cookieid ORDER BY createtime ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS pv2, --从起点到当前行,结果同pv1
AVG(pv) OVER(PARTITION BY cookieid) AS pv3,--分组内所有行
AVG(pv) OVER(PARTITION BY cookieid ORDER BY createtime ROWS BETWEEN 3 PRECEDING AND CURRENT ROW) AS pv4,--当前行+往前3行
AVG(pv) OVER(PARTITION BY cookieid ORDER BY createtime ROWS BETWEEN 3 PRECEDING AND 1 FOLLOWING) AS pv5,--当前行+往前3行+往后1行
AVG(pv) OVER(PARTITION BY cookieid ORDER BY createtime ROWS BETWEEN CURRENT ROW AND UNBOUNDED FOLLOWING) AS pv6 --当前行+往后所有行
FROM test_data order by cookieid,createtime;
+-----------+-------------+-----+---------------------+---------------------+---------------------+--------------------+--------------------+---------------------+--+
| cookieid | createtime | pv | pv1 | pv2 | pv3 | pv4 | pv5 | pv6 |
+-----------+-------------+-----+---------------------+---------------------+---------------------+--------------------+--------------------+---------------------+--+
| cookie1 | 2015-04-10 | 1 | 1.0 | 1.0 | 3.7142857142857144 | 1.0 | 3.0 | 3.7142857142857144 |
| cookie1 | 2015-04-11 | 5 | 3.0 | 3.0 | 3.7142857142857144 | 3.0 | 4.333333333333333 | 4.166666666666667 |
| cookie1 | 2015-04-12 | 7 | 4.333333333333333 | 4.333333333333333 | 3.7142857142857144 | 4.333333333333333 | 4.0 | 4.0 |
| cookie1 | 2015-04-13 | 3 | 4.0 | 4.0 | 3.7142857142857144 | 4.0 | 3.6 | 3.25 |
| cookie1 | 2015-04-14 | 2 | 3.6 | 3.6 | 3.7142857142857144 | 4.25 | 4.2 | 3.3333333333333335 |
| cookie1 | 2015-04-15 | 4 | 3.6666666666666665 | 3.6666666666666665 | 3.7142857142857144 | 4.0 | 4.0 | 4.0 |
| cookie1 | 2015-04-16 | 4 | 3.7142857142857144 | 3.7142857142857144 | 3.7142857142857144 | 3.25 | 3.25 | 4.0 |
| cookie2 | 2015-04-10 | 6 | 6.0 | 6.0 | 5.0 | 6.0 | 5.5 | 5.0 |
| cookie2 | 2015-04-11 | 5 | 5.5 | 5.5 | 5.0 | 5.5 | 6.0 | 4.833333333333333 |
| cookie2 | 2015-04-12 | 7 | 6.0 | 6.0 | 5.0 | 6.0 | 5.5 | 4.8 |
| cookie2 | 2015-04-13 | 4 | 5.5 | 5.5 | 5.0 | 5.5 | 5.0 | 4.25 |
| cookie2 | 2015-04-14 | 3 | 5.0 | 5.0 | 5.0 | 4.75 | 4.8 | 4.333333333333333 |
| cookie2 | 2015-04-15 | 5 | 5.0 | 5.0 | 5.0 | 4.75 | 4.8 | 5.0 |
| cookie2 | 2015-04-16 | 5 | 5.0 | 5.0 | 5.0 | 4.25 | 4.25 | 5.0 |
+-----------+-------------+-----+---------------------+---------------------+---------------------+--------------------+--------------------+---------------------+--+
--MIN
SELECT cookieid,createtime,pv,
MIN(pv) OVER(PARTITION BY cookieid ORDER BY createtime) AS pv1, -- 默认为从起点到当前行
MIN(pv) OVER(PARTITION BY cookieid ORDER BY createtime ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS pv2,--从起点到当前行,结果同pv1
MIN(pv) OVER(PARTITION BY cookieid) AS pv3,--分组内所有行
MIN(pv) OVER(PARTITION BY cookieid ORDER BY createtime ROWS BETWEEN 3 PRECEDING AND CURRENT ROW) AS pv4,--当前行+往前3行
MIN(pv) OVER(PARTITION BY cookieid ORDER BY createtime ROWS BETWEEN 3 PRECEDING AND 1 FOLLOWING) AS pv5,--当前行+往前3行+往后1行
MIN(pv) OVER(PARTITION BY cookieid ORDER BY createtime ROWS BETWEEN CURRENT ROW AND UNBOUNDED FOLLOWING) AS pv6 --当前行+往后所有行
FROM test_data order by cookieid,createtime;
+-----------+-------------+-----+------+------+------+------+------+------+--+
| cookieid | createtime | pv | pv1 | pv2 | pv3 | pv4 | pv5 | pv6 |
+-----------+-------------+-----+------+------+------+------+------+------+--+
| cookie1 | 2015-04-10 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| cookie1 | 2015-04-11 | 5 | 1 | 1 | 1 | 1 | 1 | 2 |
| cookie1 | 2015-04-12 | 7 | 1 | 1 | 1 | 1 | 1 | 2 |
| cookie1 | 2015-04-13 | 3 | 1 | 1 | 1 | 1 | 1 | 2 |
| cookie1 | 2015-04-14 | 2 | 1 | 1 | 1 | 2 | 2 | 2 |
| cookie1 | 2015-04-15 | 4 | 1 | 1 | 1 | 2 | 2 | 4 |
| cookie1 | 2015-04-16 | 4 | 1 | 1 | 1 | 2 | 2 | 4 |
| cookie2 | 2015-04-10 | 6 | 6 | 6 | 3 | 6 | 5 | 3 |
| cookie2 | 2015-04-11 | 5 | 5 | 5 | 3 | 5 | 5 | 3 |
| cookie2 | 2015-04-12 | 7 | 5 | 5 | 3 | 5 | 4 | 3 |
| cookie2 | 2015-04-13 | 4 | 4 | 4 | 3 | 4 | 3 | 3 |
| cookie2 | 2015-04-14 | 3 | 3 | 3 | 3 | 3 | 3 | 3 |
| cookie2 | 2015-04-15 | 5 | 3 | 3 | 3 | 3 | 3 | 5 |
| cookie2 | 2015-04-16 | 5 | 3 | 3 | 3 | 3 | 3 | 5 |
+-----------+-------------+-----+------+------+------+------+------+------+--+
--MAX
SELECT cookieid,createtime,pv,
MAX(pv) OVER(PARTITION BY cookieid ORDER BY createtime) AS pv1, -- 默认为从起点到当前行
MAX(pv) OVER(PARTITION BY cookieid ORDER BY createtime ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW) AS pv2, --从起点到当前行,结果同pv1
MAX(pv) OVER(PARTITION BY cookieid) AS pv3, --分组内所有行
MAX(pv) OVER(PARTITION BY cookieid ORDER BY createtime ROWS BETWEEN 3 PRECEDING AND CURRENT ROW) AS pv4, --当前行+往前3行
MAX(pv) OVER(PARTITION BY cookieid ORDER BY createtime ROWS BETWEEN 3 PRECEDING AND 1 FOLLOWING) AS pv5, --当前行+往前3行+往后1行
MAX(pv) OVER(PARTITION BY cookieid ORDER BY createtime ROWS BETWEEN CURRENT ROW AND UNBOUNDED FOLLOWING) AS pv6 --当前行+往后所有行
FROM test_data order by cookieid,createtime;
+-----------+-------------+-----+------+------+------+------+------+------+--+
| cookieid | createtime | pv | pv1 | pv2 | pv3 | pv4 | pv5 | pv6 |
+-----------+-------------+-----+------+------+------+------+------+------+--+
| cookie1 | 2015-04-10 | 1 | 1 | 1 | 7 | 1 | 5 | 7 |
| cookie1 | 2015-04-11 | 5 | 5 | 5 | 7 | 5 | 7 | 7 |
| cookie1 | 2015-04-12 | 7 | 7 | 7 | 7 | 7 | 7 | 7 |
| cookie1 | 2015-04-13 | 3 | 7 | 7 | 7 | 7 | 7 | 4 |
| cookie1 | 2015-04-14 | 2 | 7 | 7 | 7 | 7 | 7 | 4 |
| cookie1 | 2015-04-15 | 4 | 7 | 7 | 7 | 7 | 7 | 4 |
| cookie1 | 2015-04-16 | 4 | 7 | 7 | 7 | 4 | 4 | 4 |
| cookie2 | 2015-04-10 | 6 | 6 | 6 | 7 | 6 | 6 | 7 |
| cookie2 | 2015-04-11 | 5 | 6 | 6 | 7 | 6 | 7 | 7 |
| cookie2 | 2015-04-12 | 7 | 7 | 7 | 7 | 7 | 7 | 7 |
| cookie2 | 2015-04-13 | 4 | 7 | 7 | 7 | 7 | 7 | 5 |
| cookie2 | 2015-04-14 | 3 | 7 | 7 | 7 | 7 | 7 | 5 |
| cookie2 | 2015-04-15 | 5 | 7 | 7 | 7 | 7 | 7 | 5 |
| cookie2 | 2015-04-16 | 5 | 7 | 7 | 7 | 5 | 5 | 5 |
+-----------+-------------+-----+------+------+------+------+------+------+--+ SELECT cookieid,
createtime,
pv,
min(pv) OVER(PARTITION BY cookieid) AS min_pv,
max(pv) OVER(PARTITION BY cookieid) AS max_pv
FROM test_data;
+-----------+-------------+-----+---------+---------+--+
| cookieid | createtime | pv | min_pv | max_pv |
+-----------+-------------+-----+---------+---------+--+
| cookie1 | 2015-04-10 | 1 | 1 | 7 |
| cookie1 | 2015-04-16 | 4 | 1 | 7 |
| cookie1 | 2015-04-15 | 4 | 1 | 7 |
| cookie1 | 2015-04-14 | 2 | 1 | 7 |
| cookie1 | 2015-04-13 | 3 | 1 | 7 |
| cookie1 | 2015-04-12 | 7 | 1 | 7 |
| cookie1 | 2015-04-11 | 5 | 1 | 7 |
| cookie2 | 2015-04-16 | 5 | 3 | 7 |
| cookie2 | 2015-04-15 | 5 | 3 | 7 |
| cookie2 | 2015-04-14 | 3 | 3 | 7 |
| cookie2 | 2015-04-13 | 4 | 3 | 7 |
| cookie2 | 2015-04-12 | 7 | 3 | 7 |
| cookie2 | 2015-04-11 | 5 | 3 | 7 |
| cookie2 | 2015-04-10 | 6 | 3 | 7 |
+-----------+-------------+-----+---------+---------+--+
Hive函数:SUM,AVG,MIN,MAX的更多相关文章
- Hive分析窗口函数(一) SUM,AVG,MIN,MAX
Hive分析窗口函数(一) SUM,AVG,MIN,MAX Hive分析窗口函数(一) SUM,AVG,MIN,MAX Hive中提供了越来越多的分析函数,用于完成负责的统计分析.抽时间将所有的分析窗 ...
- Hive学习之路 (十三)Hive分析窗口函数(一) SUM,AVG,MIN,MAX
数据准备 数据格式 cookie1,, cookie1,, cookie1,, cookie1,, cookie1,, cookie1,, cookie1,, 创建数据库及表 create datab ...
- MybatisPlus Lambda表达式 聚合查询 分组查询 COUNT SUM AVG MIN MAX GroupBy
一.序言 众所周知,MybatisPlus在处理单表DAO操作时非常的方便.在处理多表连接连接查询也有优雅的解决方案.今天分享MybatisPlus基于Lambda表达式优雅实现聚合分组查询. 由于视 ...
- C# 中奇妙的函数–6. 五个序列聚合运算(Sum, Average, Min, Max,Aggregate)
今天,我们将着眼于五个用于序列的聚合运算.很多时候当我们在对序列进行操作时,我们想要做基于这些序列执行某种汇总然后,计算结果. Enumerable 静态类的LINQ扩展方法可以做到这一点 .就像之前 ...
- SQL模糊查询,sum,AVG,MAX,min函数
cmd mysql -hlocalhost -uroot -p select * from emp where ename like '___' -- 三个横线, - 代表字符,可以查询 三个enam ...
- 三、函数 (SUM、MIN、MAX、COUNT、AVG)
第八章 使用数据处理函数 8.1 函数 SQL支持利用函数来处理数据.函数一般是在数据上执行的,给数据的转换和处理提供了方便. 每一个DBMS都有特定的函数.只有少数几个函数被所有主要的DBMS等同的 ...
- LINQ to SQL Count/Sum/Min/Max/Avg Join
public class Linq { MXSICEDataContext Db = new MXSICEDataContext(); // LINQ to SQL // Count/Sum/Min/ ...
- LINQ to SQL 语句(3) 之 Count/Sum/Min/Max/Avg
LINQ to SQL 语句(3) 之 Count/Sum/Min/Max/Avg [1] Count/Sum 讲解 [2] Min 讲解 [3] Max 讲解 [4] Average 和 Agg ...
- [转]LINQ语句之Select/Distinct和Count/Sum/Min/Max/Avg
在讲述了LINQ,顺便说了一下Where操作,这篇开始我们继续说LINQ语句,目的让大家从语句的角度了解LINQ,LINQ包括LINQ to Objects.LINQ to DataSets.LINQ ...
随机推荐
- PHP MVC框架核心类
PHP MVC框架核心类 现在我们举几个核心框架的例子演示:在framework/core下建立一个Framework.class.php的文件.写入以下代码: // framework/core/F ...
- javaMail邮件发送功能(多收件人,多抄送人,多密送人,多附件)
private Session session; private Transport transport; private String mailHost = ""; privat ...
- 桶排序/基数排序(Radix Sort)
说基数排序之前,我们先说桶排序: 基本思想:是将阵列分到有限数量的桶子里.每个桶子再个别排序(有可能再使用别的排序算法或是以递回方式继续使用桶排序进行排序).桶排序是鸽巢排序的一种归纳结果.当要被排序 ...
- 用Canvas写一个简单的游戏--别踩白块儿
第一次写博客也不知怎么写,反正就按照我自己的想法来吧!怎么说呢?还是不要扯那些多余的话了,直接上正题吧! 第一次用canvas写游戏,所以挑个简单实现点的来干:别踩白块儿,其他那些怎么操作的那些就不用 ...
- nxlog4go 的配置驱动
刚开始接触log4go项目时,没有注意到配置的重要性. 阅读了log4j.log4net.log4cpp.log4cplus的部分代码,发现它们都是以xml配置来驱动日志系统运行的. 多个源文件共享一 ...
- .net core2.0下Ioc容器Autofac使用
.net core发布有一段时间了,最近两个月开始使用.net core2.0开发项目,大大小小遇到了一些问题.准备写个系列介绍一下是如何解决这些问题以及对应技术.先从IOC容器Autofac开始该系 ...
- 浅谈new/delete和malloc/free的用法与区别
每个程序在执行时都会占用一块可用的内存空间,用于存放动态分配的对象,此内存空间称为自由存储区或堆. 一.new和delete用法 如下几行代码: int *pi=new int; int *pi=ne ...
- 中文分词 sphni与scws
1.安装sphnixcd /usr/local/srcwget http://sphinxsearch.com/files/sphinx-2.2.11-release.tar.gztar -zxvf ...
- Linux中SVN的备份与恢复
linux中SVN备份有三种方式 1.svnadmin dump 是官方推荐的备份方式,优点是比较灵活,可以全量备份也可以增量备份,并提供版本恢复机制. 缺点是版本数过大,增长到数万以上,那么dump ...
- 动态控制jQuery easyui datagrid工具栏显示隐藏
//隐藏第一个按钮 $('div.datagrid-toolbar a').eq(0).hide(); //隐藏第一条分隔线 $('div.datagrid-toolbar div').eq(0).h ...