Home Database Mysql Tutorial Hive分析窗口函数(四) LAG,LEAD,FIRST_VALUE,LAST_VALUE

Hive分析窗口函数(四) LAG,LEAD,FIRST_VALUE,LAST_VALUE

Jun 07, 2016 pm 02:51 PM
first hive v function analyze window

1.LAG功能是什么? 2.LEAD与LAG功能有什么相的地方那个? 3.FIRST_VALUE与LAST_VALUE分别完成什么功能? 继续学习这四个分析函数。注意: 这几个函数不支持WINDOW子句。 Hive版本为 apache-hive-0.13.1 数据准备: 水电费 cookie1,2015-04-10 10:00:02,url2

1.LAG功能是什么?
2.LEAD与LAG功能有什么相似的地方那个?

3.FIRST_VALUE与LAST_VALUE分别完成什么功能?


继续学习这四个分析函数。 注意: 这几个函数不支持WINDOW子句。 Hive版本为 apache-hive-0.13.1 数据准备:

水电费

    cookie1,2015-04-10 10:00:02,url2
    cookie1,2015-04-10 10:00:00,url1
    cookie1,2015-04-10 10:03:04,1url3
    cookie1,2015-04-10 10:50:05,url6
    cookie1,2015-04-10 11:00:00,url7
    cookie1,2015-04-10 10:10:00,url4
    cookie1,2015-04-10 10:50:01,url5
    cookie2,2015-04-10 10:00:02,url22
    cookie2,2015-04-10 10:00:00,url11
    cookie2,2015-04-10 10:03:04,1url33
    cookie2,2015-04-10 10:50:05,url66
    cookie2,2015-04-10 11:00:00,url77
    cookie2,2015-04-10 10:10:00,url44
    cookie2,2015-04-10 10:50:01,url55

    CREATE EXTERNAL TABLE lxw1234 (
    cookieid string,
    createtime string,  --页面访问时间
    url STRING       --被访问页面
    ) ROW FORMAT DELIMITED
    FIELDS TERMINATED BY ','
    stored as textfile location '/tmp/lxw11/';


    hive> select * from lxw1234;
    OK
    cookie1 2015-04-10 10:00:02     url2
    cookie1 2015-04-10 10:00:00     url1
    cookie1 2015-04-10 10:03:04     1url3
    cookie1 2015-04-10 10:50:05     url6
    cookie1 2015-04-10 11:00:00     url7
    cookie1 2015-04-10 10:10:00     url4
    cookie1 2015-04-10 10:50:01     url5
    cookie2 2015-04-10 10:00:02     url22
    cookie2 2015-04-10 10:00:00     url11
    cookie2 2015-04-10 10:03:04     1url33
    cookie2 2015-04-10 10:50:05     url66
    cookie2 2015-04-10 11:00:00     url77
    cookie2 2015-04-10 10:10:00     url44
    cookie2 2015-04-10 10:50:01     url55
Copy after login
LAG

LAG(col,n,DEFAULT) 用于统计窗口内往上第n行值
第一个参数为列名,第二个参数为往上第n行(可选,默认为1),第三个参数为默认值(当往上第n行为NULL时候,取默认值,如不指定,则为NULL)

    SELECT cookieid,
    createtime,
    url,
    ROW_NUMBER() OVER(PARTITION BY cookieid ORDER BY createtime) AS rn,
    LAG(createtime,1,'1970-01-01 00:00:00') OVER(PARTITION BY cookieid ORDER BY createtime) AS last_1_time,
    LAG(createtime,2) OVER(PARTITION BY cookieid ORDER BY createtime) AS last_2_time
    FROM lxw1234;


    cookieid createtime             url    rn       last_1_time             last_2_time
    -------------------------------------------------------------------------------------------
    cookie1 2015-04-10 10:00:00     url1    1       1970-01-01 00:00:00     NULL
    cookie1 2015-04-10 10:00:02     url2    2       2015-04-10 10:00:00     NULL
    cookie1 2015-04-10 10:03:04     1url3   3       2015-04-10 10:00:02     2015-04-10 10:00:00
    cookie1 2015-04-10 10:10:00     url4    4       2015-04-10 10:03:04     2015-04-10 10:00:02
    cookie1 2015-04-10 10:50:01     url5    5       2015-04-10 10:10:00     2015-04-10 10:03:04
    cookie1 2015-04-10 10:50:05     url6    6       2015-04-10 10:50:01     2015-04-10 10:10:00
    cookie1 2015-04-10 11:00:00     url7    7       2015-04-10 10:50:05     2015-04-10 10:50:01
    cookie2 2015-04-10 10:00:00     url11   1       1970-01-01 00:00:00     NULL
    cookie2 2015-04-10 10:00:02     url22   2       2015-04-10 10:00:00     NULL
    cookie2 2015-04-10 10:03:04     1url33  3       2015-04-10 10:00:02     2015-04-10 10:00:00
    cookie2 2015-04-10 10:10:00     url44   4       2015-04-10 10:03:04     2015-04-10 10:00:02
    cookie2 2015-04-10 10:50:01     url55   5       2015-04-10 10:10:00     2015-04-10 10:03:04
    cookie2 2015-04-10 10:50:05     url66   6       2015-04-10 10:50:01     2015-04-10 10:10:00
    cookie2 2015-04-10 11:00:00     url77   7       2015-04-10 10:50:05     2015-04-10 10:50:01


    last_1_time: 指定了往上第1行的值,default为'1970-01-01 00:00:00'  
                 cookie1第一行,往上1行为NULL,因此取默认值 1970-01-01 00:00:00
                 cookie1第三行,往上1行值为第二行值,2015-04-10 10:00:02
                 cookie1第六行,往上1行值为第五行值,2015-04-10 10:50:01
    last_2_time: 指定了往上第2行的值,为指定默认值
                                                     cookie1第一行,往上2行为NULL
                                                     cookie1第二行,往上2行为NULL
                                                     cookie1第四行,往上2行为第二行值,2015-04-10 10:00:02
                                                     cookie1第七行,往上2行为第五行值,2015-04-10 10:50:01
Copy after login

LEAD

与LAG相反
LEAD(col,n,DEFAULT) 用于统计窗口内往下第n行值
第一个参数为列名,第二个参数为往下第n行(可选,默认为1),第三个参数为默认值(当往下第n行为NULL时候,取默认值,如不指定,则为NULL)

    SELECT cookieid,
    createtime,
    url,
    ROW_NUMBER() OVER(PARTITION BY cookieid ORDER BY createtime) AS rn,
    LEAD(createtime,1,'1970-01-01 00:00:00') OVER(PARTITION BY cookieid ORDER BY createtime) AS next_1_time,
    LEAD(createtime,2) OVER(PARTITION BY cookieid ORDER BY createtime) AS next_2_time
    FROM lxw1234;


    cookieid createtime             url    rn       next_1_time             next_2_time
    -------------------------------------------------------------------------------------------
    cookie1 2015-04-10 10:00:00     url1    1       2015-04-10 10:00:02     2015-04-10 10:03:04
    cookie1 2015-04-10 10:00:02     url2    2       2015-04-10 10:03:04     2015-04-10 10:10:00
    cookie1 2015-04-10 10:03:04     1url3   3       2015-04-10 10:10:00     2015-04-10 10:50:01
    cookie1 2015-04-10 10:10:00     url4    4       2015-04-10 10:50:01     2015-04-10 10:50:05
    cookie1 2015-04-10 10:50:01     url5    5       2015-04-10 10:50:05     2015-04-10 11:00:00
    cookie1 2015-04-10 10:50:05     url6    6       2015-04-10 11:00:00     NULL
    cookie1 2015-04-10 11:00:00     url7    7       1970-01-01 00:00:00     NULL
    cookie2 2015-04-10 10:00:00     url11   1       2015-04-10 10:00:02     2015-04-10 10:03:04
    cookie2 2015-04-10 10:00:02     url22   2       2015-04-10 10:03:04     2015-04-10 10:10:00
    cookie2 2015-04-10 10:03:04     1url33  3       2015-04-10 10:10:00     2015-04-10 10:50:01
    cookie2 2015-04-10 10:10:00     url44   4       2015-04-10 10:50:01     2015-04-10 10:50:05
    cookie2 2015-04-10 10:50:01     url55   5       2015-04-10 10:50:05     2015-04-10 11:00:00
    cookie2 2015-04-10 10:50:05     url66   6       2015-04-10 11:00:00     NULL
    cookie2 2015-04-10 11:00:00     url77   7       1970-01-01 00:00:00     NULL

    --逻辑与LAG一样,只不过LAG是往上,LEAD是往下。
Copy after login

FIRST_VALUE

取分组内排序后,截止到当前行,第一个值

    SELECT cookieid,
    createtime,
    url,
    ROW_NUMBER() OVER(PARTITION BY cookieid ORDER BY createtime) AS rn,
    FIRST_VALUE(url) OVER(PARTITION BY cookieid ORDER BY createtime) AS first1
    FROM lxw1234;

    cookieid  createtime            url     rn      first1
    ---------------------------------------------------------
    cookie1 2015-04-10 10:00:00     url1    1       url1
    cookie1 2015-04-10 10:00:02     url2    2       url1
    cookie1 2015-04-10 10:03:04     1url3   3       url1
    cookie1 2015-04-10 10:10:00     url4    4       url1
    cookie1 2015-04-10 10:50:01     url5    5       url1
    cookie1 2015-04-10 10:50:05     url6    6       url1
    cookie1 2015-04-10 11:00:00     url7    7       url1
    cookie2 2015-04-10 10:00:00     url11   1       url11
    cookie2 2015-04-10 10:00:02     url22   2       url11
    cookie2 2015-04-10 10:03:04     1url33  3       url11
    cookie2 2015-04-10 10:10:00     url44   4       url11
    cookie2 2015-04-10 10:50:01     url55   5       url11
    cookie2 2015-04-10 10:50:05     url66   6       url11
    cookie2 2015-04-10 11:00:00     url77   7       url11
Copy after login

LAST_VALUE

取分组内排序后,截止到当前行,最后一个值


    SELECT cookieid,
    createtime,
    url,
    ROW_NUMBER() OVER(PARTITION BY cookieid ORDER BY createtime) AS rn,
    LAST_VALUE(url) OVER(PARTITION BY cookieid ORDER BY createtime) AS last1
    FROM lxw1234;


    cookieid  createtime            url    rn       last1  
    -----------------------------------------------------------------
    cookie1 2015-04-10 10:00:00     url1    1       url1
    cookie1 2015-04-10 10:00:02     url2    2       url2
    cookie1 2015-04-10 10:03:04     1url3   3       1url3
    cookie1 2015-04-10 10:10:00     url4    4       url4
    cookie1 2015-04-10 10:50:01     url5    5       url5
    cookie1 2015-04-10 10:50:05     url6    6       url6
    cookie1 2015-04-10 11:00:00     url7    7       url7
    cookie2 2015-04-10 10:00:00     url11   1       url11
    cookie2 2015-04-10 10:00:02     url22   2       url22
    cookie2 2015-04-10 10:03:04     1url33  3       1url33
    cookie2 2015-04-10 10:10:00     url44   4       url44
    cookie2 2015-04-10 10:50:01     url55   5       url55
    cookie2 2015-04-10 10:50:05     url66   6       url66
    cookie2 2015-04-10 11:00:00     url77   7       url77
Copy after login

如果不指定ORDER BY,则默认按照记录在文件中的偏移量进行排序,会出现错误的结果

    SELECT cookieid,
    createtime,
    url,
    FIRST_VALUE(url) OVER(PARTITION BY cookieid) AS first2  
    FROM lxw1234;

    cookieid  createtime            url     first2
    ----------------------------------------------
    cookie1 2015-04-10 10:00:02     url2    url2
    cookie1 2015-04-10 10:00:00     url1    url2
    cookie1 2015-04-10 10:03:04     1url3   url2
    cookie1 2015-04-10 10:50:05     url6    url2
    cookie1 2015-04-10 11:00:00     url7    url2
    cookie1 2015-04-10 10:10:00     url4    url2
    cookie1 2015-04-10 10:50:01     url5    url2
    cookie2 2015-04-10 10:00:02     url22   url22
    cookie2 2015-04-10 10:00:00     url11   url22
    cookie2 2015-04-10 10:03:04     1url33  url22
    cookie2 2015-04-10 10:50:05     url66   url22
    cookie2 2015-04-10 11:00:00     url77   url22
    cookie2 2015-04-10 10:10:00     url44   url22
    cookie2 2015-04-10 10:50:01     url55   url22

    SELECT cookieid,
    createtime,
    url,
    LAST_VALUE(url) OVER(PARTITION BY cookieid) AS last2  
    FROM lxw1234;

    cookieid  createtime            url     last2
    ----------------------------------------------
    cookie1 2015-04-10 10:00:02     url2    url5
    cookie1 2015-04-10 10:00:00     url1    url5
    cookie1 2015-04-10 10:03:04     1url3   url5
    cookie1 2015-04-10 10:50:05     url6    url5
    cookie1 2015-04-10 11:00:00     url7    url5
    cookie1 2015-04-10 10:10:00     url4    url5
    cookie1 2015-04-10 10:50:01     url5    url5
    cookie2 2015-04-10 10:00:02     url22   url55
    cookie2 2015-04-10 10:00:00     url11   url55
    cookie2 2015-04-10 10:03:04     1url33  url55
    cookie2 2015-04-10 10:50:05     url66   url55
    cookie2 2015-04-10 11:00:00     url77   url55
    cookie2 2015-04-10 10:10:00     url44   url55
    cookie2 2015-04-10 10:50:01     url55   url55
Copy after login

如果想要取分组内排序后最后一个值,则需要变通一下:

    SELECT cookieid,
    createtime,
    url,
    ROW_NUMBER() OVER(PARTITION BY cookieid ORDER BY createtime) AS rn,
    LAST_VALUE(url) OVER(PARTITION BY cookieid ORDER BY createtime) AS last1,
    FIRST_VALUE(url) OVER(PARTITION BY cookieid ORDER BY createtime DESC) AS last2
    FROM lxw1234
    ORDER BY cookieid,createtime;

    cookieid  createtime            url     rn     last1    last2
    -------------------------------------------------------------
    cookie1 2015-04-10 10:00:00     url1    1       url1    url7
    cookie1 2015-04-10 10:00:02     url2    2       url2    url7
    cookie1 2015-04-10 10:03:04     1url3   3       1url3   url7
    cookie1 2015-04-10 10:10:00     url4    4       url4    url7
    cookie1 2015-04-10 10:50:01     url5    5       url5    url7
    cookie1 2015-04-10 10:50:05     url6    6       url6    url7
    cookie1 2015-04-10 11:00:00     url7    7       url7    url7
    cookie2 2015-04-10 10:00:00     url11   1       url11   url77
    cookie2 2015-04-10 10:00:02     url22   2       url22   url77
    cookie2 2015-04-10 10:03:04     1url33  3       1url33  url77
    cookie2 2015-04-10 10:10:00     url44   4       url44   url77
    cookie2 2015-04-10 10:50:01     url55   5       url55   url77
    cookie2 2015-04-10 10:50:05     url66   6       url66   url77
    cookie2 2015-04-10 11:00:00     url77   7       url77   url77
Copy after login



Statement of this Website
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

Video Face Swap

Video Face Swap

Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Tools

Notepad++7.3.1

Notepad++7.3.1

Easy-to-use and free code editor

SublimeText3 Chinese version

SublimeText3 Chinese version

Chinese version, very easy to use

Zend Studio 13.0.1

Zend Studio 13.0.1

Powerful PHP integrated development environment

Dreamweaver CS6

Dreamweaver CS6

Visual web development tools

SublimeText3 Mac version

SublimeText3 Mac version

God-level code editing software (SublimeText3)

Tips for dynamically creating new functions in golang functions Tips for dynamically creating new functions in golang functions Apr 25, 2024 pm 02:39 PM

Go language provides two dynamic function creation technologies: closure and reflection. closures allow access to variables within the closure scope, and reflection can create new functions using the FuncOf function. These technologies are useful in customizing HTTP routers, implementing highly customizable systems, and building pluggable components.

Considerations for parameter order in C++ function naming Considerations for parameter order in C++ function naming Apr 24, 2024 pm 04:21 PM

In C++ function naming, it is crucial to consider parameter order to improve readability, reduce errors, and facilitate refactoring. Common parameter order conventions include: action-object, object-action, semantic meaning, and standard library compliance. The optimal order depends on the purpose of the function, parameter types, potential confusion, and language conventions.

How to write efficient and maintainable functions in Java? How to write efficient and maintainable functions in Java? Apr 24, 2024 am 11:33 AM

The key to writing efficient and maintainable Java functions is: keep it simple. Use meaningful naming. Handle special situations. Use appropriate visibility.

Complete collection of excel function formulas Complete collection of excel function formulas May 07, 2024 pm 12:04 PM

1. The SUM function is used to sum the numbers in a column or a group of cells, for example: =SUM(A1:J10). 2. The AVERAGE function is used to calculate the average of the numbers in a column or a group of cells, for example: =AVERAGE(A1:A10). 3. COUNT function, used to count the number of numbers or text in a column or a group of cells, for example: =COUNT(A1:A10) 4. IF function, used to make logical judgments based on specified conditions and return the corresponding result.

Comparison of the advantages and disadvantages of C++ function default parameters and variable parameters Comparison of the advantages and disadvantages of C++ function default parameters and variable parameters Apr 21, 2024 am 10:21 AM

The advantages of default parameters in C++ functions include simplifying calls, enhancing readability, and avoiding errors. The disadvantages are limited flexibility and naming restrictions. Advantages of variadic parameters include unlimited flexibility and dynamic binding. Disadvantages include greater complexity, implicit type conversions, and difficulty in debugging.

What are the benefits of C++ functions returning reference types? What are the benefits of C++ functions returning reference types? Apr 20, 2024 pm 09:12 PM

The benefits of functions returning reference types in C++ include: Performance improvements: Passing by reference avoids object copying, thus saving memory and time. Direct modification: The caller can directly modify the returned reference object without reassigning it. Code simplicity: Passing by reference simplifies the code and requires no additional assignment operations.

What is the difference between custom PHP functions and predefined functions? What is the difference between custom PHP functions and predefined functions? Apr 22, 2024 pm 02:21 PM

The difference between custom PHP functions and predefined functions is: Scope: Custom functions are limited to the scope of their definition, while predefined functions are accessible throughout the script. How to define: Custom functions are defined using the function keyword, while predefined functions are defined by the PHP kernel. Parameter passing: Custom functions receive parameters, while predefined functions may not require parameters. Extensibility: Custom functions can be created as needed, while predefined functions are built-in and cannot be modified.

C++ Function Exception Advanced: Customized Error Handling C++ Function Exception Advanced: Customized Error Handling May 01, 2024 pm 06:39 PM

Exception handling in C++ can be enhanced through custom exception classes that provide specific error messages, contextual information, and perform custom actions based on the error type. Define an exception class inherited from std::exception to provide specific error information. Use the throw keyword to throw a custom exception. Use dynamic_cast in a try-catch block to convert the caught exception to a custom exception type. In the actual case, the open_file function throws a FileNotFoundException exception. Catching and handling the exception can provide a more specific error message.

See all articles