pig中各种sql语句的实现

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Pig是一个基于Hadoop的大规模数据分析平台，它提供的SQL-LIKE语言叫Pig
Latin，该语言的编译器会把类SQL的数据分析请求转换为一系列经过优化处理的MapReduce运算。使用pig可以在处理海量数据时达到事半功倍的效果，比使用Java，C++等语言编写大规模数据处理程序的难度要小N倍，实现同样的效果的代码量也小N倍。我们可以在不熟悉map/reduce的情况下使用类似与sql语句的pig
latin语句来实现复杂的数据处理。

我这里以Mysql 5.1.x为例,Pig的版本是0.8

同时我将数据放在了两个文件,存放在/tmp/data_file_1和/tmp/data_file_2中.文件内容如下:

tmp_file_1:

Txt代码

zhangsan 23 1

lisi 24 1

wangmazi 30 1

meinv 18 0

dama 55 0

tmp_file_2:

Txt代码

1 a

23 bb

50 ccc

30 dddd

66 eeeee

1.从文件导入数据

1)Mysql (Mysql需要先创建表).

CREATE TABLE TMP_TABLE(USER VARCHAR(32),AGE INT,IS_MALE BOOLEAN);

CREATE TABLE TMP_TABLE_2(AGE INT,OPTIONS VARCHAR(50)); -- 用于Join

LOAD DATA LOCAL INFILE '/tmp/data_file_1' INTO TABLE TMP_TABLE ;

LOAD DATA LOCAL INFILE '/tmp/data_file_2' INTO TABLE TMP_TABLE_2;

2)Pig

tmp_table = LOAD '/tmp/data_file_1' USING PigStorage('\t') AS (user:chararray, age:int,is_male:int);

tmp_table_2= LOAD '/tmp/data_file_2' USING PigStorage('\t') AS (age:int,options:chararray);

2.查询整张表

1)Mysql

SELECT * FROM TMP_TABLE;

2)Pig

DUMP tmp_table;

3. 查询前50行

1)Mysql

SELECT * FROM TMP_TABLE LIMIT 50;

2)Pig

tmp_table_limit = LIMIT tmp_table 50;

DUMP tmp_table_limit;

4.查询某些列

1)Mysql

SELECT USER FROM TMP_TABLE;

2)Pig

tmp_table_user = FOREACH tmp_table GENERATE user;

DUMP tmp_table_user;

5. 给列取别名

1)Mysql

SELECT USER AS USER_NAME,AGE AS USER_AGE FROM TMP_TABLE;

2)Pig

tmp_table_column_alias = FOREACH tmp_table GENERATE user AS user_name,age AS user_age;

DUMP tmp_table_column_alias;

6.排序

1)Mysql

SELECT * FROM TMP_TABLE ORDER BY AGE;

2)Pig

tmp_table_order = ORDER tmp_table BY age ASC;

DUMP tmp_table_order;

7.条件查询

1）Mysql

SELECT * FROM TMP_TABLE WHERE AGE>20;

2) Pig

tmp_table_where = FILTER tmp_table by age > 20;

DUMP tmp_table_where;

8.内连接Inner Join

1)Mysql

SELECT * FROM TMP_TABLE A JOIN TMP_TABLE_2 B ON A.AGE=B.AGE;

2)Pig

tmp_table_inner_join = JOIN tmp_table BY age,tmp_table_2 BY age;

DUMP tmp_table_inner_join;

9.左连接Left Join

1)Mysql

SELECT * FROM TMP_TABLE A LEFT JOIN TMP_TABLE_2 B ON A.AGE=B.AGE;

2)Pig

tmp_table_left_join = JOIN tmp_table BY age LEFT OUTER,tmp_table_2 BY age;

DUMP tmp_table_left_join;

10.右连接Right Join

1)Mysql

SELECT * FROM TMP_TABLE A RIGHT JOIN TMP_TABLE_2 B ON A.AGE=B.AGE;

2)Pig

tmp_table_right_join = JOIN tmp_table BY age RIGHT OUTER,tmp_table_2 BY age;

DUMP tmp_table_right_join;

11.全连接Full Join

1)Mysql

SELECT * FROM TMP_TABLE A JOIN TMP_TABLE_2 B ON A.AGE=B.AGE

UNION SELECT * FROM TMP_TABLE A LEFT JOIN TMP_TABLE_2 B ON A.AGE=B.AGE

UNION SELECT * FROM TMP_TABLE A RIGHT JOIN TMP_TABLE_2 B ON A.AGE=B.AGE;

2)Pig

tmp_table_full_join = JOIN tmp_table BY age FULL OUTER,tmp_table_2 BY age;

DUMP tmp_table_full_join;

12.同时对多张表交叉查询

1)Mysql

SELECT * FROM TMP_TABLE,TMP_TABLE_2;

2)Pig

tmp_table_cross = CROSS tmp_table,tmp_table_2;

DUMP tmp_table_cross;

13.分组GROUP BY

1)Mysql

SELECT * FROM TMP_TABLE GROUP BY IS_MALE;

2)Pig

tmp_table_group = GROUP tmp_table BY is_male;

DUMP tmp_table_group;

14.分组并统计

1)Mysql

SELECT IS_MALE,COUNT(*) FROM TMP_TABLE GROUP BY IS_MALE;

2)Pig

tmp_table_group_count = GROUP tmp_table BY is_male;

tmp_table_group_count = FOREACH tmp_table_group_count GENERATE group,COUNT($1);

DUMP tmp_table_group_count;

15.查询去重DISTINCT

1)MYSQL

SELECT DISTINCT IS_MALE FROM TMP_TABLE;

2)Pig

tmp_table_distinct = FOREACH tmp_table GENERATE is_male;

tmp_table_distinct = DISTINCT tmp_table_distinct;

DUMP tmp_table_distinct;