pig中各种sql语句的实现
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:
- zhangsan 23 1
- lisi 24 1
- wangmazi 30 1
- meinv 18 0
- dama 55 0
tmp_file_2:
- 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);
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;