pig和mysql脚本对比

测试数据位于：/home/hadoop/luogankun/workspace/sync_data/pig

dept和emp表来源自oracle数据库自带的表

dept.txt

10      ACCOUNTING      NEW YORK

20      RESEARCH        DALLAS

30      SALES   CHICAGO

40      OPERATIONS      BOSTON

emp.txt

7369    SMITH   CLERK   7902    1980-12-17      800.00          20

7499    ALLEN   SALESMAN        7698    1981-2-20       1600.00 300.00  30

7521    WARD    SALESMAN        7698    1981-2-22       1250.00 500.00  30

7566    JONES   MANAGER 7839    1981-4-2        2975.00         20

7654    MARTIN  SALESMAN        7698    1981-9-28       1250.00 1400.00 30

7698    BLAKE   MANAGER 7839    1981-5-1        2850.00         30

7782    CLARK   MANAGER 7839    1981-6-9        2450.00         10

7788    SCOTT   ANALYST 7566    1987-4-19       3000.00         20

7839    KING    PRESIDENT               1981-11-17      5000.00         10

7844    TURNER  SALESMAN        7698    1981-9-8        1500.00 0.00    30

7876    ADAMS   CLERK   7788    1987-5-23       1100.00         20

7900    JAMES   CLERK   7698    1981-12-3       950.00          30

7902    FORD    ANALYST 7566    1981-12-3       3000.00         20

7934    MILLER  CLERK   7782    1982-1-23       1300.00         10

上传数据到HDFS系统中

cd /home/hadoop/luogankun/workspace/sync_data/pig

hadoop fs -put dept.txt input/pig/dept.txt

hadoop fs -put emp.txt input/pig/emp.txt

导入

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

dept= LOAD 'input/pig/dept.txt' USING PigStorage('\t') AS (deptno:int,dname:chararray,loc:chararray);

emp = LOAD 'input/pig/emp.txt' USING PigStorage('\t') AS (empno:int,ename:chararray, job:chararray, mgr:int, hiredate:chararray,sal:double,comm:double,dept:int);

查看表结构

desc TMP_TABLE;

describe dept

dept: {deptno: int,dname: chararray,loc: chararray}

describe emp

emp: {empno: int,ename: chararray,job: chararray,mgr: int,hiredate: chararray,sal: double,comm: double,dept: int}

查询整张表

SELECT * FROM TMP_TABLE;

DUMP dept

(10,ACCOUNTING,NEW YORK)

(20,RESEARCH,DALLAS)

(30,SALES,CHICAGO)

(40,OPERATIONS,BOSTON)

DUMP emp

(7369,SMITH,CLERK,7902,1980-12-17,800.0,,20)

(7499,ALLEN,SALESMAN,7698,1981-2-20,1600.0,300.0,30)

(7521,WARD,SALESMAN,7698,1981-2-22,1250.0,500.0,30)

(7566,JONES,MANAGER,7839,1981-4-2,2975.0,,20)

(7654,MARTIN,SALESMAN,7698,1981-9-28,1250.0,1400.0,30)

(7698,BLAKE,MANAGER,7839,1981-5-1,2850.0,,30)

(7782,CLARK,MANAGER,7839,1981-6-9,2450.0,,10)

(7788,SCOTT,ANALYST,7566,1987-4-19,3000.0,,20)

(7839,KING,PRESIDENT,,1981-11-17,5000.0,,10)

(7844,TURNER,SALESMAN,7698,1981-9-8,1500.0,0.0,30)

(7876,ADAMS,CLERK,7788,1987-5-23,1100.0,,20)

(7900,JAMES,CLERK,7698,1981-12-3,950.0,,30)

(7902,FORD,ANALYST,7566,1981-12-3,3000.0,,20)

(7934,MILLER,CLERK,7782,1982-1-23,1300.0,,10)

查询前N条

SELECT * FROM TMP_TABLE LIMIT 10;

emp_table_limit = LIMIT emp 10;

DUMP emp_table_limit;

(7369,SMITH,CLERK,7902,1980-12-17,800.0,,20)

(7499,ALLEN,SALESMAN,7698,1981-2-20,1600.0,300.0,30)

(7521,WARD,SALESMAN,7698,1981-2-22,1250.0,500.0,30)

(7566,JONES,MANAGER,7839,1981-4-2,2975.0,,20)

(7654,MARTIN,SALESMAN,7698,1981-9-28,1250.0,1400.0,30)

(7698,BLAKE,MANAGER,7839,1981-5-1,2850.0,,30)

(7782,CLARK,MANAGER,7839,1981-6-9,2450.0,,10)

(7788,SCOTT,ANALYST,7566,1987-4-19,3000.0,,20)

(7839,KING,PRESIDENT,,1981-11-17,5000.0,,10)

(7844,TURNER,SALESMAN,7698,1981-9-8,1500.0,0.0,30)

查询表中的某些列

SELECT USER FROM TMP_TABLE;

emp_table_empno_ename = FOREACH emp GENERATE empno, ename;

describe emp_table_empno_ename

emp_table_empno_ename: {empno: int,ename: chararray}

DUMP emp_table_empno_ename;

(7369,SMITH)

(7499,ALLEN)

(7521,WARD)

(7566,JONES)

(7654,MARTIN)

(7698,BLAKE)

(7782,CLARK)

(7788,SCOTT)

(7839,KING)

(7844,TURNER)

(7876,ADAMS)

(7900,JAMES)

(7902,FORD)

(7934,MILLER)

给列取别名

SELECT USER AS USER_NAME,AGE AS USER_AGE FROM TMP_TABLE;

emp_table_column_alias = FOREACH emp GENERATE empno AS id,ename AS name;

describe emp_table_column_alias

emp_table_column_alias: {id: int,name: chararray}

DUMP emp_table_column_alias

(7369,SMITH)

(7499,ALLEN)

(7521,WARD)

(7566,JONES)

(7654,MARTIN)

(7698,BLAKE)

(7782,CLARK)

(7788,SCOTT)

(7839,KING)

(7844,TURNER)

(7876,ADAMS)

(7900,JAMES)

(7902,FORD)

(7934,MILLER)

排序

SELECT * FROM TMP_TABLE ORDER BY AGE;

emp_table_order = ORDER emp BY empno ASC;

DUMP emp_table_order;

(7369,SMITH,CLERK,7902,1980-12-17,800.0,,20)

(7499,ALLEN,SALESMAN,7698,1981-2-20,1600.0,300.0,30)

(7521,WARD,SALESMAN,7698,1981-2-22,1250.0,500.0,30)

(7566,JONES,MANAGER,7839,1981-4-2,2975.0,,20)

(7654,MARTIN,SALESMAN,7698,1981-9-28,1250.0,1400.0,30)

(7698,BLAKE,MANAGER,7839,1981-5-1,2850.0,,30)

(7782,CLARK,MANAGER,7839,1981-6-9,2450.0,,10)

(7788,SCOTT,ANALYST,7566,1987-4-19,3000.0,,20)

(7839,KING,PRESIDENT,,1981-11-17,5000.0,,10)

(7844,TURNER,SALESMAN,7698,1981-9-8,1500.0,0.0,30)

(7876,ADAMS,CLERK,7788,1987-5-23,1100.0,,20)

(7900,JAMES,CLERK,7698,1981-12-3,950.0,,30)

(7902,FORD,ANALYST,7566,1981-12-3,3000.0,,20)

(7934,MILLER,CLERK,7782,1982-1-23,1300.0,,10)

条件查询

SELECT * FROM TMP_TABLE WHERE AGE>20;

emp_table_where = FILTER emp by sal > 1500;

DUMP emp_table_where;

(7499,ALLEN,SALESMAN,7698,1981-2-20,1600.0,300.0,30)

(7566,JONES,MANAGER,7839,1981-4-2,2975.0,,20)

(7698,BLAKE,MANAGER,7839,1981-5-1,2850.0,,30)

(7782,CLARK,MANAGER,7839,1981-6-9,2450.0,,10)

(7788,SCOTT,ANALYST,7566,1987-4-19,3000.0,,20)

(7839,KING,PRESIDENT,,1981-11-17,5000.0,,10)

(7902,FORD,ANALYST,7566,1981-12-3,3000.0,,20)

内连接Inner Join

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

emp_table_inner_join = JOIN emp BY dept,dept BY deptno;

describe emp_table_inner_join

emp_table_inner_join:

{emp::empno: int,emp::ename: chararray,emp::job: chararray,emp::mgr: int,

emp::hiredate: chararray,emp::sal: double,emp::comm: double,emp::dept: int,

dept::deptno: int,dept::dname: chararray,dept::loc: chararray}

DUMP emp_table_inner_join;

(7839,KING,PRESIDENT,,1981-11-17,5000.0,,10,10,ACCOUNTING,NEW YORK)

(7782,CLARK,MANAGER,7839,1981-6-9,2450.0,,10,10,ACCOUNTING,NEW YORK)

(7934,MILLER,CLERK,7782,1982-1-23,1300.0,,10,10,ACCOUNTING,NEW YORK)

(7369,SMITH,CLERK,7902,1980-12-17,800.0,,20,20,RESEARCH,DALLAS)

(7566,JONES,MANAGER,7839,1981-4-2,2975.0,,20,20,RESEARCH,DALLAS)

(7876,ADAMS,CLERK,7788,1987-5-23,1100.0,,20,20,RESEARCH,DALLAS)

(7902,FORD,ANALYST,7566,1981-12-3,3000.0,,20,20,RESEARCH,DALLAS)

(7788,SCOTT,ANALYST,7566,1987-4-19,3000.0,,20,20,RESEARCH,DALLAS)

(7499,ALLEN,SALESMAN,7698,1981-2-20,1600.0,300.0,30,30,SALES,CHICAGO)

(7844,TURNER,SALESMAN,7698,1981-9-8,1500.0,0.0,30,30,SALES,CHICAGO)

(7900,JAMES,CLERK,7698,1981-12-3,950.0,,30,30,SALES,CHICAGO)

(7698,BLAKE,MANAGER,7839,1981-5-1,2850.0,,30,30,SALES,CHICAGO)

(7654,MARTIN,SALESMAN,7698,1981-9-28,1250.0,1400.0,30,30,SALES,CHICAGO)

(7521,WARD,SALESMAN,7698,1981-2-22,1250.0,500.0,30,30,SALES,CHICAGO)

左连接Left Join

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

emp_table_left_join = JOIN emp BY dept LEFT OUTER,dept BY deptno;

describe emp_table_left_join

emp_table_left_join: {emp::empno: int,emp::ename: chararray,emp::job: chararray,emp::mgr: int,

emp::hiredate: chararray,emp::sal: double,emp::comm: double,emp::dept: int,

dept::deptno: int,dept::dname: chararray,dept::loc: chararray}

DUMP emp_table_left_join;

(7839,KING,PRESIDENT,,1981-11-17,5000.0,,10,10,ACCOUNTING,NEW YORK)

(7782,CLARK,MANAGER,7839,1981-6-9,2450.0,,10,10,ACCOUNTING,NEW YORK)

(7934,MILLER,CLERK,7782,1982-1-23,1300.0,,10,10,ACCOUNTING,NEW YORK)

(7369,SMITH,CLERK,7902,1980-12-17,800.0,,20,20,RESEARCH,DALLAS)

(7566,JONES,MANAGER,7839,1981-4-2,2975.0,,20,20,RESEARCH,DALLAS)

(7876,ADAMS,CLERK,7788,1987-5-23,1100.0,,20,20,RESEARCH,DALLAS)

(7902,FORD,ANALYST,7566,1981-12-3,3000.0,,20,20,RESEARCH,DALLAS)

(7788,SCOTT,ANALYST,7566,1987-4-19,3000.0,,20,20,RESEARCH,DALLAS)

(7499,ALLEN,SALESMAN,7698,1981-2-20,1600.0,300.0,30,30,SALES,CHICAGO)

(7844,TURNER,SALESMAN,7698,1981-9-8,1500.0,0.0,30,30,SALES,CHICAGO)

(7900,JAMES,CLERK,7698,1981-12-3,950.0,,30,30,SALES,CHICAGO)

(7698,BLAKE,MANAGER,7839,1981-5-1,2850.0,,30,30,SALES,CHICAGO)

(7654,MARTIN,SALESMAN,7698,1981-9-28,1250.0,1400.0,30,30,SALES,CHICAGO)

(7521,WARD,SALESMAN,7698,1981-2-22,1250.0,500.0,30,30,SALES,CHICAGO)

右连接Right Join

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

emp_table_right_join = JOIN emp BY dept RIGHT OUTER,dept BY deptno;

describe emp_table_right_join

emp_table_right_join: {emp::empno: int,emp::ename: chararray,emp::job: chararray,emp::mgr: int,

emp::hiredate: chararray,emp::sal: double,emp::comm: double,emp::dept: int,

dept::deptno: int,dept::dname: chararray,dept::loc: chararray}

DUMP emp_table_right_join;

(7839,KING,PRESIDENT,,1981-11-17,5000.0,,10,10,ACCOUNTING,NEW YORK)

(7782,CLARK,MANAGER,7839,1981-6-9,2450.0,,10,10,ACCOUNTING,NEW YORK)

(7934,MILLER,CLERK,7782,1982-1-23,1300.0,,10,10,ACCOUNTING,NEW YORK)

(7369,SMITH,CLERK,7902,1980-12-17,800.0,,20,20,RESEARCH,DALLAS)

(7566,JONES,MANAGER,7839,1981-4-2,2975.0,,20,20,RESEARCH,DALLAS)

(7876,ADAMS,CLERK,7788,1987-5-23,1100.0,,20,20,RESEARCH,DALLAS)

(7902,FORD,ANALYST,7566,1981-12-3,3000.0,,20,20,RESEARCH,DALLAS)

(7788,SCOTT,ANALYST,7566,1987-4-19,3000.0,,20,20,RESEARCH,DALLAS)

(7499,ALLEN,SALESMAN,7698,1981-2-20,1600.0,300.0,30,30,SALES,CHICAGO)

(7844,TURNER,SALESMAN,7698,1981-9-8,1500.0,0.0,30,30,SALES,CHICAGO)

(7900,JAMES,CLERK,7698,1981-12-3,950.0,,30,30,SALES,CHICAGO)

(7698,BLAKE,MANAGER,7839,1981-5-1,2850.0,,30,30,SALES,CHICAGO)

(7654,MARTIN,SALESMAN,7698,1981-9-28,1250.0,1400.0,30,30,SALES,CHICAGO)

(7521,WARD,SALESMAN,7698,1981-2-22,1250.0,500.0,30,30,SALES,CHICAGO)

(,,,,,,,,40,OPERATIONS,BOSTON)

全连接Full Join

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

emp_table_full_join = JOIN emp BY dept FULL OUTER,dept BY deptno;

describe emp_table_full_join

emp_table_full_join: {emp::empno: int,emp::ename: chararray,emp::job: chararray,emp::mgr: int,

emp::hiredate: chararray,emp::sal: double,emp::comm: double,emp::dept: int,

dept::deptno: int,dept::dname: chararray,dept::loc: chararray}

DUMP emp_table_full_join;

(7839,KING,PRESIDENT,,1981-11-17,5000.0,,10,10,ACCOUNTING,NEW YORK)

(7782,CLARK,MANAGER,7839,1981-6-9,2450.0,,10,10,ACCOUNTING,NEW YORK)

(7934,MILLER,CLERK,7782,1982-1-23,1300.0,,10,10,ACCOUNTING,NEW YORK)

(7369,SMITH,CLERK,7902,1980-12-17,800.0,,20,20,RESEARCH,DALLAS)

(7566,JONES,MANAGER,7839,1981-4-2,2975.0,,20,20,RESEARCH,DALLAS)

(7876,ADAMS,CLERK,7788,1987-5-23,1100.0,,20,20,RESEARCH,DALLAS)

(7902,FORD,ANALYST,7566,1981-12-3,3000.0,,20,20,RESEARCH,DALLAS)

(7788,SCOTT,ANALYST,7566,1987-4-19,3000.0,,20,20,RESEARCH,DALLAS)

(7499,ALLEN,SALESMAN,7698,1981-2-20,1600.0,300.0,30,30,SALES,CHICAGO)

(7844,TURNER,SALESMAN,7698,1981-9-8,1500.0,0.0,30,30,SALES,CHICAGO)

(7900,JAMES,CLERK,7698,1981-12-3,950.0,,30,30,SALES,CHICAGO)

(7698,BLAKE,MANAGER,7839,1981-5-1,2850.0,,30,30,SALES,CHICAGO)

(7654,MARTIN,SALESMAN,7698,1981-9-28,1250.0,1400.0,30,30,SALES,CHICAGO)

(7521,WARD,SALESMAN,7698,1981-2-22,1250.0,500.0,30,30,SALES,CHICAGO)

(,,,,,,,,40,OPERATIONS,BOSTON)

同时对多张表交叉查询

SELECT * FROM TMP_TABLE,TMP_TABLE_2;

emp_table_cross = CROSS emp,dept;

describe emp_table_cross

emp_table_cross: {emp::empno: int,emp::ename: chararray,emp::job: chararray,emp::mgr: int,

emp::hiredate: chararray,emp::sal: double,emp::comm: double,emp::dept: int,

dept::deptno: int,dept::dname: chararray,dept::loc: chararray}

DUMP emp_table_cross;

(7369,SMITH,CLERK,7902,1980-12-17,800.0,,20,10,ACCOUNTING,NEW YORK)

(7369,SMITH,CLERK,7902,1980-12-17,800.0,,20,20,RESEARCH,DALLAS)

(7369,SMITH,CLERK,7902,1980-12-17,800.0,,20,30,SALES,CHICAGO)

(7369,SMITH,CLERK,7902,1980-12-17,800.0,,20,40,OPERATIONS,BOSTON)

(7499,ALLEN,SALESMAN,7698,1981-2-20,1600.0,300.0,30,10,ACCOUNTING,NEW YORK)

(7499,ALLEN,SALESMAN,7698,1981-2-20,1600.0,300.0,30,20,RESEARCH,DALLAS)

(7499,ALLEN,SALESMAN,7698,1981-2-20,1600.0,300.0,30,30,SALES,CHICAGO)

(7499,ALLEN,SALESMAN,7698,1981-2-20,1600.0,300.0,30,40,OPERATIONS,BOSTON)

(7521,WARD,SALESMAN,7698,1981-2-22,1250.0,500.0,30,10,ACCOUNTING,NEW YORK)

(7521,WARD,SALESMAN,7698,1981-2-22,1250.0,500.0,30,20,RESEARCH,DALLAS)

(7521,WARD,SALESMAN,7698,1981-2-22,1250.0,500.0,30,30,SALES,CHICAGO)

(7521,WARD,SALESMAN,7698,1981-2-22,1250.0,500.0,30,40,OPERATIONS,BOSTON)

(7566,JONES,MANAGER,7839,1981-4-2,2975.0,,20,10,ACCOUNTING,NEW YORK)

(7566,JONES,MANAGER,7839,1981-4-2,2975.0,,20,20,RESEARCH,DALLAS)

(7566,JONES,MANAGER,7839,1981-4-2,2975.0,,20,30,SALES,CHICAGO)

(7566,JONES,MANAGER,7839,1981-4-2,2975.0,,20,40,OPERATIONS,BOSTON)

(7654,MARTIN,SALESMAN,7698,1981-9-28,1250.0,1400.0,30,10,ACCOUNTING,NEW YORK)

(7654,MARTIN,SALESMAN,7698,1981-9-28,1250.0,1400.0,30,20,RESEARCH,DALLAS)

(7654,MARTIN,SALESMAN,7698,1981-9-28,1250.0,1400.0,30,30,SALES,CHICAGO)

(7654,MARTIN,SALESMAN,7698,1981-9-28,1250.0,1400.0,30,40,OPERATIONS,BOSTON)

(7698,BLAKE,MANAGER,7839,1981-5-1,2850.0,,30,10,ACCOUNTING,NEW YORK)

(7698,BLAKE,MANAGER,7839,1981-5-1,2850.0,,30,20,RESEARCH,DALLAS)

(7698,BLAKE,MANAGER,7839,1981-5-1,2850.0,,30,30,SALES,CHICAGO)

(7698,BLAKE,MANAGER,7839,1981-5-1,2850.0,,30,40,OPERATIONS,BOSTON)

(7782,CLARK,MANAGER,7839,1981-6-9,2450.0,,10,10,ACCOUNTING,NEW YORK)

(7782,CLARK,MANAGER,7839,1981-6-9,2450.0,,10,20,RESEARCH,DALLAS)

(7782,CLARK,MANAGER,7839,1981-6-9,2450.0,,10,30,SALES,CHICAGO)

(7782,CLARK,MANAGER,7839,1981-6-9,2450.0,,10,40,OPERATIONS,BOSTON)

(7788,SCOTT,ANALYST,7566,1987-4-19,3000.0,,20,10,ACCOUNTING,NEW YORK)

(7788,SCOTT,ANALYST,7566,1987-4-19,3000.0,,20,20,RESEARCH,DALLAS)

(7788,SCOTT,ANALYST,7566,1987-4-19,3000.0,,20,30,SALES,CHICAGO)

(7788,SCOTT,ANALYST,7566,1987-4-19,3000.0,,20,40,OPERATIONS,BOSTON)

(7839,KING,PRESIDENT,,1981-11-17,5000.0,,10,10,ACCOUNTING,NEW YORK)

(7839,KING,PRESIDENT,,1981-11-17,5000.0,,10,20,RESEARCH,DALLAS)

(7839,KING,PRESIDENT,,1981-11-17,5000.0,,10,30,SALES,CHICAGO)

(7839,KING,PRESIDENT,,1981-11-17,5000.0,,10,40,OPERATIONS,BOSTON)

(7844,TURNER,SALESMAN,7698,1981-9-8,1500.0,0.0,30,10,ACCOUNTING,NEW YORK)

(7844,TURNER,SALESMAN,7698,1981-9-8,1500.0,0.0,30,20,RESEARCH,DALLAS)

(7844,TURNER,SALESMAN,7698,1981-9-8,1500.0,0.0,30,30,SALES,CHICAGO)

(7844,TURNER,SALESMAN,7698,1981-9-8,1500.0,0.0,30,40,OPERATIONS,BOSTON)

(7876,ADAMS,CLERK,7788,1987-5-23,1100.0,,20,10,ACCOUNTING,NEW YORK)

(7876,ADAMS,CLERK,7788,1987-5-23,1100.0,,20,20,RESEARCH,DALLAS)

(7876,ADAMS,CLERK,7788,1987-5-23,1100.0,,20,30,SALES,CHICAGO)

(7876,ADAMS,CLERK,7788,1987-5-23,1100.0,,20,40,OPERATIONS,BOSTON)

(7900,JAMES,CLERK,7698,1981-12-3,950.0,,30,10,ACCOUNTING,NEW YORK)

(7900,JAMES,CLERK,7698,1981-12-3,950.0,,30,20,RESEARCH,DALLAS)

(7900,JAMES,CLERK,7698,1981-12-3,950.0,,30,30,SALES,CHICAGO)

(7900,JAMES,CLERK,7698,1981-12-3,950.0,,30,40,OPERATIONS,BOSTON)

(7902,FORD,ANALYST,7566,1981-12-3,3000.0,,20,10,ACCOUNTING,NEW YORK)

(7902,FORD,ANALYST,7566,1981-12-3,3000.0,,20,20,RESEARCH,DALLAS)

(7902,FORD,ANALYST,7566,1981-12-3,3000.0,,20,30,SALES,CHICAGO)

(7902,FORD,ANALYST,7566,1981-12-3,3000.0,,20,40,OPERATIONS,BOSTON)

(7934,MILLER,CLERK,7782,1982-1-23,1300.0,,10,10,ACCOUNTING,NEW YORK)

(7934,MILLER,CLERK,7782,1982-1-23,1300.0,,10,20,RESEARCH,DALLAS)

(7934,MILLER,CLERK,7782,1982-1-23,1300.0,,10,30,SALES,CHICAGO)

(7934,MILLER,CLERK,7782,1982-1-23,1300.0,,10,40,OPERATIONS,BOSTON)

分组GROUP BY

SELECT * FROM TMP_TABLE GROUP BY IS_MALE;

emp_table_group = GROUP emp BY dept;

describe emp_table_group

emp_table_group: {

    group: int,

    emp: {

        (empno: int,ename: chararray,job: chararray,mgr: int,hiredate: chararray,sal: double, comm: double,dept: int)

    }

}

DUMP emp_table_group;

(10,{

    (7839,KING,PRESIDENT,,1981-11-17,5000.0,,10),

    (7782,CLARK,MANAGER,7839,1981-6-9,2450.0,,10),

    (7934,MILLER,CLERK,7782,1982-1-23,1300.0,,10)})

(20,{

    (7369,SMITH,CLERK,7902,1980-12-17,800.0,,20),

    (7566,JONES,MANAGER,7839,1981-4-2,2975.0,,20),

    (7876,ADAMS,CLERK,7788,1987-5-23,1100.0,,20),

    (7902,FORD,ANALYST,7566,1981-12-3,3000.0,,20),

    (7788,SCOTT,ANALYST,7566,1987-4-19,3000.0,,20)})

(30,{

    (7499,ALLEN,SALESMAN,7698,1981-2-20,1600.0,300.0,30),

    (7844,TURNER,SALESMAN,7698,1981-9-8,1500.0,0.0,30),

    (7900,JAMES,CLERK,7698,1981-12-3,950.0,,30),

    (7698,BLAKE,MANAGER,7839,1981-5-1,2850.0,,30),

    (7654,MARTIN,SALESMAN,7698,1981-9-28,1250.0,1400.0,30),

    (7521,WARD,SALESMAN,7698,1981-2-22,1250.0,500.0,30)})

分组并统计

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

emp_table_group_count = GROUP emp BY dept;

describe emp_table_group_count

emp_table_group_count: {

       group: int,

       emp: {

            (empno: int,ename: chararray,job: chararray,mgr: int,hiredate: chararray,sal: double,comm: double,dept: int

            )

       }

}

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

describe emp_table_group_count

DUMP emp_table_group_count;

(10,3)

(20,5)

(30,6)

emp_table_group_count = FOREACH emp_table_group_count GENERATE emp.dept,COUNT($1);

describe emp_table_group_count

emp_table_group_count: {{(dept: int)},long}

DUMP emp_table_group_count;

({(10),(10),(10)},3)

({(20),(20),(20),(20),(20)},5)

({(30),(30),(30),(30),(30),(30)},6)

去重DISTINCT

SELECT DISTINCT IS_MALE FROM TMP_TABLE;

emp_table_distinct = FOREACH emp GENERATE dept;

describe emp_table_distinct

emp_table_distinct: {dept: int}

emp_table_distinct = DISTINCT emp_table_distinct;

describe emp_table_distinct

emp_table_distinct: {dept: int}

DUMP  emp_table_distinct;

(10)

(20)

(30)

pig判空

select * from emp where comm is not null;

emp_table_where_null = FILTER emp by comm is not null;

DUMP emp_table_where_null;

(7499,ALLEN,SALESMAN,7698,1981-2-20,1600.0,300.0,30)

(7521,WARD,SALESMAN,7698,1981-2-22,1250.0,500.0,30)

(7654,MARTIN,SALESMAN,7698,1981-9-28,1250.0,1400.0,30)

(7844,TURNER,SALESMAN,7698,1981-9-8,1500.0,0.0,30)

pig和mysql脚本对比的更多相关文章

[原] KVM 环境下MySQL性能对比
KVM 环境下MySQL性能对比标签(空格分隔): Cloud2.0 [TOC] 测试目的对比MySQL在物理机和KVM环境下性能情况压测标准压测遵循单一变量原则,所有的对比都是只改变一个变量 ...
MongoDB（五）mongo语法和mysql语法对比学习
我们总是在对比中看到自己的优点和缺点,对于mongodb来说也是一样,对比学习让我们尽快的掌握关于mongodb的基础知识. mongodb与MySQL命令对比关系型数据库一般是由数据库(datab ...
mongodb与mysql命令对比
mongodb与mysql命令对比传统的关系数据库一般由数据库(database).表(table).记录(record)三个层次概念组成,MongoDB是由数据库(database).集合(col ...
cmd执行mssql脚本或者执行mysql脚本
private static int ExecuteMSSql(DbInfo db, string sqlPath) { Console.WriteLine("=============== ...
聚集索引、非聚集索引、聚集索引组织表、堆组织表、Mysql/PostgreSQL对比、联合主键/自增长、InnoDB/MyISAM（引擎方面另开一篇）
参考了多篇文章,分别记录,如下. 下面是第一篇的总结 http://www.jb51.net/article/76007.htm: 在MySQL中,InnoDB引擎表是(聚集)索引组织表(cluste ...
LoadRunner利用ODBC编写MySql脚本
最近做了几周的LoadRunner测试,有一些心得,记录下来,以便以后查找. LoadRunner测试数据库是模拟客户端去连接数据库服务器,因此,需要协议(或者说驱动的支持).LoadRunner本身 ...
数据市中心全省中国mysql脚本
1.查尔斯省 watermark/2/text/aHR0cDovL2Jsb2cuY3Nkbi5uZXQvd2h6aGFvY2hhbw==/font/5a6L5L2T/fontsize/400/fill ...
Rehat一键安装mysql脚本和备份数据库脚本
Rehat一键安装mysql脚本 ##说明:适用,Rehat 5 6 7 1.运行状态,运行成功输出mysql临时密码 2.代码如下 #!/bin/bash #获取系统信息 sudo cat /etc ...
MongoDB批量操作及与MySQL效率对比
本文主要通过批量与非批量对比操作的方式介绍MongoDB的bulkWrite()方法的使用.顺带与关系型数据库MySQL进行对比,比较这两种不同类型数据库的效率.如果只是想学习bulkWrite()的 ...

随机推荐

[LeetCode&Python] Problem 682. Baseball Game
You're now a baseball game point recorder. Given a list of strings, each string can be one of the 4 ...
Robot Framework 安装笔记
安装python 自行搜寻安装安装pip 进入python目录下的Scripts文件夹下,cmd,执行easy_install.exe pip 安装pywin32 pip install pywin ...
null 与 undefinded
null表示"没有对象",即该处不应该有值.典型用法是: (1) 作为函数的参数,表示该函数的参数不是对象. (2) 作为对象原型链的终点. Object.getPrototype ...
HDU1702：ACboy needs your help again!
ACboy needs your help again! Time Limit: 1000/1000 MS (Java/Others) Memory Limit: 32768/32768 K ( ...
Make menuconfig生成文件
1.当我们在执行make menuconfig这个命令时,一共涉及到了以下几个文件: Linux内核根目录下的scripts文件夹 arch/$ARCH/Kconfig文件.各层目录下的Kconfig ...
hasura-graphql 集成 pipelinedb 1.0.0
pipelinedb 1.0.0 已经是一个标准的pg 扩展了,同时以前的语法也有变动,但是集成进hasura-graphql 更方便了使用docker-compose 运行环境准备 docker ...
C# 使用oledb 方式连接本地或者远程oracel 数据库的方式
对于C# 进行oracle 数据库的开发来说使用oracle 提供的odp.net 方式是比较方便的,同时在性能以及兼容性也是比较好的但是,对于不打算使用的,那么该如何使用oledb 进行连接连接 ...
理解git
为了真正了解git,我们从底部.底层开始,了解git核心,知其然并知其所以然. 为什么要进行版本控制呢? 因为编写文件不可能一次到位,文件总是有不同的状态需要保存下来,方便以后出错回滚. git 是目 ...
Jmeter之JDBC
jdbc:mysql://ip:3306/test?useUnicode=true&characterEncoding=utf8&allowMultiQueries=true
JWT 基础教程
原文地址:JWT 基础教程博客地址:http://www.extlight.com 一.前言针对前后端分离的项目,大多是通过 token 进行身份认证来进行交互,今天将介绍一种简单的创建 toke ...

pig和mysql脚本对比

pig和mysql脚本对比的更多相关文章

随机推荐

热门专题