Home Database Mysql Tutorial Hive与Oracle表关联语句对比

Hive与Oracle表关联语句对比

Jun 07, 2016 pm 04:48 PM

在将ORACLE存储过程迁移到HIVE平台时,不可避免地会遇到表关联的相应语法问题。本文详细对比了ORALCE和HIVE的各种表关联语法,包

在将Oracle存储过程迁移到HIVE平台时,不可避免地会遇到表关联的相应语法问题。

本文详细对比了ORALCE和HIVE的各种表关联语法,,包括内关联,左,右关联,全外关联和笛卡尔积。

一.创建表

ORACLE:

create table a
(
a1  number(10),
a2 varchar2(50)
);

create table b
(
b1  number(10),
b2 varchar2(50)
);

HIVE:

CREATE TABLE IF NOT EXISTS a (
a1 STRING,
a2 STRING)
COMMENT 'TABLE A'
ROW FORMAT DELIMITED
FIELDS TERMINATED BY '|'
LINES TERMINATED BY '\n'
STORED AS TEXTFILE
TBLPROPERTIES ( 'created_at'='2014-04-28','creator'='HENRY' );

二.插入数据

ORACLE:

insert into a(a1,a2) values(1,'X');
insert into a(a1,a2) values(2,'Y');
insert into a(a1,a2) values(3,'Z');

insert into b(b1,b2) values(1,'X');
insert into b(b1,b2) values(2,'Y');
insert into b(b1,b2) values(4,'Z');

HIVE:

hive (default)> load data local inpath './data1' into table a;
Copying data from file:/home/Hadoop/roger/sql/renguihe/data
Copying file: file:/home/hadoop/roger/sql/renguihe/data
Loading data to table default.a
Table default.a stats: [num_partitions: 0, num_files: 1, num_rows: 0, total_size: 12, raw_data_size: 0]
OK
Time taken: 1.961 seconds
hive (default)> load data local inpath './data1' into table b;
Copying data from file:/home/hadoop/roger/sql/renguihe/data
Copying file: file:/home/hadoop/roger/sql/renguihe/data
Loading data to table default.b
Table default.b stats: [num_partitions: 0, num_files: 1, num_rows: 0, total_size: 12, raw_data_size: 0]
OK
Time taken: 0.392 seconds

其中data1数据文件内容为:

1|X
2|Y
3|Z

data2数据文件内容为:

1|X
2|Y
4|Z

三.等值关联

ORACLE:

select * from a,b where a.a1 = b.b1;

或:

select * from a join b on a.a1 = b.b1;

结果如下图所示:

 

HIVE:

select * from a join b on a.a1 = b.b1;

注意HIVE中不能使用where来表示关联条件。

执行过程及结果如下图所示:

hive (default)> select * from a join b on a.a1 = b.b1;       
Total MapReduce jobs = 1
setting HADOOP_USER_NAME        hadoop
Execution log at: /tmp/hadoop/.log
2014-04-29 09:13:27    Starting to launch local task to process map join;      maximum memory = 1908932608
2014-04-29 09:13:27    Processing rows:        3      Hashtable size: 3      Memory usage:  110981704      rate:  0.058
2014-04-29 09:13:27    Dump the hashtable into file: file:/tmp/hadoop/hive_2014-04-29_09-13-25_273_8486588204512196396/-local-10002/HashTable-Stage-3/MapJoin-mapfile00--.hashtable
2014-04-29 09:13:27    Upload 1 File to: file:/tmp/hadoop/hive_2014-04-29_09-13-25_273_8486588204512196396/-local-10002/HashTable-Stage-3/MapJoin-mapfile00--.hashtable File size: 438
2014-04-29 09:13:27    End of local task; Time Taken: 0.339 sec.
Execution completed successfully
Mapred Local Task Succeeded . Convert the Join into MapJoin
Mapred Local Task Succeeded . Convert the Join into MapJoin
Launching Job 1 out of 1
Number of reduce tasks is set to 0 since there's no reduce operator
Starting Job = job_201404251509_0131, Tracking URL = IP:50030/jobdetails.jsp?jobid=job_201404251509_0131
Kill
Command = /home/hadoop/package/hadoop-1.0.4/libexec/../bin/hadoop job  -kill job_201404251509_0131
Hadoop job information for Stage-3: number of mappers: 1; number of reducers: 0
2014-04-29 09:13:39,979 Stage-3 map = 0%,  reduce = 0%
2014-04-29 09:13:46,025 Stage-3 map = 100%,  reduce = 0%, Cumulative CPU 1.59 sec
2014-04-29 09:13:47,034 Stage-3 map = 100%,  reduce = 0%, Cumulative CPU 1.59 sec
2014-04-29 09:13:48,044 Stage-3 map = 100%,  reduce = 0%, Cumulative CPU 1.59 sec
2014-04-29 09:13:49,052 Stage-3 map = 100%,  reduce = 0%, Cumulative CPU 1.59 sec
2014-04-29 09:13:50,061 Stage-3 map = 100%,  reduce = 0%, Cumulative CPU 1.59 sec
2014-04-29 09:13:51,069 Stage-3 map = 100%,  reduce = 0%, Cumulative CPU 1.59 sec
2014-04-29 09:13:52,077 Stage-3 map = 100%,  reduce = 100%, Cumulative CPU 1.59 sec
MapReduce Total cumulative CPU time: 1 seconds 590 msec
Ended Job = job_201404251509_0131
MapReduce Jobs Launched:
Job 0: Map: 1  Cumulative CPU: 1.59 sec  HDFS Read: 211 HDFS Write: 16 SUCCESS
Total MapReduce CPU Time Spent: 1 seconds 590 msec
OK
a1      a2      b1      b2
1      X      1      X
2      Y      2      Y

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