HIVE中Sqoop1.4.6安装、hive与oracle表互导的示例分析

这篇文章主要为大家展示了“HIVE中Sqoop1.4.6安装、hive与oracle表互导的示例分析”,内容简而易懂,条理清晰,希望能够帮助大家解决疑惑,下面让小编带领大家一起研究并学习一下“HIVE中Sqoop1.4.6安装、hive与oracle表互导的示例分析”这篇文章吧。

创新互联长期为近1000家客户提供的网站建设服务,团队从业经验10年,关注不同地域、不同群体,并针对不同对象提供差异化的产品和服务;打造开放共赢平台,与合作伙伴共同营造健康的互联网生态环境。为乳山企业提供专业的网站制作、做网站乳山网站改版等技术服务。拥有十余年丰富建站经验和众多成功案例,为您定制开发。

1. sqoop数据迁移

1.1 概述

sqoop是apache旗下一款“Hadoop和关系数据库服务器之间传送数据”的工具。 
导入数据:MySQL,Oracle导入数据到Hadoop的HDFS、HIVE、HBASE等数据存储系统; 
导出数据:从Hadoop的文件系统中导出数据到关系数据库

1.2 工作机制

将导入或导出命令翻译成mapreduce程序来实现 
在翻译出的mapreduce中主要是对inputformat和outputformat进行定制

1.3 sqoop实战及原理

1.3.1 sqoop安装

安装sqoop的前提是已经具备java和hadoop的环境 
1、下载并解压 
最新版下载地址http://ftp.wayne.edu/apache/sqoop/1.4.6/ 
比如:sqoop-1.4.6.bin__hadoop-2.0.4-alpha.tar.gz

[root@hadoop1 sqoop]# tar -zxvf sqoop-1.4.6.bin__hadoop-2.0.4-alpha.tar.gz
[root@hadoop1 sqoop]# mv sqoop-1.4.6.bin__hadoop-2.0.4-alpha sqoop
[root@hadoop1 sqoop]# ls
apache-hive-1.2.1-bin hadoop-2.7.4 hdfs pig-0.17.0 pig_1517170893185.log sqoop tmp

2、修改配置文件 
在/etc/profile中配置sqoop_home,代码如下:

vim /etc/profile
export SQOOP_HOME=/usr/local/hadoop/sqoop
追加path
export PATH=$PATH:$SQOOP_HOME/bin
[root@hadoop1 sqoop]# source /etc/profile
$ cd $SQOOP_HOME/conf
$ mv sqoop-env-template.sh sqoop-env.sh

打开sqoop-env.sh并编辑下面几行: ## 去掉前面的##

export HADOOP_COMMON_HOME=/usr/local/hadoop/hadoop-2.7.4/
export HADOOP_MAPRED_HOME=/usr/local/hadoop/hadoop-2.7.4/
export HIVE_HOME=/usr/local/hadoop/apache-hive-1.2.1-bin/

配置后的界面效果如下: 
这里写图片描述

3.1 加入oracle的驱动包
将 ojdbc6.jar 放到 $SQOOP_HOME/lib/ 下。

3.2 加入mysql的jdbc驱动包 
将mysql-connector-java-5.1.38.jar 放到 $SQOOP_HOME/lib/ 下。

4、验证启动

$ cd $SQOOP_HOME/bin
$ sqoop-version

预期的输出:


[root@hadoop1 sqoop]# sqoop-version
Warning: /usr/local/hadoop/sqoop/../hbase does not exist! HBase imports will fail.
Please set $HBASE_HOME to the root of your HBase installation.
Warning: /usr/local/hadoop/sqoop/../hcatalog does not exist! HCatalog jobs will fail.
Please set $HCAT_HOME to the root of your HCatalog installation.
Warning: /usr/local/hadoop/sqoop/../accumulo does not exist! Accumulo imports will fail.
Please set $ACCUMULO_HOME to the root of your Accumulo installation.
Warning: /usr/local/hadoop/sqoop/../zookeeper does not exist! Accumulo imports will fail.
Please set $ZOOKEEPER_HOME to the root of your Zookeeper installation.
18/01/29 19:09:34 INFO sqoop.Sqoop: Running Sqoop version: 1.4.6
Sqoop 1.4.6
git commit id c0c5a81723759fa575844a0a1eae8f510fa32c25
Compiled by root on Mon Apr 27 14:38:36 CST 2015
[root@hadoop1 sqoop]#

到这里,整个Sqoop安装工作完成。


数据迁移> oracle to hive ## 注意 HIVE 表名需要大写
sqoop# sqoop import --hive-import --connect jdbc:oracle:thin:@10.100.25.8:1521:devdb1 --username andy --password andy \
--table ANDY --hive-database oracletohive --hive-table ANDY -m 1
说明: 迁移的表时,如果 hive中已经存在,则默认会追加在原表中。 如果 hive 中不存在,则自动创建。


日志输出:
18/01/29 19:35:46 INFO hive.HiveImport: Loading uploaded data into Hive
18/01/29 19:35:51 INFO hive.HiveImport: 
18/01/29 19:35:51 INFO hive.HiveImport: Logging initialized using configuration in jar:file:/usr/local/hadoop/apache-hive-1.2.1-bin/lib/hive-common-1.2.1.jar!/hive-log4j.properties
18/01/29 19:36:02 INFO hive.HiveImport: OK
18/01/29 19:36:02 INFO hive.HiveImport: Time taken: 2.42 seconds
18/01/29 19:36:03 INFO hive.HiveImport: Loading data to table oracletohive.andy
18/01/29 19:36:04 INFO hive.HiveImport: Table oracletohive.andy stats: [numFiles=1, totalSize=1996]
18/01/29 19:36:04 INFO hive.HiveImport: OK
18/01/29 19:36:04 INFO hive.HiveImport: Time taken: 1.579 seconds
18/01/29 19:36:04 INFO hive.HiveImport: Hive import complete.
18/01/29 19:36:04 INFO hive.HiveImport: Export directory is contains the _SUCCESS file only, removing the directory.

> show databases;
OK
default
oracletohive
Time taken: 0.027 seconds, Fetched: 2 row(s)
hive> 
> use oracletohive;
OK
Time taken: 0.034 seconds
hive> 
> show tables;
OK
andy
Time taken: 0.037 seconds, Fetched: 1 row(s)
hive> select count(*) from andy;
Hadoop job information for Stage-1: number of mappers: 1; number of reducers: 1
2018-01-29 19:43:46,040 Stage-1 map = 0%, reduce = 0%
2018-01-29 19:43:54,738 Stage-1 map = 100%, reduce = 0%, Cumulative CPU 1.49 sec
2018-01-29 19:44:03,323 Stage-1 map = 100%, reduce = 100%, Cumulative CPU 3.39 sec
MapReduce Total cumulative CPU time: 3 seconds 390 msec
Ended Job = job_1517222580457_0002
MapReduce Jobs Launched: 
Stage-Stage-1: Map: 1 Reduce: 1 Cumulative CPU: 3.39 sec HDFS Read: 16343 HDFS Write: 2 SUCCESS
Total MapReduce CPU Time Spent: 3 seconds 390 msec
OK
7
Time taken: 34.543 seconds, Fetched: 1 row(s)

数据迁移> hive to oracle

hive迁移oracle,需要提前在oracle中创建迁移的表,否则报 java.sql.SQLSyntaxErrorException: ORA-00942: table or view does not exist


sqoop# sqoop export --table ANDY --connect jdbc:oracle:thin:@10.100.25.8:1521:devdb1 --username andy --password andy 
--export-dir /user/hive/warehouse/oracletohive.db/andy --input-fields-terminated-by '\001' \
--input-lines-terminated-by '\n'

日志输出:
18/01/29 20:21:34 INFO mapreduce.Job: Job job_1517222580457_0005 completed successfully
18/01/29 20:21:34 INFO mapreduce.Job: Counters: 30
。。。。。 省略输出
18/01/29 20:21:34 INFO mapreduce.ExportJobBase: Transferred 5.502 KB in 116.7414 seconds (48.2605 bytes/sec)
18/01/29 20:21:34 INFO mapreduce.ExportJobBase: Exported 7 records.

-- oracle端查看
SQL> select count(*) from andy;

COUNT(*)
----------
14 > 由 7条 变为了 14条 , 说明 hive 导入 oracle 成功!

以上是“HIVE中Sqoop1.4.6安装、hive与oracle表互导的示例分析”这篇文章的所有内容,感谢各位的阅读!相信大家都有了一定的了解,希望分享的内容对大家有所帮助,如果还想学习更多知识,欢迎关注创新互联行业资讯频道!


文章标题:HIVE中Sqoop1.4.6安装、hive与oracle表互导的示例分析
本文地址:http://myzitong.com/article/pjggcp.html