hive学习笔记之八:Sqoop

程序员欣宸 2021-04-16 13:50:19
Mysql hadoop


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关于Sqoop

Sqoop是Apache开源项目,用于在Hadoop和关系型数据库之间高效传输大量数据,本文将与您一起实践以下内容:

  1. 部署Sqoop
  2. 用Sqoop将hive表数据导出至MySQL
  3. 用Sqoop将MySQL数据导入到hive表

部署

  1. 在hadoop账号的家目录下载Sqoop的<font color="blue">1.4.7</font>版本:
wget https://mirror.bit.edu.cn/apache/sqoop/1.4.7/sqoop-1.4.7.bin__hadoop-2.6.0.tar.gz
  1. 解压:
tar -zxvf sqoop-1.4.7.bin__hadoop-2.6.0.tar.gz
  1. 解压后得到文件夹<font color="blue">sqoop-1.4.7.bin__hadoop-2.6.0</font>,将<font color="red">mysql-connector-java-5.1.47.jar</font>复制到<font color="blue">sqoop-1.4.7.bin__hadoop-2.6.0/lib</font>目录下
  2. 进入目录<font color="blue">sqoop-1.4.7.bin__hadoop-2.6.0/conf</font>,将<font color="red">sqoop-env-template.sh</font>改名为<font color="blue">sqoop-env.sh</font>:
mv sqoop-env-template.sh sqoop-env.sh
  1. 用编辑器打开<font color="blue">sqoop-env.sh</font>,增加下面三个配置,<font color="red">HADOOP_COMMON_HOME</font>和<font color="red">HADOOP_MAPRED_HOME</font>是完整的hadoop路径,<font color="red">HIVE_HOME</font>是完整的hive路径:
export HADOOP_COMMON_HOME=/home/hadoop/hadoop-2.7.7
export HADOOP_MAPRED_HOME=/home/hadoop/hadoop-2.7.7
export HIVE_HOME=/home/hadoop/apache-hive-1.2.2-bin
  1. 安装和配置完成了,进入<font color="blue">sqoop-1.4.7.bin__hadoop-2.6.0/bin</font>,执行<font color="blue">./sqoop version</font>查看sqoop版本,如下所示,可见是1.4.7版本(有些环境变量没配置会输出告警,在此先忽略):
[[email protected] bin]$ ./sqoop version
Warning: /home/hadoop/sqoop-1.4.7.bin__hadoop-2.6.0/bin/../../hbase does not exist! HBase imports will fail.
Please set $HBASE_HOME to the root of your HBase installation.
Warning: /home/hadoop/sqoop-1.4.7.bin__hadoop-2.6.0/bin/../../hcatalog does not exist! HCatalog jobs will fail.
Please set $HCAT_HOME to the root of your HCatalog installation.
Warning: /home/hadoop/sqoop-1.4.7.bin__hadoop-2.6.0/bin/../../accumulo does not exist! Accumulo imports will fail.
Please set $ACCUMULO_HOME to the root of your Accumulo installation.
Warning: /home/hadoop/sqoop-1.4.7.bin__hadoop-2.6.0/bin/../../zookeeper does not exist! Accumulo imports will fail.
Please set $ZOOKEEPER_HOME to the root of your Zookeeper installation.
20/11/02 12:02:58 INFO sqoop.Sqoop: Running Sqoop version: 1.4.7
Sqoop 1.4.7
git commit id 2328971411f57f0cb683dfb79d19d4d19d185dd8
Compiled by maugli on Thu Dec 21 15:59:58 STD 2017
  • sqoop装好之后,接下来体验其功能

MySQL准备

为了接下来的实战,需要把MySQL准备好,这里给出的MySQL的配置供您参考:

  1. MySQL版本:5.7.29
  2. MySQL服务器IP:192.168.50.43
  3. MySQL服务端口:3306
  4. 账号:root
  5. 密码:123456
  6. 数据库名:sqoop

关于MySQL部署,我这为了省事儿,是用docker部署的,参考《群晖DS218+部署mysql》

从hive导入MySQL(export)

  • 执行以下命令,将hive的数据导入到MySQL:
./sqoop export \
--connect jdbc:mysql://192.168.50.43:3306/sqoop \
--table address \
--username root \
--password 123456 \
--export-dir '/user/hive/warehouse/address' \
--fields-terminated-by ','
  • 查看<font color="blue">address</font>表,数据已经导入:

在这里插入图片描述

从MySQL导入hive(import)

  1. 在hive的命令行模式执行以下语句,新建名为address2的表结构和address一模一样:
create table address2 (addressid int, province string, city string)
row format delimited
fields terminated by ',';
  1. 执行以下命令,将MySQL的address表的数据导入到hive的address2表,<font color="red">-m 2</font>表示启动2个map任务:
./sqoop import \
--connect jdbc:mysql://192.168.50.43:3306/sqoop \
--table address \
--username root \
--password 123456 \
--target-dir '/user/hive/warehouse/address2' \
-m 2
  1. 执行完毕后,控制台输入类似以下内容:
 Virtual memory (bytes) snapshot=4169867264
Total committed heap usage (bytes)=121765888
File Input Format Counters 
Bytes Read=0
File Output Format Counters 
Bytes Written=94
20/11/02 16:09:22 INFO mapreduce.ImportJobBase: Transferred 94 bytes in 16.8683 seconds (5.5726 bytes/sec)
20/11/02 16:09:22 INFO mapreduce.ImportJobBase: Retrieved 5 records.
  1. 去查看hive的address2表,可见数据已经成功导入:
hive> select * from address2;
OK
1 guangdong guangzhou
2 guangdong shenzhen
3 shanxi xian
4 shanxi hanzhong
6 jiangshu nanjing
Time taken: 0.049 seconds, Fetched: 5 row(s)
  • 至此,Sqoop工具的部署和基本操作已经体验完成,希望您在执行数据导入导出操作时,此文能给您一些参考;

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