一、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/

2、修改配置文件

$ cd sqoop/conf（默认将sqoop解压到当前目录下）

$ mv sqoop-env-template.sh sqoop-env.sh

打开sqoop-env.sh并编辑下面几行：

export HADOOP_COMMON_HOME=/home/hadoop/apps/hadoop-2.6.4/（可用which （hadoop）命令查看位置）

export HADOOP_MAPRED_HOME=/home/hadoop/apps/hadoop-2.6.4/

export HIVE_HOME=/home/hadoop/apps/hive

3、加入mysql的jdbc驱动包

cp  ~/apps/hive/lib/mysql-connector-java-5.1.28.jar   /sqoop/lib/（在之前的hive安装中已经导入过mysql驱动包）

若无，则可以将驱动包上传至虚拟机，拷入至sqoop/lib中

4、验证启动

$ cd sqoop/bin

$ sqoop-version

预期的输出：

15/12/17 14:52:32 INFO sqoop.Sqoop: Running Sqoop version: 1.4.6

Sqoop 1.4.6 git commit id 5b34accaca7de251fc91161733f906af2eddbe83

Compiled by abe on Fri Aug 1 11:19:26 PDT 2015

到这里，整个Sqoop安装工作完成。

5、使用

cd sqoop/

使用bin/sqoop help 可查看其中操作指令

Available commands:
  codegen            Generate code to interact with database records
  create-hive-table  Import a table definition into Hive
  eval               Evaluate a SQL statement and display the results
  export             Export an HDFS directory to a database table
  help               List available commands
  import             Import a table from a database to HDFS
  import-all-tables  Import tables from a database to HDFS
  import-mainframe   Import datasets from a mainframe server to HDFS
  job                Work with saved jobs
  list-databases     List available databases on a server
  list-tables        List available tables in a database
  merge              Merge results of incremental imports
  metastore          Run a standalone Sqoop metastore
  version            Display version information

举例：将mysql数据库中某表数据导入HDFS中，由于前边的hadoop配置，最终数据会导向HDFS中的/usr/hadoop/文件夹中：

$bin/sqoop import   \
--connect jdbc:mysql://min1:3306/mysql   \   数据库链接信息
--username root  \
--password 123456   \
--table db   \      选择导出哪张表数据
--m 1 

系统会运行mapreduce程序，在min1:8088以及min1:50070中可看到运行过程，如果成功执行，那么会得到下面的输出。

9/03/18 16:53:53 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1552575186473_0030
19/03/18 16:53:54 INFO impl.YarnClientImpl: Submitted application application_1552575186473_0030
19/03/18 16:53:54 INFO mapreduce.Job: The url to track the job: http://min1:8088/proxy/application_1552575186473_0030/
19/03/18 16:53:54 INFO mapreduce.Job: Running job: job_1552575186473_0030
19/03/18 16:54:11 INFO mapreduce.Job: Job job_1552575186473_0030 running in uber mode : false
19/03/18 16:54:11 INFO mapreduce.Job:  map 0% reduce 0%
19/03/18 16:54:32 INFO mapreduce.Job:  map 100% reduce 0%
19/03/18 16:54:33 INFO mapreduce.Job: Job job_1552575186473_0030 completed successfully
19/03/18 16:54:33 INFO mapreduce.Job: Counters: 30
        File System Counters
                FILE: Number of bytes read=0
                FILE: Number of bytes written=124571
                FILE: Number of read operations=0
                FILE: Number of large read operations=0
                FILE: Number of write operations=0
                HDFS: Number of bytes read=87
                HDFS: Number of bytes written=95
                HDFS: Number of read operations=4
                HDFS: Number of large read operations=0
                HDFS: Number of write operations=2
        Job Counters 
                Launched map tasks=1
                Other local map tasks=1
                Total time spent by all maps in occupied slots (ms)=16705
                Total time spent by all reduces in occupied slots (ms)=0
                Total time spent by all map tasks (ms)=16705
                Total vcore-milliseconds taken by all map tasks=16705
                Total megabyte-milliseconds taken by all map tasks=17105920
        Map-Reduce Framework
                Map input records=2
                Map output records=2
                Input split bytes=87
                Spilled Records=0
                Failed Shuffles=0
                Merged Map outputs=0
                GC time elapsed (ms)=110
                CPU time spent (ms)=2980
                Physical memory (bytes) snapshot=103735296
                Virtual memory (bytes) snapshot=2064986112
                Total committed heap usage (bytes)=30474240
        File Input Format Counters 
                Bytes Read=0
        File Output Format Counters 
                Bytes Written=95
19/03/18 16:54:33 INFO mapreduce.ImportJobBase: Transferred 95 bytes in 52.9843 seconds (1.793 bytes/sec)
19/03/18 16:54:33 INFO mapreduce.ImportJobBase: Retrieved 2 records.