[Hadoop] Sqoop安装过程详解

Sqoop是一个用来将Hadoop和关系型数据库中的数据相互转移的工具，可以将一个关系型数据库（例如 ： MySQL ,Oracle ,Postgres等）中的数据导进到Hadoop的HDFS中，也可以将HDFS的数据导进到关系型数据库中。

Sqoop官方版本：http://apache.dataguru.cn/sqoop/1.4.2/
Sqoop CDH版本：http://archive.cloudera.com/cdh/3/sqoop-1.2.0-CDH3B4.tar.gz
Hadoop CDH版本：http://archive.cloudera.com/cdh/3/hadoop-0.20.2-CDH3B4.tar.gz

之前已经安装Hadoop-0.20.2，因sqoop官方版本不支持此版本，但可使用CDH3版本，如上面的下载链接。为了测试方便，可以通过拷贝相应的包到sqoop-1.2.0-CDH3B4/lib下，依然可以使用Hadoop-0.20.2版本。

sqoop版本:sqoop-1.2.0-CDH3B4

Hadoop版本：0.20.2

mysql版本:5.6.11

1）解压缩sqoop安装文件

[hadoop@node01 ~]$ tar -xzvf sqoop-1.2.0-CDH3B4.tar.gz

2）sqoop-1.2.0-CDH3B4依赖hadoop-core-0.20.2-CDH3B4.jar，所以你需要下载hadoop- 0.20.2-CDH3B4.tar.gz，解压缩后将hadoop-0.20.2-CDH3B4/hadoop-core-0.20.2- CDH3B4.jar复制到sqoop-1.2.0-CDH3B4/lib中。

[hadoop@node01 ~]$ cp hadoop-core-0.20.2-CDH3B4.jar sqoop-1.2.0-CDH3B4/lib

[hadoop@node01 ~]$ ls -l sqoop-1.2.0-CDH3B4/lib/hadoop-core-0.20.2-CDH3B4.jar

-rw-r--r--. 1 hadoop root 3452461 May 9 05:40 sqoop-1.2.0-CDH3B4/lib/hadoop-core-0.20.2-CDH3B4.jar

3）另外，sqoop导入mysql数据运行过程中依赖mysql-connector-java-*.jar，所以你需要下载mysql-connector-java-*.jar并复制到sqoop-1.2.0-CDH3B4/lib中

[hadoop@node01 ~]$ cp mysql-connector-java-5.1.24-bin.jar sqoop-1.2.0-CDH3B4/lib

[hadoop@node01 ~]$ ls -l sqoop-1.2.0-CDH3B4/lib/mysql-connector-java-5.1.24-bin.jar

-rw-r--r--. 1 hadoop root 846263 May 9 05:43 sqoop-1.2.0-CDH3B4/lib/mysql-connector-java-5.1.24-bin.jar

4）修改SQOOP的文件configure-sqoop，注释掉hbase和zookeeper检查（除非你准备使用HABASE等HADOOP上的组件），否则在进行hbase和zookeeper检查时，可能会卡在这里。

[hadoop@node01 bin]$ pwd

/home/hadoop/sqoop-1.2.0-CDH3B4/bin

[hadoop@node01 bin]$ vi configure-sqoop

#if [ -z "${HBASE_HOME}" ]; then

# HBASE_HOME=/usr/lib/hbase

#fi

#if [ -z "${ZOOKEEPER_HOME}" ]; then

# ZOOKEEPER_HOME=/usr/lib/zookeeper

#fi

#if [ ! -d "${HBASE_HOME}" ]; then

# echo "Error: $HBASE_HOME does not exist!"

# echo 'Please set $HBASE_HOME to the root of your HBase installation.'

# exit 1

#fi

#if [ ! -d "${ZOOKEEPER_HOME}" ]; then

# echo "Error: $ZOOKEEPER_HOME does not exist!"

# echo 'Please set $ZOOKEEPER_HOME to the root of your ZooKeeper installation.'

# exit 1

#fi

5）启动Hadoop

[hadoop@node01 bin]$ start-all.sh

[hadoop@node01 bin]$ jps

2732 Jps

2478 NameNode

2665 JobTracker

2600 SecondaryNameNode

6）从MySQL导入数据到HDFS

（1）在MySQL里创建测试数据库sqooptest

[hadoop@node01 ~]$ mysql -u root -p

mysql> create database sqooptest;

Query OK, 1 row affected (0.01 sec)

（2）创建sqoop专有用户

mysql> create user 'sqoop' identified by 'sqoop';

Query OK, 0 rows affected (0.00 sec)

mysql> grant all privileges on *.* to 'sqoop' with grant option;

Query OK, 0 rows affected (0.00 sec)

mysql> flush privileges;

Query OK, 0 rows affected (0.00 sec)

（3）生成测试数据

mysql> use sqooptest;

Database changed

mysql> create table tb1 as select table_schema,table_name,table_type from information_schema.TABLES;

Query OK, 154 rows affected (0.28 sec)

Records: 154 Duplicates: 0 Warnings: 0

（4）测试sqoop与mysql的连接

[hadoop@node01 ~]$ sqoop list-databases --connect jdbc:mysql://node01:3306/ --username sqoop --password sqoop

13/05/09 06:15:01 WARN tool.BaseSqoopTool: Setting your password on the command-line is insecure. Consider using -P instead.

13/05/09 06:15:01 INFO manager.MySQLManager: Executing SQL statement: SHOW DATABASES

information_schema

hive

mysql

performance_schema

sqooptest

test

（5）从MySQL导入数据到HDFS

[hadoop@node01 ~]$ sqoop import --connect jdbc:mysql://node01:3306/sqooptest --username sqoop --password sqoop --table tb1 -m 1

13/05/09 06:16:39 WARN tool.BaseSqoopTool: Setting your password on the command-line is insecure. Consider using -P instead.

13/05/09 06:16:39 INFO tool.CodeGenTool: Beginning code generation

13/05/09 06:16:39 INFO manager.MySQLManager: Executing SQL statement: SELECT t.* FROM `tb1` AS t LIMIT 1

13/05/09 06:16:39 INFO manager.MySQLManager: Executing SQL statement: SELECT t.* FROM `tb1` AS t LIMIT 1

13/05/09 06:16:39 INFO orm.CompilationManager: HADOOP_HOME is /home/hadoop/hadoop-0.20.2/bin/..

13/05/09 06:16:39 INFO orm.CompilationManager: Found hadoop core jar at: /home/hadoop/hadoop-0.20.2/bin/../hadoop-0.20.2-core.jar

13/05/09 06:16:42 INFO orm.CompilationManager: Writing jar file: /tmp/sqoop-hadoop/compile/4175ce59fd53eb3de75875cfd3bd450b/tb1.jar

13/05/09 06:16:42 WARN manager.MySQLManager: It looks like you are importing from mysql.

13/05/09 06:16:42 WARN manager.MySQLManager: This transfer can be faster! Use the --direct

13/05/09 06:16:42 WARN manager.MySQLManager: option to exercise a MySQL-specific fast path.

13/05/09 06:16:42 INFO manager.MySQLManager: Setting zero DATETIME behavior to convertToNull (mysql)

13/05/09 06:16:42 INFO mapreduce.ImportJobBase: Beginning import of tb1

13/05/09 06:16:43 INFO manager.MySQLManager: Executing SQL statement: SELECT t.* FROM `tb1` AS t LIMIT 1

13/05/09 06:16:45 INFO mapred.JobClient: Running job: job_201305090600_0001

13/05/09 06:16:46 INFO mapred.JobClient: map 0% reduce 0%

13/05/09 06:17:01 INFO mapred.JobClient: map 100% reduce 0%

13/05/09 06:17:03 INFO mapred.JobClient: Job complete: job_201305090600_0001

13/05/09 06:17:03 INFO mapred.JobClient: Counters: 5

13/05/09 06:17:03 INFO mapred.JobClient: Job Counters

13/05/09 06:17:03 INFO mapred.JobClient: Launched map tasks=1

13/05/09 06:17:03 INFO mapred.JobClient: FileSystemCounters

13/05/09 06:17:03 INFO mapred.JobClient: HDFS_BYTES_WRITTEN=7072

13/05/09 06:17:03 INFO mapred.JobClient: Map-Reduce Framework

13/05/09 06:17:03 INFO mapred.JobClient: Map input records=154

13/05/09 06:17:03 INFO mapred.JobClient: Spilled Records=0

13/05/09 06:17:03 INFO mapred.JobClient: Map output records=154

13/05/09 06:17:03 INFO mapreduce.ImportJobBase: Transferred 6.9062 KB in 19.9871 seconds (353.8277 bytes/sec)

13/05/09 06:17:03 INFO mapreduce.ImportJobBase: Retrieved 154 records.

（6）在HDFS上查看刚刚导入的数据

[hadoop@node01 ~]$ hadoop dfs -ls tb1

Found 2 items

drwxr-xr-x - hadoop supergroup 0 2013-05-09 06:16 /user/hadoop/tb1/_logs

-rw-r--r-- 2 hadoop supergroup 7072 2013-05-09 06:16 /user/hadoop/tb1/part-m-00000