[Hadoop] Sqoop安装过程详解

长平狐 发布于 2013/06/03 15:43
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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


原文链接:http://blog.csdn.net/u010415792/article/details/8907650
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