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.jarsqoop-1.2.0-CDH3B4/lib
[hadoop@node01 ~]$ ls -lsqoop-1.2.0-CDH3B4/lib/hadoop-core-0.20.2-CDH3B4.jar
-rw-r--r--. 1 hadoop root 3452461 May  9 05:40sqoop-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 ~]$ cpmysql-connector-java-5.1.24-bin.jar sqoop-1.2.0-CDH3B4/lib
[hadoop@node01 ~]$ ls -lsqoop-1.2.0-CDH3B4/lib/mysql-connector-java-5.1.24-bin.jar
-rw-r--r--. 1 hadoop root 846263 May  9 05:43sqoop-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 notexist!"
#  echo 'Please set $HBASE_HOME to the root ofyour HBase installation.'
#  exit 1
#fi
#if [ ! -d "${ZOOKEEPER_HOME}" ]; then
#  echo "Error: $ZOOKEEPER_HOME does notexist!"
#  echo 'Please set $ZOOKEEPER_HOME to the rootof 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' withgrant 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 selecttable_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 --connectjdbc:mysql://node01:3306/ --username sqoop --password sqoop
13/05/09 06:15:01 WARN tool.BaseSqoopTool: Settingyour password on the command-line is insecure. Consider using -P instead.
13/05/09 06:15:01 INFO manager.MySQLManager: ExecutingSQL statement: SHOW DATABASES
information_schema
hive
mysql
performance_schema
sqooptest
test
 
(5)从MySQL导入数据到HDFS
[hadoop@node01 ~]$ sqoop import --connectjdbc:mysql://node01:3306/sqooptest --username sqoop --password sqoop --tabletb1 -m 1
13/05/09 06:16:39 WARN tool.BaseSqoopTool: Settingyour password on the command-line is insecure. Consider using -P instead.
13/05/09 06:16:39 INFO tool.CodeGenTool: Beginningcode generation
13/05/09 06:16:39 INFO manager.MySQLManager: ExecutingSQL statement: SELECT t.* FROM `tb1` AS t LIMIT 1
13/05/09 06:16:39 INFO manager.MySQLManager: ExecutingSQL 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: Foundhadoop 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: Writingjar file: /tmp/sqoop-hadoop/compile/4175ce59fd53eb3de75875cfd3bd450b/tb1.jar
13/05/09 06:16:42 WARN manager.MySQLManager: It lookslike you are importing from mysql.
13/05/09 06:16:42 WARN manager.MySQLManager: Thistransfer can be faster! Use the --direct
13/05/09 06:16:42 WARN manager.MySQLManager: option toexercise a MySQL-specific fast path.
13/05/09 06:16:42 INFO manager.MySQLManager: Settingzero 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: ExecutingSQL 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:  map100% 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:   JobCounters
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

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