Sqoop是一個(gè)用來將Hadoop和關(guān)系型數(shù)據(jù)庫中的數(shù)據(jù)相互轉(zhuǎn)移的工具，可以將一個(gè)關(guān)系型數(shù)據(jù)庫（例如 ： MySQL ,Oracle ,Postgres等）中的數(shù)據(jù)導(dǎo)進(jìn)到Hadoop的HDFS中，也可以將HDFS的數(shù)據(jù)導(dǎo)進(jìn)到關(guān)系型數(shù)據(jù)庫中。
Sqoop中一大亮點(diǎn)就是可以通過hadoop的mapreduce把數(shù)據(jù)從關(guān)系型數(shù)據(jù)庫中導(dǎo)入數(shù)據(jù)到HDFS。
一、安裝sqoop
1、下載sqoop壓縮包，并解壓
壓縮包分別是：sqoop-1.2.0-CDH3B4.tar.gz，hadoop-0.20.2-CDH3B4.tar.gz， Mysql JDBC驅(qū)動(dòng)包mysql-connector-java-5.1.10-bin.jar
[root@node1 ~]# ll
drwxr-xr-x 15 root root 4096 Feb 22 2011 hadoop-0.20.2-CDH3B4-rw-r--r-- 1 root root 724225 Sep 15 06:46 mysql-connector-java-5.1.10-bin.jardrwxr-xr-x 11 root root 4096 Feb 22 2011 sqoop-1.2.0-CDH3B4
2、將sqoop-1.2.0-CDH3B4拷貝到/home/hadoop目錄下，并將Mysql JDBC驅(qū)動(dòng)包和hadoop-0.20.2-CDH3B4下的hadoop-core-0.20.2-CDH3B4.jar至sqoop-1.2.0-CDH3B4/lib下，最后修改一下屬主。
[root@node1 ~]# cp mysql-connector-java-5.1.10-bin.jar sqoop-1.2.0-CDH3B4/lib[root@node1 ~]# cp hadoop-0.20.2-CDH3B4/hadoop-core-0.20.2-CDH3B4.jar sqoop-1.2.0-CDH3B4/lib[root@node1 ~]# chown -R hadoop:hadoop sqoop-1.2.0-CDH3B4[root@node1 ~]# mv sqoop-1.2.0-CDH3B4 /home/hadoop[root@node1 ~]# ll /home/hadoop
total 35748-rw-rw-r-- 1 hadoop hadoop 343 Sep 15 05:13 derby.logdrwxr-xr-x 13 hadoop hadoop 4096 Sep 14 16:16 hadoop-0.20.2drwxr-xr-x 9 hadoop hadoop 4096 Sep 14 20:21 hive-0.10.0-rw-r--r-- 1 hadoop hadoop 36524032 Sep 14 20:20 hive-0.10.0.tar.gzdrwxr-xr-x 8 hadoop hadoop 4096 Sep 25 2012 jdk1.7drwxr-xr-x 12 hadoop hadoop 4096 Sep 15 00:25 mahout-distribution-0.7drwxrwxr-x 5 hadoop hadoop 4096 Sep 15 05:13 metastore_db-rw-rw-r-- 1 hadoop hadoop 406 Sep 14 16:02 scp.shdrwxr-xr-x 11 hadoop hadoop 4096 Feb 22 2011 sqoop-1.2.0-CDH3B4drwxrwxr-x 3 hadoop hadoop 4096 Sep 14 16:17 tempdrwxrwxr-x 3 hadoop hadoop 4096 Sep 14 15:59 user
3、配置configure-sqoop，注釋掉對于HBase和ZooKeeper的檢查
[root@node1 bin]# pwd
/home/hadoop/sqoop-1.2.0-CDH3B4/bin
[root@node1 bin]# vi configure-sqoop
#!/bin/bash## Licensed to Cloudera, Inc. under one or more# contributor license agreements. See the NOTICE file distributed with# this work for additional information regarding copyright ownership....# Check: If we can't find our dependencies, give up here.if [ ! -d "${HADOOP_HOME}" ]; then echo "Error: $HADOOP_HOME does not exist!" echo 'Please set $HADOOP_HOME to the root of your Hadoop installation.' exit 1fi#if [ ! -d "${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 $ZOOKEEPER_HOME to the root of your ZooKeeper installation.'# exit 1#fi4、修改/etc/profile和.bash_profile文件，添加Hadoop_Home,調(diào)整PATH
[hadoop@node1 ~]$ vi .bash_profile
# .bash_profile# Get the aliases and functionsif [ -f ~/.bashrc ]; then . ~/.bashrcfi# User specific environment and startup programsHADOOP_HOME=/home/hadoop/hadoop-0.20.2PATH=$HADOOP_HOME/bin:$PATH:$HOME/binexport HIVE_HOME=/home/hadoop/hive-0.10.0export MAHOUT_HOME=/home/hadoop/mahout-distribution-0.7export PATH HADOOP_HOME
二、測試Sqoop
1、查看mysql中的數(shù)據(jù)庫：
[hadoop@node1 bin]$ ./sqoop list-databases --connect jdbc:mysql://192.168.1.152:3306/ --username sqoop --password sqoop
13/09/15 07:17:16 WARN tool.BaseSqoopTool: Setting your password on the command-line is insecure. Consider using -P instead.13/09/15 07:17:17 INFO manager.MySQLManager: Executing SQL statement: SHOW DATABASESinformation_schemamysqlperformance_schemasqooptest
2、將mysql的表導(dǎo)入到hive中：
[hadoop@node1 bin]$ ./sqoop import --connect jdbc:mysql://192.168.1.152:3306/sqoop --username sqoop --password sqoop --table test --hive-import -m 1
13/09/15 08:15:01 WARN tool.BaseSqoopTool: Setting your password on the command-line is insecure. Consider using -P instead.13/09/15 08:15:01 INFO tool.BaseSqoopTool: Using Hive-specific delimiters for output. You can override13/09/15 08:15:01 INFO tool.BaseSqoopTool: delimiters with --fields-terminated-by, etc.13/09/15 08:15:01 INFO tool.CodeGenTool: Beginning code generation13/09/15 08:15:01 INFO manager.MySQLManager: Executing SQL statement: SELECT t.* FROM `test` AS t LIMIT 113/09/15 08:15:02 INFO manager.MySQLManager: Executing SQL statement: SELECT t.* FROM `test` AS t LIMIT 113/09/15 08:15:02 INFO orm.CompilationManager: HADOOP_HOME is /home/hadoop/hadoop-0.20.2/bin/..13/09/15 08:15:02 INFO orm.CompilationManager: Found hadoop core jar at: /home/hadoop/hadoop-0.20.2/bin/../hadoop-0.20.2-core.jar13/09/15 08:15:03 INFO orm.CompilationManager: Writing jar file: /tmp/sqoop-hadoop/compile/a71936fd2bb45ea6757df22751a320e3/test.jar13/09/15 08:15:03 WARN manager.MySQLManager: It looks like you are importing from mysql.13/09/15 08:15:03 WARN manager.MySQLManager: This transfer can be faster! Use the --direct13/09/15 08:15:03 WARN manager.MySQLManager: option to exercise a MySQL-specific fast path.13/09/15 08:15:03 INFO manager.MySQLManager: Setting zero DATETIME behavior to convertToNull (mysql)13/09/15 08:15:03 INFO mapreduce.ImportJobBase: Beginning import of test13/09/15 08:15:04 INFO manager.MySQLManager: Executing SQL statement: SELECT t.* FROM `test` AS t LIMIT 113/09/15 08:15:05 INFO mapred.JobClient: Running job: job_201309150505_000913/09/15 08:15:06 INFO mapred.JobClient: map 0% reduce 0%13/09/15 08:15:34 INFO mapred.JobClient: map 100% reduce 0%13/09/15 08:15:36 INFO mapred.JobClient: Job complete: job_201309150505_000913/09/15 08:15:36 INFO mapred.JobClient: Counters: 513/09/15 08:15:36 INFO mapred.JobClient: Job Counters 13/09/15 08:15:36 INFO mapred.JobClient: Launched map tasks=113/09/15 08:15:36 INFO mapred.JobClient: FileSystemCounters13/09/15 08:15:36 INFO mapred.JobClient: HDFS_BYTES_WRITTEN=58332313/09/15 08:15:36 INFO mapred.JobClient: Map-Reduce Framework13/09/15 08:15:36 INFO mapred.JobClient: Map input records=6553613/09/15 08:15:36 INFO mapred.JobClient: Spilled Records=013/09/15 08:15:36 INFO mapred.JobClient: Map output records=6553613/09/15 08:15:36 INFO mapreduce.ImportJobBase: Transferred 569.6514 KB in 32.0312 seconds (17.7842 KB/sec)13/09/15 08:15:36 INFO mapreduce.ImportJobBase: Retrieved 65536 records.13/09/15 08:15:36 INFO hive.HiveImport: Removing temporary files from import process: test/_logs13/09/15 08:15:36 INFO hive.HiveImport: Loading uploaded data into Hive13/09/15 08:15:36 INFO manager.MySQLManager: Executing SQL statement: SELECT t.* FROM `test` AS t LIMIT 113/09/15 08:15:36 INFO manager.MySQLManager: Executing SQL statement: SELECT t.* FROM `test` AS t LIMIT 113/09/15 08:15:41 INFO hive.HiveImport: Logging initialized using configuration in jar:file:/home/hadoop/hive-0.10.0/lib/hive-common-0.10.0.jar!/hive-log4j.properties13/09/15 08:15:41 INFO hive.HiveImport: Hive history file=/tmp/hadoop/hive_job_log_hadoop_201309150815_1877092059.txt13/09/15 08:16:10 INFO hive.HiveImport: OK13/09/15 08:16:10 INFO hive.HiveImport: Time taken: 28.791 seconds13/09/15 08:16:11 INFO hive.HiveImport: Loading data to table default.test13/09/15 08:16:12 INFO hive.HiveImport: Table default.test stats: [num_partitions: 0, num_files: 1, num_rows: 0, total_size: 583323, raw_data_size: 0]13/09/15 08:16:12 INFO hive.HiveImport: OK13/09/15 08:16:12 INFO hive.HiveImport: Time taken: 1.704 seconds13/09/15 08:16:12 INFO hive.HiveImport: Hive import complete.
三、Sqoop 命令
Sqoop大約有13種命令,和幾種通用的參數(shù)(都支持這13種命令)，這里先列出這13種命令。
接著列出Sqoop的各種通用參數(shù),然后針對以上13個(gè)命令列出他們自己的參數(shù)。Sqoop通用參數(shù)又分Common arguments,Incremental import arguments,Output line formatting arguments,Input parsing arguments,Hive arguments,HBase arguments,Generic Hadoop command-line arguments,下面說明一下幾個(gè)常用的命令:
1.Common arguments
通用參數(shù),主要是針對關(guān)系型數(shù)據(jù)庫鏈接的一些參數(shù)
1）列出mysql數(shù)據(jù)庫中的所有數(shù)據(jù)庫