继续写，其实mysql 导入导出 hdfs 对于实际项目开发没啥用的，但是那个可以拿来入门。今天写跟Hbase和Hive的协作。我突然发现我的教程写的顺序很凌乱啊，没有先介绍Hive 的安装，这点向大家道歉，我后面补上。 数据准备 mysql 在mysql 里面建立表 employee

继续写，其实mysql 导入导出 hdfs 对于实际项目开发没啥用的，但是那个可以拿来入门。今天写跟Hbase和Hive的协作。我突然发现我的教程写的顺序很凌乱啊，没有先介绍Hive 的安装，这点向大家道歉，我后面补上。

数据准备

mysql

在mysql 里面建立表 employee 并插入数据

CREATE TABLE `employee` (

`id` int(11) NOT NULL,

`name` varchar(20) NOT NULL,

PRIMARY KEY (`id`)

) ENGINE=MyISAM DEFAULT CHARSET=utf8;

insert into employee (id,name) values (1,'michael');

insert into employee (id,name) values (2,'ted');

insert into employee (id,name) values (3,'jack');

Hbase

hbase(main):006:0> create 'employee','info'

0 row(s) in 0.4440 seconds

=> Hbase::Table - employee

Hive

不需要数据准备，等等用--create-hive-table会自动建表

从mysql导入到Hbase

# sqoop import --connect jdbc:mysql://localhost:3306/sqoop_test --username root --password root --table employee --hbase-table employee --column-family info --hbase-row-key id -m 1

Warning: /usr/lib/sqoop/../hive-hcatalog does not exist! HCatalog jobs will fail.

Please set $HCAT_HOME to the root of your HCatalog installation.

Warning: /usr/lib/sqoop/../accumulo does not exist! Accumulo imports will fail.

Please set $ACCUMULO_HOME to the root of your Accumulo installation.

14/12/01 17:36:25 INFO sqoop.Sqoop: Running Sqoop version: 1.4.4-cdh5.0.1

14/12/01 17:36:25 WARN tool.BaseSqoopTool: Setting your password on the command-line is insecure. Consider using -P instead.

14/12/01 17:36:25 INFO manager.MySQLManager: Preparing to use a MySQL streaming resultset.

14/12/01 17:36:25 INFO tool.CodeGenTool: Beginning code generation

14/12/01 17:36:26 INFO manager.SqlManager: Executing SQL statement: SELECT t.* FROM `employee` AS t LIMIT 1

14/12/01 17:36:26 INFO manager.SqlManager: Executing SQL statement: SELECT t.* FROM `employee` AS t LIMIT 1

14/12/01 17:36:26 INFO orm.CompilationManager: HADOOP_MAPRED_HOME is /usr/lib/hadoop-mapreduce

……中间日志太多了，用省略号代替

14/12/01 17:37:12 INFO mapreduce.ImportJobBase: Transferred 0 bytes in 37.3924 seconds (0 bytes/sec)

14/12/01 17:37:12 INFO mapreduce.ImportJobBase: Retrieved 3 records.

去检查下hbase

hbase(main):001:0> scan 'employee'

SLF4J: Class path contains multiple SLF4J bindings.

SLF4J: Found binding in [jar:file:/usr/lib/hadoop/lib/slf4j-log4j12.jar!/org/slf4j/impl/StaticLoggerBinder.class]

SLF4J: Found binding in [jar:file:/usr/lib/zookeeper/lib/slf4j-log4j12-1.7.5.jar!/org/slf4j/impl/StaticLoggerBinder.class]

SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.

SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]

ROW COLUMN+CELL

1 column=info:name, timestamp=1417426628685, value=michael

2 column=info:name, timestamp=1417426628685, value=ted

3 column=info:name, timestamp=1417426628685, value=jack

3 row(s) in 0.1630 seconds

成功插入3条数据

从mysql导入hive

# sqoop import --connect jdbc:mysql://localhost:3306/sqoop_test --username root --password root --table employee --hive-import --hive-table hive_employee --create-hive-table

Warning: /usr/lib/sqoop/../hive-hcatalog does not exist! HCatalog jobs will fail.

Please set $HCAT_HOME to the root of your HCatalog installation.

Warning: /usr/lib/sqoop/../accumulo does not exist! Accumulo imports will fail.

Please set $ACCUMULO_HOME to the root of your Accumulo installation.

……………………

14/12/02 15:12:13 INFO hive.HiveImport: Loading data to table default.hive_employee

14/12/02 15:12:14 INFO hive.HiveImport: Table default.hive_employee stats: [num_partitions: 0, num_files: 4, num_rows: 0, total_size: 23, raw_data_size: 0]

14/12/02 15:12:14 INFO hive.HiveImport: OK

14/12/02 15:12:14 INFO hive.HiveImport: Time taken: 0.799 seconds

14/12/02 15:12:14 INFO hive.HiveImport: Hive import complete.

14/12/02 15:12:14 INFO hive.HiveImport: Export directory is empty, removing it.

这里说下真实环境中mysql的jdbc链接不要用localhost，因为这个任务会被分布式的发送不同的hadoop机子上，要那些机子真的可以通过jdbc连到mysql上才行，否则会丢数据

检查下hive

hive> select * from hive_employee;

OK

1michael

2ted

3jack

Time taken: 0.179 seconds, Fetched: 3 row(s)

还有一点要声明下：目前sqoop只能从mysql导入数据到hive的原生表(也就是基于hdfs存储的)，无法导入数据到外部表(比如基于hbase建立的hive表)

下课！下次讲导出！

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