Hadoop生态组件Hive，Sqoop安装及Sqoop从HDFS/hive抽取数据到关系型数据库Mysql

一般Hive依赖关系型数据库Mysql，故先安装Mysql

$:  yum install mysql-server mysql-client [yum安装]
$:  /etc/init.d/mysqld start  [启动mysql服务]
$:  mysql  [登录mysql客户端]
mysql> create database hive;

安装配置Hive

$:  tar zvxf apache-hive-2.1.1-bin.tar

1. 配置环境变量

export HIVE_HOME=/usr/local/apache-hive-2.1.1-bin
export PATH=$PATH:${HIVE_HOME}/bin

2. 配置Hive的基本信息

$: cd /home/hadoop/apache-hive-2.1.1-bin/conf
$: cp hive-default.xml.template hive-site.xml                     #默认配置
$: cp hive-env.sh.template hive-env.sh                           #环境配置文件
$: cp hive-exec-log4j.properties.template hive-exec-log4j.properties   #exec默认配置
$: cp hive-log4j.properties.template hive-log4j.properties           #log默认配置

3. 编辑hive-env.sh,为了方便，直接在最后加上以下信息:

export JAVA_HOME=/home/hadoop/jdk1.8.0_144
export HADOOP_HOME=/home/hadoop/hadoop-2.7.3
export HIVE_HOME=/home/hadoop/apache-hive-2.1.1-bin
export HIVE_CONF_DIR=/home/hadoop/apache-hive-2.1.1-bin/conf

hive-site.xml配置,这个文件较大，只配置name和以下对应的即可，其他信息可以不用管

<property>
      <name>javax.jdo.option.ConnectionURL</name>
      <value>jdbc:mysql://127.0.0.1:3306/metastore?createDatabaseIfNotExist=true</value>
      <description>the URL of the MySQL database</description>
    </property>

<property>
  <name>javax.jdo.option.ConnectionDriverName</name>
  <value>com.mysql.jdbc.Driver</value>
  <description>Driver class name for a JDBC metastore</description>
</property>
<property>
  <name>javax.jdo.option.ConnectionUserName</name>
  <value>hive</value>
</property>
<property>
  <name>javax.jdo.option.ConnectionPassword</name>
  <value>hive</value>
</property>

这里主要配置与mysql的驱动连接等，类似java的JDBC，一定要保证配置正确

4. Hive是将HDFS作为数据的文件系统，所以需要创建一些存储目录并赋权限

hadoop fs -mkdir /home/hive/log
hadoop fs -mkdir /home/hive/warehouse
hadoop fs -mkdir /home/hive/tmp
hadoop fs -chmod g+w /home/hive/log
hadoop fs -chmod g+w /home/hive/warehouse
hadoop fs -chmod g+w /home/hive/tmp

5. 将JDBC 驱动 mysql-connect-java-xxx.jar 复制至$HIVE_HOME/lib目录下

6. 初始化数据库

schematool -initSchema -dbType mysql

在这一步通常会报错，

[root@slave1 bin]# schematool -initSchema -dbType mysql
which: no hbase in (/home/hadoop/sqoop-1.4.6/bin:/home/hadoop/apache-hive-2.1.1-bin/bin:/home/hadoop/hadoop-2.7.3/bin:/home/hadoop/jdk1.8.0_144/bin:/usr/local/sbin:/usr/local/bin:/sbin:/bin:/usr/sbin:/usr/bin:/root/bin)
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/home/hadoop/apache-hive-2.1.1-bin/lib/log4j-slf4j-impl-2.4.1.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/home/hadoop/hadoop-2.7.3/share/hadoop/common/lib/slf4j-log4j12-1.7.10.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.apache.logging.slf4j.Log4jLoggerFactory]
Metastore connection URL:	 jdbc:mysql://localhost:3306/hive?createDatabaseIfNotExist=true&characterEncoding=UTF-8&useSSL=false
Metastore Connection Driver :	 com.mysql.jdbc.Driver
Metastore connection User:	 hive
Starting metastore schema initialization to 2.1.0
Initialization script hive-schema-2.1.0.mysql.sql
Error: Duplicate key name 'PCS_STATS_IDX' (state=42000,code=1061)
org.apache.hadoop.hive.metastore.HiveMetaException: Schema initialization FAILED! Metastore state would be inconsistent !!
Underlying cause: java.io.IOException : Schema script failed, errorcode 2
Use --verbose for detailed stacktrace.
*** schemaTool failed ***

总结了一下，只要按照以上步骤配置，一般报错都是在hive-site.xml配置时所配置的mysql信息和实际的不对应，所以会报错。另外如果配置好了，启动了hive的服务和客户端做了很多操作然后再关闭，再次启动初始化数据库时也会报错，这个时候最好的方法是删除掉mysql的与hive对应的数据库实例，然后新建一个相同的即可。
如果出现以下信息则是数据库的问题

java.sql.SQLException: Access denied for user 'root'@'****' (using password: YES)

这是因为mysql在验证用户登陆的时候，首先是验证host列，如果host列在验证user列，再password列，而现在按照我之前的连接语句：按照host列找到为空的那列（空匹配所有用户名），所以匹配到了这条记录，然后发现这条记录的密码为空，而我的语句里面有密码，那么就会报错。
解决方案:

mysql> use mysql;
Database changed
mysql> delete from user where user='';
Query OK, 1 row affected (0.00 sec)
mysql> flush privileges;
Query OK, 0 rows affected (0.00 sec)

出现以下信息则安装配置成功

[root@slave1 bin]# schematool -initSchema -dbType mysql
which: no hbase in (/home/hadoop/sqoop-1.4.6/bin:/home/hadoop/apache-hive-2.1.1-bin/bin:/home/hadoop/hadoop-2.7.3/bin:/home/hadoop/jdk1.8.0_144/bin:/usr/local/sbin:/usr/local/bin:/sbin:/bin:/usr/sbin:/usr/bin:/root/bin)
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/home/hadoop/apache-hive-2.1.1-bin/lib/log4j-slf4j-impl-2.4.1.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/home/hadoop/hadoop-2.7.3/share/hadoop/common/lib/slf4j-log4j12-1.7.10.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.apache.logging.slf4j.Log4jLoggerFactory]
Metastore connection URL:	 jdbc:mysql://localhost:3306/hive?createDatabaseIfNotExist=true&characterEncoding=UTF-8&useSSL=false
Metastore Connection Driver :	 com.mysql.jdbc.Driver
Metastore connection User:	 hive
Starting metastore schema initialization to 2.1.0
Initialization script hive-schema-2.1.0.mysql.sql
Initialization script completed
schemaTool completed

7. 启动hive服务和客户端并创建数据库和一张表

$: hiveserver2
$: hive
hive> create database dock；
hive> use dock;
hive> create table if not exists dock.dock_tb(
    > id varchar(64) COMMENT 'dock id',
    > md5code varchar(64) COMMENT 'dock md5 code',
    > number varchar(64) COMMENT 'dock number',
    > ip varchar(64) COMMENT 'dock ip',
    > game varchar(64) COMMENT 'dock game',
    > time varchar(64) COMMENT 'dock time',
    > day varchar(64) COMMENT 'dock day',
    > year varchar(64) COMMENT 'dock year',
    > month varchar(64) COMMENT 'dock month',
    > type varchar(64) COMMENT 'dock type')
    > COMMENT 'Description of the table'
    > LOCATION '/data/wscn/dock_test_log/20171101/EtlResult/dockClick';

可以看到dock_tb表以HDFS上/data/wscn/dock_test_log/20171101/EtlResult/dockClick下的文件作为数据源和存储路径。

安装配置sqoop

1. 解压并配置环境变量

$: tar –zxvf sqoop-1.4.6.bin__hadoop-2.0.4-alpha.tar.gz
$: mv sqoop-1.4.6.bin__hadoop-2.0.4-alpha sqoop-1.4.6
$: export SQOOP_HOME=/home/hadoop/sqoop-1.4.6
$: export PATH=$PATH:${ SQOOP_HOME }/bin

2. 配置基本信息

$:cd /home/hadoop/sqoop-1.4.6/conf

如下配置,默认是被注释的

#Set path to where bin/hadoop is available
export HADOOP_COMMON_HOME=/home/hadoop/hadoop-2.7.3

#Set path to where hadoop-*-core.jar is available
export HADOOP_MAPRED_HOME=/home/hadoop/hadoop-2.7.3

#set the path to where bin/hbase is available
#export HBASE_HOME=

#Set the path to where bin/hive is available
export HIVE_HOME=/home/hadoop/apache-hive-2.1.1-bin

3. 配置完成后测试

$: sqoop help

如果出现以下信息证明安装配置成功

Warning: /home/hadoop/sqoop-1.4.6/bin/../../hbase does not exist! HBase imports will fail.
Please set $HBASE_HOME to the root of your HBase installation.
Warning: /home/hadoop/sqoop-1.4.6/bin/../../hcatalog does not exist! HCatalog jobs will fail.
Please set $HCAT_HOME to the root of your HCatalog installation.
Warning: /home/hadoop/sqoop-1.4.6/bin/../../accumulo does not exist! Accumulo imports will fail.
Please set $ACCUMULO_HOME to the root of your Accumulo installation.
Warning: /home/hadoop/sqoop-1.4.6/bin/../../zookeeper does not exist! Accumulo imports will fail.
Please set $ZOOKEEPER_HOME to the root of your Zookeeper installation.
17/11/11 02:26:22 INFO sqoop.Sqoop: Running Sqoop version: 1.4.6
usage: sqoop COMMAND [ARGS]

Available commands:
  codegen            Generate code to interact with database records
  create-hive-table  Import a table definition into Hive
  eval               Evaluate a SQL statement and display the results
  export             Export an HDFS directory to a database table
  help               List available commands
  import             Import a table from a database to HDFS
  import-all-tables  Import tables from a database to HDFS
  import-mainframe   Import datasets from a mainframe server to HDFS
  job                Work with saved jobs
  list-databases     List available databases on a server
  list-tables        List available tables in a database
  merge              Merge results of incremental imports
  metastore          Run a standalone Sqoop metastore
  version            Display version information

See 'sqoop help COMMAND' for information on a specific command.

利用sqoop将HDFS上格式化后的数据导入到mysql，前提是mysql事先有对应的表

sqoop export --connect jdbc:mysql://127.0.0.1:3306/hive --username hive --password hive --table dock_tb1 --export-dir hdfs://127.0.0.1:9000/data/wscn/dock_test_log/20171101/EtlResult/dockClick --input-fields-terminated-by '01'

利用sqoop将mysql的数据导入到hdfs

$: sqoop import --connect jdbc:mysql://127.0.0.1:3306/hive --username hive --password hive --table dock_tb --target-dir /data/wscn/dock_test_log/20171101/EtlResult/dockClick1 -m 1

具体的sqoop命令参照http://blog.csdn.net/whiteForever/article/details/52609422