ubuntu14.04下Hadoop2.6.0+Hive1.1.1安装

1.Hive是基于Hadoop构建的一套数据仓库分析系统，它提供了丰富的SQL查询方式来分析存储在Hadoop 分布式文件系统中的数据。其在Hadoop的架构体系中承担了一个SQL解析的过程，它提供了对外的入口来获取用户的指令然后对指令进行分析，解析出一个MapReduce程序组成可执行计划，并按照该计划生成对应的MapReduce任务提交给Hadoop集群处理，获取最终的结果。元数据——如表模式——存储在名为metastore的数据库中。
2.下载http://mirror.bjtu.edu.cn/apache/hive/
解压到/usr/local/hadoop/hive
3.拷贝mysql-connector-java-5.1.6-bin.jar 到hive 的lib下面
4.将hive下的新版本jline的JAR包拷贝到hadoop下：
cp /usr/local/hadoop/hive /lib/jline-2.12.jar  /usr/local/hadoop /share/hadoop/yarn/lib 并且移除$HADOOP_HOME/share/hadoop/yarn/lib/下的jline-0.9.94.jar文件
5.gedit ~/.bashrc
#HADOOP VARIABLES START  
export JAVA_HOME=/jdk/jdk1.8.0_91  
export HADOOP_INSTALL=/usr/local/hadoop  
export PATH=$PATH:$HADOOP_INSTALL/bin 
export PATH=$PATH:$JAVA_HOME/bin  
export PATH=$PATH:$HADOOP_INSTALL/sbin 
export HADOOP_MAPRED_HOME=$HADOOP_INSTALL 
export HADOOP_COMMON_HOME=$HADOOP_INSTALL 
export HADOOP_HDFS_HOME=$HADOOP_INSTALL 
export YARN_HOME=$HADOOP_INSTALL 
exportHADOOP_COMMON_LIB_NATIVE_DIR=$HADOOP_INSTALL/lib/native 
exportHADOOP_OPTS="-Djava.library.path=$HADOOP_INSTALL/lib" 
#HADOOP VARIABLES END
#set Hive environment
export HIVE_HOME=/usr/local/hadoop/hive
export PATH=$PATH:$HIVE_HOME/bin
export CLASSPATH=$CLASSPATH:$HIVE_HOME/bin
6.gedit /etc/profile
#set java environment
export JAVA_HOME=/jdk/jdk1.8.0_91
export JRE_HOME=$JAVA_HOME/jre
exportCLASSPATH=$CLASSPATH:$JAVA_HOME/lib:$JRE_HOME/lib
export PATH=$PATH:$JAVA_HOME/bin:$JRE_HOME/bin
#set hive
export HIVE_HOME=/usr/local/hadoop/hive
export PATH=$HIVE_HOME/bin:$PATH
7.重命名配置文件
对conf 目录下的配置文件重命名，执行如下命令：
mv hive-env.sh.template hive-env.sh
mv hive-default.xml.template hive-site.xml
8.在hive-env.sh中
HADOOP_HOME=/usr/local/hadoop
export HIVE_CONF_DIR=/usr/local/hadoop/hive/conf
9.修改hive-site.xml
  <property>
    <name>hive.exec.scratchdir</name>
   <value>/usr/local/hadoop/hive/tmp</value>
    <description>HDFS rootscratch dir for Hive jobs which gets created with write all (733) permission.For each connecting user, an HDFS scratch dir:${hive.exec.scratchdir}/&lt;username&gt; is created, with${hive.scratch.dir.permission}.</description>
  </property>
  <property>
   <name>hive.exec.local.scratchdir</name>
   <value>/usr/local/hadoop/hive/tmp</value>
    <description>Local scratchspace for Hive jobs</description>
  </property>
  <property>
   <name>hive.downloaded.resources.dir</name>
   <value>/usr/local/hadoop/hive/tmp</value>
      Maximum number of bytes ascript is allowed to emit to standard error (per map-reduce task).
      This prevents runaway scriptsfrom filling logs partitions to capacity
    </description>
  </property>
  <property>
   <name>hive.metastore.warehouse.dir</name>
   <value>/usr/local/hadoop/hive/warehouse</value>
    <description>location ofdefault database for the warehouse</description>
  </property>
  <property>
   <name>hive.metastore.uris</name>
   <value>thrift://127.0.0.1:9083</value>
    <description>Thrift URIfor the remote metastore. Used by metastore client to connect to remotemetastore.</description>
  </property>
 <property>
   <name>hive.metastore.local</name>
    <value>true</value>
   <description></description>
  </property>
  <property>
   <name>javax.jdo.option.ConnectionPassword</name>
   <value>myhive</value>
    <description>password touse against metastore database</description>
  </property>
  <property>
   <name>javax.jdo.option.ConnectionURL</name>  <value>jdbc:mysql://localhost:3306/hive?createDatabaseIfNotExsit=true;characterEncoding=UTF-8</value>
    <description>JDBC connectstring for a JDBC metastore</description>
  </property>
 <property>
   <name>javax.jdo.option.ConnectionUserName</name>
   <value>myhive</value>
    <description>Username touse against metastore database</description>
  </property>