Apache Hive 快速入门

时间:2022-05-03
本文章向大家介绍Apache Hive 快速入门，主要内容包括第 63 章 Apache Hive、基本概念、基础应用、原理机制和需要注意的事项等，并结合实例形式分析了其使用技巧，希望通过本文能帮助到大家理解应用这部分内容。

本文节选自《Netkiller Database 手札》

CentOS 7.3 + Server JRE 1.8 + Hadoop-2.8.0 + Hive-2.1.1

第 63 章 Apache Hive

目录

  • 63.1. 安装 Apache Hive
    • 63.1.1. MySQL
    • 63.1.2. Hadoop
    • 63.1.3. Hive
    • 63.1.4. 启动 Hive
    • 63.1.5. 访问 Hive
  • 63.2. 管理 Hive
    • 63.2.5.1. HDFS 目录迁移
    • 63.2.5.2. 导出表数据到本地文件
    • 63.2.5.3.
    • 63.2.4.1. 从文本文件导入数据
    • 63.2.4.2. 从其他表查询数据并创建新表
    • 63.2.4.3. 从其他表查询数据然后插入指定表中
    • 63.2.4.4.
    • 63.2.3.1. 创建视图
    • 63.2.3.2. 删除视图
    • 63.2.2.1. 创建分区表
    • 63.2.2.2. 显示分区情况
    • 63.2.2.3. 增加分区
    • 63.2.2.4. 向分区表导入数据
    • 63.2.1.1. 创建表
    • 63.2.1.2. 显示表
    • 63.2.1.3. 删除表
    • 63.2.1.4. 查看表结构
    • 63.2.1.5. 为表增加字段
    • 63.2.1.6. 修改表名称
    • 63.2.1.7. 使用已有表结构创建新表
    • 63.2.1. 表管理
    • 63.2.2. 分区表
    • 63.2.3. 视图管理
    • 63.2.4. 数据管理
    • 63.2.5. HDFS与本地文件系统管理
  • 63.3. HiveQL - Hive查询语言
    • 63.3.1. JOIN 连接查询
    • 63.3.2. 子查询

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。

63.1. 安装 Apache Hive

安装 Apache Hive 需要 Hadoop和MySQL，这里假设你已经懂得如何安装Hadoop和MySQL，所以一下将采用Netkiller OSCM一件安装脚本来初始化Hadoop和MySQL,如果需要详细的安装步骤请参考笔者的相关文章。

63.1.1. MySQL

默认情况下, Hive 使用内嵌的 Derby 数据库保存元数据, 通常生产环境会使用 MySQL 来存放 Hive 元数据。

使用下面脚本一键安装MySQL 5.7 安装后会显示mysql的初始密码，是所有初始密码登陆后修改为你的需要密码

			curl -s https://raw.githubusercontent.com/oscm/shell/master/database/mysql/5.7/mysql.server.sh | bash

2016-02-16T08:22:58.253030Z 1 [Note] A temporary password is generated for root@localhost: sd%%my.Ak7Ma

安装 MySQL JDBC 连接库。

			curl -s https://raw.githubusercontent.com/oscm/shell/master/database/mysql/5.7/mysql-connector-java.sh | bash

创建一个 hive 数据库用来存储 Hive 元数据，且数据库访问的用户名和密码都为 hive。

			mysql> CREATE DATABASE hive; 
Query OK, 1 row affected (0.03 sec)

创建用户hive并授权访问hive数据库

			mysql> CREATE USER 'hive'@'localhost' IDENTIFIED BY 'hive';
Query OK, 0 rows affected (0.04 sec)

mysql> GRANT ALL ON hive.* TO 'hive'@'localhost' IDENTIFIED BY 'hive';
Query OK, 0 rows affected (0.01 sec)

mysql> GRANT ALL ON hive.* TO 'hive'@'%' IDENTIFIED BY 'hive';
Query OK, 0 rows affected (0.00 sec)

mysql> FLUSH PRIVILEGES;
Query OK, 0 rows affected (0.00 sec)

mysql> quit;
Bye

63.1.2. Hadoop

安装 Hadoop 采用单机模式

			curl -s https://raw.githubusercontent.com/oscm/shell/master/distributed/hadoop/hadoop-2.8.0.sh | bash
curl -s https://raw.githubusercontent.com/oscm/shell/master/distributed/hadoop/single.sh | bash
curl -s https://raw.githubusercontent.com/oscm/shell/master/distributed/hadoop/startup.sh | bash

63.1.3. Hive

可以从 Apache 镜像站点中下载最新稳定版的 apache-hive-2.1.1-bin.tar.gz

			cd /usr/local/src
wget http://mirrors.hust.edu.cn/apache/hive/stable-2/apache-hive-2.1.1-bin.tar.gz

tar zxf apache-hive-2.1.1-bin.tar.gz
mv apache-hive-2.1.1-bin /srv/apache-hive-2.1.1
ln -s /srv/apache-hive-2.1.1/ /srv/apache-hive
chown hadoop:hadoop -R /srv/apache-hive-2.1.1			
			cat > /srv/apache-hive/conf/hive-env.sh <<'EOF'
export JAVA_HOME=/srv/java
export HADOOP_HOME=/srv/apache-hadoop
export HBASE_HOME=/srv/apache-hbase
export HIVE_HOME=/srv/apache-hive
export PATH=$PATH:$JAVA_HOME/bin:$HADOOP_HOME/bin:$HADOOP_HOME/sbin:$HIVE_HOME/bin
EOF

cat >> ~/.bash_profile <<'EOF'
export JAVA_HOME=/srv/java
export HADOOP_HOME=/srv/apache-hadoop
export HBASE_HOME=/srv/apache-hbase
export HIVE_HOME=/srv/apache-hive
export PATH=$PATH:$JAVA_HOME/bin:$HADOOP_HOME/bin:$HADOOP_HOME/sbin:$HIVE_HOME/bin
EOF

source ~/.bash_profile

安装JDBC驱动

			[root@localhost apache-hive]# ln -s  /usr/share/java/mysql-connector-java.jar /srv/apache-hive/lib/
[root@localhost apache-hive]# ll /srv/apache-hive/lib/mysql-connector-java.jar 
lrwxrwxrwx 1 root root 40 Jun 29 01:59 /srv/apache-hive/lib/mysql-connector-java.jar -> /usr/share/java/mysql-connector-java.jar

修改 hive-site.xml 配置文件，配置工作目录

  <property>
    <name>hive.querylog.location</name>
    <value>/tmp/live/hadoop</value>
    <description>Location of Hive run time structured log file</description>
  </property>
  <property>
    <name>hive.exec.local.scratchdir</name>
    <value>/tmp/hive</value>
    <description>Local scratch space for Hive jobs</description>
  </property>
  <property>
    <name>hive.downloaded.resources.dir</name>
    <value>/tmp/hive/${hive.session.id}_resources</value>
    <description>Temporary local directory for added resources in the remote file system.</description>
  </property>

  <property>
    <name>hive.querylog.location</name>
    <value>/user/hive/log</value>
    <description>Location of Hive run time structured log file</description>
  </property>

把默认的 Derby 修改为 MySQL 需要在该文件中配置 MySQL 数据库连接信息。

			<property>
    <name>javax.jdo.option.ConnectionURL</name>
    <value>jdbc:derby:;databaseName=metastore_db;create=true</value>
    <description>
      JDBC connect string for a JDBC metastore.
      To use SSL to encrypt/authenticate the connection, provide database-specific SSL flag in the connection URL.
      For example, jdbc:postgresql://myhost/db?ssl=true for postgres database.
    </description>
  </property>
  <property>
    <name>javax.jdo.option.ConnectionDriverName</name>
    <value>org.apache.derby.jdbc.EmbeddedDriver</value>
    <description>Driver class name for a JDBC metastore</description>
  </property>
  <property>
    <name>javax.jdo.option.ConnectionUserName</name>
    <value>APP</value>
    <description>Username to use against metastore database</description>
  </property>
  <property>
    <name>javax.jdo.option.ConnectionPassword</name>
    <value>mine</value>
    <description>password to use against metastore database</description>
  </property>

将上面配置项 value 改为下面的配置

  <property>
    <name>javax.jdo.option.ConnectionURL</name>
    <value>jdbc:mysql://localhost:3306/hive?createDatabaseIfNotExist=true&amp;characterEncoding=UTF-8&amp;useSSL=false</value>
  </property>
  <property>
    <name>javax.jdo.option.ConnectionDriverName</name>
    <value>com.mysql.jdbc.Driver</value>
  </property>
  <property>
    <name>javax.jdo.option.ConnectionUserName</name>
    <value>hive</value>
  </property>
  <property>
    <name>javax.jdo.option.ConnectionPassword</name>
    <value>hive</value>
  </property>

63.1.4. 启动 Hive

启动 Hive 前你必须做两件事，一是创建HDFS目录，二是初始化 MySQL 数据库。

为 Hive 创建 HDFS 工作目录并给它们赋相应的权限。

			[root@localhost ~]$ su - hadoop
[hadoop@localhost ~]$ /srv/apache-hadoop/bin/hdfs dfs -mkdir -p /user/hive/warehouse
[hadoop@localhost ~]$ /srv/apache-hadoop/bin/hdfs dfs -mkdir -p /tmp/hive
[hadoop@localhost ~]$ /srv/apache-hadoop/bin/hdfs dfs -chmod g+w /user/hive/warehouse
[hadoop@localhost ~]$ /srv/apache-hadoop/bin/hdfs dfs -chmod 777 /tmp/hive

初始化 MySQL 数据库

			[hadoop@localhost ~]$ /srv/apache-hive/bin/schematool -dbType mysql -initSchema
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/srv/apache-hive-2.1.1/lib/log4j-slf4j-impl-2.4.1.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/srv/apache-hadoop-2.8.0/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

63.1.5. 访问 Hive

启动 Hadoop

			[hadoop@localhost ~]$ /srv/apache-hadoop/sbin/start-all.sh 
This script is Deprecated. Instead use start-dfs.sh and start-yarn.sh
Starting namenodes on [localhost]
localhost: starting namenode, logging to /srv/apache-hadoop-2.8.0/logs/hadoop-hadoop-namenode-localhost.localdomain.out
localhost: starting datanode, logging to /srv/apache-hadoop-2.8.0/logs/hadoop-hadoop-datanode-localhost.localdomain.out
Starting secondary namenodes [0.0.0.0]
0.0.0.0: starting secondarynamenode, logging to /srv/apache-hadoop-2.8.0/logs/hadoop-hadoop-secondarynamenode-localhost.localdomain.out
starting yarn daemons
starting resourcemanager, logging to /srv/apache-hadoop-2.8.0/logs/yarn-hadoop-resourcemanager-localhost.localdomain.out
localhost: starting nodemanager, logging to /srv/apache-hadoop-2.8.0/logs/yarn-hadoop-nodemanager-localhost.localdomain.out

进入 Hive 然后输入 show databases; 测试安装是否正常。

			[hadoop@localhost conf]$ /srv/apache-hive/bin/hive
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/srv/apache-hive-2.1.1/lib/log4j-slf4j-impl-2.4.1.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/srv/apache-hadoop-2.8.0/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]

Logging initialized using configuration in file:/srv/apache-hive-2.1.1/conf/hive-log4j2.properties Async: true
Hive-on-MR is deprecated in Hive 2 and may not be available in the future versions. Consider using a different execution engine (i.e. spark, tez) or using Hive 1.X releases.
hive> show databases;
OK
default
Time taken: 0.264 seconds, Fetched: 1 row(s)
hive>

至此 Apache Hive 已经安装配置完成！

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