（十一）Hive数据仓库的使用

古城微笑少年丶 2023-06-20 06:48 5阅读 0赞

**目录**

一、目的及要求：

目的：

要求：

二、环境要求：

所需环境：

集群规划：

三、详细步骤：

步骤一：启动

步骤二：数据仓库的使用

1、查看表信息

2、hive常用命令

3、Hive的数据模型\_内部表；

4、Hive的数据模型\_分区表

5、Hive的数据模型\_外部表

6、Hive的数据模型\_桶表

7、Hive的数据模型\_视图

四、总结

# 一、目的及要求： #

## 目的： ##

**        掌握数据仓库Hive的使用**

## 要求： ##

1.**掌握数据仓库Hive的使用；**

**        2.能够正常操作数据库、表、数据。**

# 二、环境要求： #

## **所需环境：** ##

1.  **五台独立PC式虚拟机；**
2.  **主机之间有有效的网络连接；**
3.  **每台主机内存2G以上，磁盘剩余空间500M以上；**
4.  **所有主机上安装CentOS7-64位操作系统；**
5.  **已完成Hadoop平台的搭建；**
6.  **已完成MySQL数据库平台的搭建；**
7.  **已完成Hive数据仓库的安装。**

## 集群规划： ##

<table style="margin-left:6.75pt;width:510px;"> 
 <tbody> 
 <tr> 
 <td style="border-color:#FFFFFF;width:117.05pt;"> 主机名 </td> 
 <td style="border-color:#FFFFFF;width:138.2pt;"> IP地址 </td> 
 <td style="border-color:#FFFFFF;width:127.6pt;"> 服务描述 </td> 
 </tr> 
 <tr> 
 <td style="border-color:#FFFFFF;width:117.05pt;"> Cluster-01 </td> 
 <td style="width:138.2pt;"> 192.168.10.111 </td> 
 <td style="width:127.6pt;"> MC管理节点 </td> 
 </tr> 
 <tr> 
 <td style="border-color:#FFFFFF;width:117.05pt;"> Cluster-02 </td> 
 <td style="width:138.2pt;"> 192.168.10.112 </td> 
 <td style="width:127.6pt;"> MC数据服务节点 </td> 
 </tr> 
 <tr> 
 <td style="border-color:#FFFFFF;width:117.05pt;"> Cluster-03 </td> 
 <td style="width:138.2pt;"> 192.168.10.113 </td> 
 <td style="width:127.6pt;"> MC数据服务节点 </td> 
 </tr> 
 <tr> 
 <td style="border-color:#FFFFFF;width:117.05pt;"> Cluster-04 </td> 
 <td style="width:138.2pt;"> 192.168.10.113 </td> 
 <td style="width:127.6pt;"> MC SQL服务节点 </td> 
 </tr> 
 <tr> 
 <td style="border-color:#FFFFFF;width:117.05pt;"> Cluster-05 </td> 
 <td style="width:138.2pt;"> 192.168.10.114 </td> 
 <td style="width:127.6pt;"> MC SQL服务节点 </td> 
 </tr> 
 </tbody> 
</table>

# 三、详细步骤： #

## **步骤一：启动** ##

**Hadoop****、Hbase、Hive、Sqoop使用使用专门用于集群的用户admin进行。**

**启动HBase集群之前首先确保Zookeeper集群已被开启状态。 （实验5台）**

**Zookeeper****的启动需要分别在每个计算机的节点上手动启动。如果家目录下执行启动报错，则需要进入zookeeper/bin目录执行启动命令。**

**启动HBase集群之前首先确保Hadoop集群已被开启状态。 （实验5台）**

**Hadoop****只需要在主节点执行启动命令。**

**1****、集群中所有主机上使用命令“zkServer.sh start”启动Zookeeper服务的脚本，使用命令“zkServer.sh status”查看该节点Zookeeper服务当前的状态，若集群中只有一个“leader”节点，其余的均为“follower”节点，则集群的工作状态正常；**

![201912091139274.png][]

![201912091139278.png][]

![2019120911392718.png][]

![2019120911392741.png][]

![20191209113924298.png][]

**2****、在主节点使用“$start-all.sh”，备用主节点使用“$yarn-daemon.sh start resourcemanager”命令,启动Hadoop集群，在主节点查看Java进程信息，若有名为“NameNode”、“ResourceManager”的两个进程，则表示Hadoop集群的主节点启动成功。在每台数据节点，若有名为“DataNode”和“NodeManager”的两个进程，则表示Hadoop集群的数据节点启动成功；**

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTMyOTc1OA_size_16_color_FFFFFF_t_70][]

![2019120911392755.png][]

![2019120911392771.png][]** **

![20191209113922403.png][]

![2019120911392780.png][]

![2019120911392781.png][]

![2019120911392780.png][]

**3****、确定Hadoop集群已启动状态，然后在主节点使用此命令,启动HBase集群。并在集群中所有主机上使用命令“jps”查看进程；**

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTMyOTc1OA_size_16_color_FFFFFF_t_70 1][]

![20191209113927101.png][]**  **

![20191209113924358.png][]

![20191209113927104.png][]

![20191209113927120.png][]

![20191209113927126.png][]

**4****、****用root用户登录，并开启mysql集群，并在管理主机上查看集群是否全部已连接；**

![20191209113927124.png][]

![20191209113923306.png][]

![20191209113927134.png][]

![20191209113924391.png][]

![20191209113927140.png][]

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTMyOTc1OA_size_16_color_FFFFFF_t_70 2][]

**5、在主节点使用命令“hive”启动Hive，启动成功后能够进入Hive的控制台；**

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTMyOTc1OA_size_16_color_FFFFFF_t_70 3][]

**6、****在控制台中使用命令“show databases;”查看当前的数据库列表；**

![20191209113927171.png][]

## **步骤二：数据仓库的使用** ##

### **1****、查看表信息** ###

**在http://192.168.10.111:50070/查看表信息；**

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTMyOTc1OA_size_16_color_FFFFFF_t_70 4][]

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTMyOTc1OA_size_16_color_FFFFFF_t_70 5][]

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTMyOTc1OA_size_16_color_FFFFFF_t_70 6][]

### **2****、hive常用命令** ###

**（1）修改参数允许强制分桶，也可以修改hive\_site.xml文件中的参数改为true；**

** ** ![20191209114837975.png][]

**（2）创建数据库；**

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTMyOTc1OA_size_16_color_FFFFFF_t_70 7][]

**（3）使用数据库；**

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTMyOTc1OA_size_16_color_FFFFFF_t_70 8][]

**（4）创建表；**

![20191209114840751.png][]

**（5）删除表；**

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTMyOTc1OA_size_16_color_FFFFFF_t_70 9][]

**（6）删除数据库；**

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTMyOTc1OA_size_16_color_FFFFFF_t_70 8][]

**（7）修改配置文件，使在导入数据的工程中，如果在见表的过程中没有指定location，那么就会在hive.metastore.warehouse.dir指定路径下，以表名创建一个文件夹，之后所有的数据就会存储在此文件夹中；**

**配置文件“/home/admin/hive/apache-hive-2.1.1-bin/conf/hive-site.xml”**

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTMyOTc1OA_size_16_color_FFFFFF_t_70 10][]

### **3****、Hive的数据模型\_内部表；** ###

**练习：启动Hive，启动成功后能够进入Hive的控制台**

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTMyOTc1OA_size_16_color_FFFFFF_t_70 11][]

**（1）****创建数据库，并使用数据库test2；**

** ** ![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTMyOTc1OA_size_16_color_FFFFFF_t_70 12][]

**（2）****创建数据库，并使用数据库test3；**

** ** ![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTMyOTc1OA_size_16_color_FFFFFF_t_70 13][]

**（3）创建表t1、t2、t3、t4；**

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTMyOTc1OA_size_16_color_FFFFFF_t_70 14][]

**（4）查看hadoop集群中Hive仓库中的表；**

![20191209115436997.png][]

![20191209115436188.png][]

![20191209115440716.png][]

**（5）向t1表中添加列，并显示表信息；** ![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTMyOTc1OA_size_16_color_FFFFFF_t_70 15][]

**（6）查看/user/hive/warehouse/目录下的test2.db和test3.db文件夹；**![20191209115440836.png][]

### **4****、Hive的数据模型\_分区表** ###

**（1）创建数据库test4,并在test4数据库中准备表数据;**

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTMyOTc1OA_size_16_color_FFFFFF_t_70 16][]

**（2）准备文本数据：admin用户家目录下新建sampledata.txt;**

![20191209115440761.png][]

** ** ![20191209115440769.png][]

**（3）将文本数据插入到数据表；**

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTMyOTc1OA_size_16_color_FFFFFF_t_70 17][]

**（4）向分区表中插入数据；**

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTMyOTc1OA_size_16_color_FFFFFF_t_70 18][]

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTMyOTc1OA_size_16_color_FFFFFF_t_70 19][]

** **![20191209115440814.png][]

**（5）查看表的分区信息；**

![2019120911543854.png][]

**（6）登录http://192.168.10.111:8088/cluster/apps可以查看job执行状态；**

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTMyOTc1OA_size_16_color_FFFFFF_t_70 19][]

### **5****、Hive的数据模型\_外部表** ###

** ****（1）准备数据：在admin家目录下分别新建student1.txt、student2.txt、student3.txt、内容：**

**student1.txt****内容： Tom，M，60,80,96**

**Mary****，F，11,22,33**

**student2.txt****内容： Jerry，M，90,11,23**

**student3.txt****内容： Rose，M，78,77,76**

**Mike****，F，99,98,98**

** **![20191209115440785.png][]![20191209115440751.png][]

** **![20191209115440831.png][]![20191209115440750.png][]

** **![20191209115438102.png][]![20191209115440781.png][]

**（2）在hdfs上创建input目录，将文件放入HDFS文件系统；**

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTMyOTc1OA_size_16_color_FFFFFF_t_70 20][]

**（3）创建数据库test5,并在数据库test5中创建外部表external\_student，并查询；**

![20191209115440830.png][]

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTMyOTc1OA_size_16_color_FFFFFF_t_70 21][]

**（4）删除HDFS上的student1.txt；**

![20191209115440862.png][]

**（5）查询外部表；**

![20191209115440829.png][]

**（6）将student.txt重新放入HDFS input目录下；**

** ** ![20191209115440833.png][]![20191209115440816.png][]

**（7）查询外部表；**

** ** ![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTMyOTc1OA_size_16_color_FFFFFF_t_70 22][]

### **6****、Hive的数据模型\_桶表** ###

**（1）创建数据库test6,并新建一个非桶表；**

![20191209115440834.png][]

![2019120911543713.png][]

**（2）在admin用户家目录下新建user.txt内容；**

![20191209115440836.png][]![20191209115440821.png][]

**（3）将文本数据插入到非桶数据表；**

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTMyOTc1OA_size_16_color_FFFFFF_t_70 23][]

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTMyOTc1OA_size_16_color_FFFFFF_t_70 24][]

**（4）查看桶表**

![20191209115440856.png][]

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTMyOTc1OA_size_16_color_FFFFFF_t_70 25][]

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTMyOTc1OA_size_16_color_FFFFFF_t_70 26][]

### **7****、Hive的数据模型\_视图** ###

**（1）创建数据库test7,在test7中创建一个测试表test01,查看表结构；**

![20191209115440913.png][]

**（2）在admin用户的家目录下准备文本数据data1.txt;**

![20191209115440892.png][]** **![20191209115440855.png][]

**（3）将文本数据导入 test01表，并查询test01表；**

** ** ![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTMyOTc1OA_size_16_color_FFFFFF_t_70 27][]

**（4）创建一个View之前，使用explain命令查看创建View的命令是如何被Hive解释执行的；**

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTMyOTc1OA_size_16_color_FFFFFF_t_70 28][]

**（5）实际创建一个View；**

** ** ![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTMyOTc1OA_size_16_color_FFFFFF_t_70 29][]

**（6）执行View之前，先explain查看实际被翻译后的执行过程；**

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTMyOTc1OA_size_16_color_FFFFFF_t_70 30][]

**（7）最后，对View执行一次查询，显示Stage-1阶段对原始表test进行了MapReduce过程；**

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTMyOTc1OA_size_16_color_FFFFFF_t_70 31][]

**（8）登录http://192.168.10.111:8088/cluster/apps可以查看job执行状态；**

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl8zOTMyOTc1OA_size_16_color_FFFFFF_t_70 24][]

# 四、总结 #

**问题一：**

\[root@localhost65apache-hive-2.1.1-bin\]\# hive

SLF4J: Class pathcontains multiple SLF4J bindings.

SLF4J: Found binding in\[jar:file:/usr/local/apache-hive-2.1.1-bin/lib/log4j-slf4j-impl-2.4.1.jar!/org/slf4j/impl/StaticLoggerBinder.class\]

SLF4J: Found bindingin\[jar:file:/usr/local/hadoop-2.6.2/share/hadoop/common/lib/slf4j-log4j12-1.7.5.jar!/org/slf4j/impl/StaticLoggerBinder.class\]

SLF4J: Seehttp://www.slf4j.org/codes.html\#multiple\_bindings for an explanation.

SLF4J: Actual bindingis of type \[org.apache.logging.slf4j.Log4jLoggerFactory\]

Logging initializedusing configuration in file:/usr/local/apache-hive-2.1.1-bin/conf/hive-log4j2.propertiesAsync: true

Exception in thread"main" java.lang.RuntimeException:org.apache.hadoop.hive.ql.metadata.HiveException: java.lang.RuntimeException:Unable to instantiate org.apache.hadoop.hive.ql.metadata.SessionHiveMetaStoreClient

atorg.apache.hadoop.hive.ql.session.SessionState.start(SessionState.java:591)

································

The last packet sentsuccessfully to the server was 0 milliseconds ago.

**原因分析：****hive****中的日志和hadoop中日志包冲突导致**

**解决方法：****将hive中的日志包去除即可(不要删除，修改名称即可)。如下：**

\[admin@Cluster-01apache-hive-2.1.1-bin\]\#mv/usr/local/apache-hive-2.1.1-bin/lib/log4j-slf4j-impl-2.4.1.jar/usr/local/apache-hive-2.1.1-bin/lib/log4j-slf4j-impl-2.4.1.jar.bak

\[admin@Cluater-01apache-hive-2.1.1-bin\]\#

**问题二：****启动hive正常，进mysql查看hive元数据库myhive也正常,但在hive中执行show databases指令报如下错误：**

![20191209115947376.png][]

**解决方案：****经过报错信息分析发现是metastore服务没有启动。**

**启动metastore（进安装hive的bin目录下执行以下命令）：**

**bin/hive --service metastore &**

**启动metastore后再启动hive，然后就可以正常执行show databases指令**

[201912091139274.png]: https://img-blog.csdnimg.cn/201912091139274.png
[201912091139278.png]: https://img-blog.csdnimg.cn/201912091139278.png
[2019120911392718.png]: https://img-blog.csdnimg.cn/2019120911392718.png
[2019120911392741.png]: https://img-blog.csdnimg.cn/2019120911392741.png
[20191209113924298.png]: https://img-blog.csdnimg.cn/20191209113924298.png
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