Hive的安装与使用-1

2018-04-26 14:47:56 浏览数 (1)

1.下载tar包，在客户端窗口上执行 wget -c http://archive.cloudera.com/cdh5/cdh/5/hive-1.1.0-cdh5.7.0.tar.gz 2.解压到app目录下 tar -zxvf hive-1.1.0-cdh5.7.0.tar.gz -C ~/app 3.配置~/.bash_profile

代码语言：javascript复制
export HIVE_HOME=/home/hadoop/app/hive-1.1.0-cdh5.7.0
export PATH=$HIVE_HOME/bin:$PATH

4.环境配置

代码语言：javascript复制
cd hive-1.1.0-cdh5.7.0/conf/
cp hive-env.sh.template hive-env.sh
vi hive-env.sh
代码语言：javascript复制
# Set HADOOP_HOME to point to a specific hadoop install directory
# HADOOP_HOME=${bin}/../../hadoop

  HADOOP_HOME=/home/hadoop/app/hadoop-2.6.0-cdh5.7.0

5.安装mysql，yum install mysql-xxx 6.配置hive-site.xml文件

代码语言：javascript复制
<configuration>
<property>
        <name>javax.jdo.option.ConnectionURL</name>
        <value>jdbc:mysql://hadoop000:3306/sparksql?createDatabaseIfNotExist=true</value>

</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>root</value>
        <description>username to use against metastore database</description>
</property>
<property>
        <name>javax.jdo.option.ConnectionPassword</name>
        <value>root</value>
        <description>password to use against metastore database</description>
</property>

</configuration>

7.拷贝数据库驱动到hive-1.1.0-cdh5.7.0/lib目录下 cp /home/hadoop/software/mysql-connector-java-5.1.27-bin.jar 8.启动hive，bin/hive

image.png

9.到mysql数据库里查看sparksql

代码语言：javascript复制
mysql> show databases;
 -------------------- 
| Database           |
 -------------------- 
| information_schema |
| azkaban            |
| hive               |
| mysql              |
| spark              |
| sparksql           |
| sqoop              |
| ss                 |
| test               |
 -------------------- 
9 rows in set (0.00 sec)

mysql> use sparksql
Database changed
mysql> show tables;
 --------------------------- 
| Tables_in_sparksql        |
 --------------------------- 
| BUCKETING_COLS            |
| CDS                       |
| COLUMNS_V2                |
| DATABASE_PARAMS           |
| DBS                       |
| FUNCS                     |
| FUNC_RU                   |
| GLOBAL_PRIVS              |
| PARTITIONS                |
| PARTITION_KEYS            |
| PARTITION_KEY_VALS        |
| PART_COL_STATS            |
| ROLES                     |
| SDS                       |
| SEQUENCE_TABLE            |
| SERDES                    |
| SKEWED_COL_NAMES          |
| SKEWED_COL_VALUE_LOC_MAP  |
| SKEWED_STRING_LIST        |
| SKEWED_STRING_LIST_VALUES |
| SKEWED_VALUES             |
| SORT_COLS                 |
| TAB_COL_STATS             |
| TBLS                      |
| VERSION                   |
 --------------------------- 
25 rows in set (0.00 sec)

10.在Hive中建表， create table hive_count(context string ); 报错：

FAILED: Execution Error, return code 1 from org.apache.hadoop.hive.ql.exec.DDLTask. MetaException(message:For direct MetaStore DB connections, we don't support retries at the client level.)

解决：

这是由于字符集的问题，需要配置MySQL的字符集： mysql> alter database hive character set latin1;

11.建好表以后，查看sparksql里的TBLS和COLUMNS_V2

image.png

12.查看hive官方文档

https://cwiki.apache.org/confluence/display/Hive/LanguageManual DML#LanguageManualDML-Loadingfilesintotables 从外部文件加载数据

代码语言：javascript复制
LOAD DATA [LOCAL] INPATH 'filepath' [OVERWRITE] INTO TABLE tablename [PARTITION (partcol1=val1, partcol2=val2 ...)]

13.在/home/hadoop/data/data.log下面有外部数据，把它导入到hive表里 LOAD DATA LOCAL INPATH '/home/hadoop/data/data.log' INTO TABLE hive_count;

14.select下结果：

image.png

15.hive ql提交执行后生成MR作业，并在yarn上运行。

代码语言：javascript复制
select word,count(1) from hive_count lateral view explode(split(context,'t')) wc as word group by word;

lateral view explode(split(context,'t')) :把每行记录按照指定分割符进行分解。

16.确认结果

image.png

yarn页面,

代码语言：javascript复制
http://hostname:8088/cluster/apps

image.png

html5 专用宿主机 hadoop hive 云数据库SQLServer

0 人点赞