hive安装 jdbc链接hive

1. 下载hive安装包

2. 进入 conf 中  ：  cp hive-default.xml.template hive-site.xml，  vi hive-site.xml

1） 找到如下对应的配置修改对应的值  （例如：  /javax.jdo.option.ConnectionURL）

<property>
　　<name>javax.jdo.option.ConnectionUserName</name>
　　<value>root</value>
</property>
<property>
　　<name>javax.jdo.option.ConnectionPassword</name>
　　<value>Gw_sp1226</value>
</property>
<property>
　　<name>javax.jdo.option.ConnectionURL</name>
　　<value>jdbc:mysql://gw-sp.novalocal:3306/hive</value>
</property>
<property>
　　<name>javax.jdo.option.ConnectionDriverName</name>
　　<value>com.mysql.jdbc.Driver</value>
</property>

 

3.  cp hive-env.sh.template hive-env.sh,    vi  hive-env.sh

export HADOOP_HOME=/home/hadoop/hadoop   ##Hadoop安装路径

export HIVE_CONF_DIR=/home/hadoop/hive-2.1.1/conf    ##Hive配置文件路径
export HIVE_AUX_JARS_PATH=/usr/hive/apache-hive-2.2.0-bin/lib   ##Hive lib 目录

4. 拷贝mysql-connector-java-5.1.7-bin.jar到hive的lib包中，（格式化json需要多加2个jar包json-serde-1.3.8-jar-with-dependencies.jar 和json-udf-1.3.8-jar-with-dependencies.jar， 具体参考如下flume存储数据到hive）

链接：https://pan.baidu.com/s/1suPzGJmtJlsROC6SVpcztQ 密码：zlgg

目标：  通过接受 1084端口的http请求信息， 存储到 hive数据库中，
osgiweb2.db为hive中创建的数据库名称
periodic_report5 为创建的数据表，

flume配置如下：
a1.sources=r1  
a1.channels=c1  
a1.sinks=k1  
  
a1.sources.r1.type = http
a1.sources.r1.bind = 0.0.0.0
a1.sources.r1.port = 1084
a1.sources.r1.handler=jkong.Test.HTTPSourceDPIHandler  

#a1.sources.r1.interceptors=i1 i2
#a1.sources.r1.interceptors.i1.type=regex_filter 
#a1.sources.r1.interceptors.i1.regex=\\{.*\\} 
#a1.sources.r1.interceptors.i2.type=timestamp
a1.channels.c1.type=memory  
a1.channels.c1.capacity=10000  
a1.channels.c1.transactionCapacity=1000  
a1.channels.c1.keep-alive=30  
  
a1.sinks.k1.type=hdfs  
a1.sinks.k1.channel=c1  
a1.sinks.k1.hdfs.path=hdfs://gw-sp.novalocal:1086/user/hive/warehouse/osgiweb2.db/periodic_report5 
a1.sinks.k1.hdfs.fileType=DataStream  
a1.sinks.k1.hdfs.writeFormat=Text  
a1.sinks.k1.hdfs.rollInterval=0  
a1.sinks.k1.hdfs.rollSize=10240  
a1.sinks.k1.hdfs.rollCount=0  
a1.sinks.k1.hdfs.idleTimeout=60

a1.sources.r1.channels=c1
a1.sinks.k1.channel=c1
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 2.  数据表创建：

create table periodic_report5(id BIGINT, deviceId STRING,report_time STRING,information STRING) row format serde "org.openx.data.jsonserde.JsonSerDe" WITH SERDEPROPERTIES("id"="$.id","deviceId"="$.deviceId","report_time"="$.report_time","information"="$.information"); 
　　2.1  将数据表中的字段也同样拆分成数据字段的创表语句（还没有试验， 暂时不用）

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create table periodic_report4(id BIGINT, deviceId STRING,report_time STRING,information STRUCT<actualTime:BIGINT,dpiVersionInfo:STRING,subDeviceInfo:STRING,wanTrafficData:STRING,ponInfo:STRING,eventType:STRING,potsInfo:STRING,deviceInfo:STRING,deviceStatus:STRING>) row format serde "org.openx.data.jsonserde.JsonSerDe" WITH SERDEPROPERTIES("input.invalid.ignore"="true","id"="$.id","deviceId"="$.deviceId","report_time"="$.report_time","requestParams.actualTime"="$.requestParams.actualTime","requestParams.dpiVersionInfo"="$.requestParams.dpiVersionInfo","requestParams.subDeviceInfo"="$.requestParams.subDeviceInfo","requestParams.wanTrafficData"="$.requestParams.wanTrafficData","requestParams.ponInfo"="$.requestParams.ponInfo","requestParams.eventType"="$.requestParams.eventType","requestParams.potsInfo"="$.requestParams.potsInfo","requestParams.deviceInfo"="$.requestParams.deviceInfo","requestParams.deviceStatus"="$.requestParams.deviceStatus"); 
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3. 启动flume语句：flume 根目录

bin/flume-ng agent --conf ./conf/ -f ./conf/flume.conf --name a1 -Dflume.root.logger=DEBUG,console
4. 启动hive语句: hive bin目录

hive    或者：
./hive -hiveconf hive.root.logger=DEBUG,console  #带log信息启动

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