Oozie

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尚硅谷大数据技术之Oozie

 

1Oozie简介

  Oozie英文翻译为:驯象人。一个基于工作流引擎的开源框架,由Cloudera公司贡献给Apache,提供对Hadoop MapReducePig Jobs的任务调度与协调。Oozie需要部署到Java Servlet容器中运行。主要用于定时调度任务,多任务可以按照执行的逻辑顺序调度。

2 Oozie的功能模块介绍

2.1 模块

1) Workflow

顺序执行流程节点,支持fork(分支多个节点),join(合并多个节点为一个)

2) Coordinator

定时触发workflow

3) Bundle Job

绑定多个Coordinator

2.2 常用节点

1) 控制流节点(Control Flow Nodes

控制流节点一般都是定义在工作流开始或者结束的位置,比如start,end,kill等。以及提供工作流的执行路径机制,如decisionforkjoin等。

2) 动作节点(Action  Nodes

负责执行具体动作的节点,比如:拷贝文件,执行某个Shell脚本等等。

3 Oozie的部署

3.1 部署HadoopCDH版本的)

3.1.2 修改Hadoop配置

hadoop-env.sh

 

export JAVA_HOME=/opt/module/jdk1.8.0_144

 

 

mapred-env.sh

 

 

export JAVA_HOME=/opt/module/jdk1.8.0_144

 

 

 

yarn-env.sh

 

 

export JAVA_HOME=/opt/module/jdk1.8.0_144

 

 

 

 

core-site.xml

<!-- 指定HDFS中NameNode的地址 -->
<property>
        <name>fs.defaultFS</name>
        <value>hdfs://hadoop102:8020</value>
</property>

<!-- 指定Hadoop运行时产生文件的存储目录 -->
<property>
        <name>hadoop.tmp.dir</name>
        <value>/opt/module/cdh/hadoop-2.5.0-cdh5.3.6/data/tmp</value>
</property>

<!-- Oozie Server的Hostname -->
<property>
  <name>hadoop.proxyuser.lxl.hosts</name>
  <value>*</value>
</property>

<!-- 允许被Oozie代理的用户组 -->
<property>
<name>hadoop.proxyuser.lxl.groups</name>
  <value>*</value>
</property>

 

 

hdfs-site.xml

<!-- 指定HDFS副本的数量 -->
<property>
  <name>dfs.replication</name>
  <value>1</value>
</property>

<!-- 指定Hadoop辅助名称节点主机配置 -->
<property>
  <name>dfs.namenode.secondary.http-address</name>
  <value>hadoop104:50090</value>
</property>

 

 

 

mapred-site.xml

<!-- 指定MR运行在YARN上 -->
<property>
    <name>mapreduce.framework.name</name>
    <value>yarn</value>
</property>

<!-- 历史服务器端地址 -->
<property>
    <name>mapreduce.jobhistory.address</name>
    <value>hadoop102:10020</value>
</property>

<!-- 历史服务器web端地址 -->
<property>
    <name>mapreduce.jobhistory.webapp.address</name>
    <value>hadoop102:19888</value>
</property>

 

 

 

yarn-site.xml

<!-- Reducer获取数据的方式 -->
<property>
        <name>yarn.nodemanager.aux-services</name>
        <value>mapreduce_shuffle</value>
</property>

<!-- 指定YARN的ResourceManager的地址 -->
<property>
        <name>yarn.resourcemanager.hostname</name>
        <value>hadoop103</value>
</property>

<!-- 日志聚集功能使能 -->
<property>
        <name>yarn.log-aggregation-enable</name>
        <value>true</value>
</property>

<!-- 日志保留时间设置7天 -->
<property>
        <name>yarn.log-aggregation.retain-seconds</name>
        <value>604800</value>
</property>

 

 

 

slaves

 

hadoop102
hadoop103
hadoop104

 

 

 

完成后:记得scp同步到其他机器节点

 

[[email protected] module]$ xsync cdh/

 

 

 

3.1.3 重启Hadoop集群

格式化:

 

[[email protected] hadoop-2.5.0-cdh5.3.6]$ bin/hdfs namenode -format

 

 

 

[[email protected] hadoop-2.5.0-cdh5.3.6]$ sbin/start-dfs.sh[[email protected] hadoop-2.5.0-cdh5.3.6]$ sbin/start-yarn.sh[[email protected] hadoop-2.5.0-cdh5.3.6]$ sbin/mr-jobhistory-daemon.sh start historyserver

 

注意:需要开启JobHistoryServer, 最好执行一个MR任务进行测试。

3.2 部署Oozie

3.2.1 解压Oozie

[[email protected] software]$ tar -zxvf /opt/software/cdh/oozie-4.0.0-cdh5.3.6.tar.gz -C ./

3.2.2 oozie根目录下解压oozie-hadooplibs-4.0.0-cdh5.3.6.tar.gz

[[email protected] oozie-4.0.0-cdh5.3.6]$ tar -zxvf oozie-hadooplibs-4.0.0-cdh5.3.6.tar.gz -C ../

完成后Oozie目录下会出现hadooplibs目录。

3.2.3 Oozie目录下创建libext目录

[[email protected] oozie-4.0.0-cdh5.3.6]$ mkdir libext/

3.2.4 拷贝依赖的Jar

1)将hadooplibs里面的jar包,拷贝到libext目录下:

[[email protected] oozie-4.0.0-cdh5.3.6]$ cp -ra hadooplibs/hadooplib-2.5.0-cdh5.3.6.oozie-4.0.0-cdh5.3.6/* libext/

2)拷贝mysql驱动包到libext目录下:

[[email protected] oozie-4.0.0-cdh5.3.6]$ cp -a /opt/software/mysql-connector-java-5.1.27/mysql-connector-java-5.1.27-bin.jar ./libext/

3.2.5 ext-2.2.zip拷贝到libext/目录下

ext是一个js框架,用于展示oozie前端页面:

[[email protected] oozie-4.0.0-cdh5.3.6]$ cp -a /opt/software/cdh/ext-2.2.zip libext/

3.2.6 修改Oozie配置文件

oozie-site.xml

属性:oozie.service.JPAService.jdbc.driver

属性值:com.mysql.jdbc.Driver

解释:JDBC的驱动

 

属性:oozie.service.JPAService.jdbc.url

属性值:jdbc:mysql://hadoop102:3306/oozie

解释:oozie所需的数据库地址

 

属性:oozie.service.JPAService.jdbc.username

属性值:root

解释:数据库用户名

 

属性:oozie.service.JPAService.jdbc.password

属性值:000000

解释:数据库密码

 

属性:oozie.service.HadoopAccessorService.hadoop.configurations

属性值:*=/opt/module/cdh/hadoop-2.5.0-cdh5.3.6/etc/hadoop

解释:让Oozie引用Hadoop的配置文件

3.2.7 Mysql中创建Oozie的数据库

进入Mysql并创建oozie数据库:

$ mysql -uroot -p000000

mysql> create database oozie;

3.2.8 初始化Oozie

1) 上传Oozie目录下的yarn.tar.gz文件到HDFS

提示:yarn.tar.gz文件会自行解压

[[email protected] oozie-4.0.0-cdh5.3.6]$ bin/oozie-setup.sh sharelib create -fs hdfs://hadoop102:8020 -locallib oozie-sharelib-4.0.0-cdh5.3.6-yarn.tar.gz

执行成功之后,去50070检查对应目录有没有文件生成。

2) 创建oozie.sql文件

[[email protected] oozie-4.0.0-cdh5.3.6]$ bin/ooziedb.sh create -sqlfile oozie.sql -run

3) 打包项目,生成war

[[email protected] oozie-4.0.0-cdh5.3.6]$ bin/oozie-setup.sh prepare-war

3.2.9 Oozie的启动与关闭

启动命令如下:

[[email protected] oozie-4.0.0-cdh5.3.6]$ bin/oozied.sh start

关闭命令如下:

[[email protected] oozie-4.0.0-cdh5.3.6]$ bin/oozied.sh stop

3.2.10 访问OozieWeb页面

http://hadoop102:11000/oozie

4 Oozie的使用

4.1 案例一:Oozie调度shell脚本

目标:使用Oozie调度Shell脚本

分步实现:

1)解压官方案例模板

[[email protected] oozie-4.0.0-cdh5.3.6]$ tar -zxvf oozie-examples.tar.gz

2)创建工作目录

[[email protected] oozie-4.0.0-cdh5.3.6]$ mkdir oozie-apps/

3)拷贝任务模板到oozie-apps/目录

[[email protected] oozie-4.0.0-cdh5.3.6]$ cp -r examples/apps/shell/ oozie-apps

4)编写脚本p1.sh

[[email protected] oozie-4.0.0-cdh5.3.6]$ vi oozie-apps/shell/p1.sh

内容如下:

#!/bin/bash

/sbin/ifconfig > /opt/module/p1.log

5)修改job.propertiesworkflow.xml文件

job.properties

#HDFS地址

nameNode=hdfs://hadoop102:8020

#ResourceManager地址

jobTracker=hadoop103:8032

#队列名称

queueName=default

examplesRoot=oozie-apps

oozie.wf.application.path=$nameNode/user/$user.name/$examplesRoot/shell

EXEC=p1.sh

workflow.xml

<workflow-app xmlns="uri:oozie:workflow:0.4" name="shell-wf">

<start to="shell-node"/>

<action name="shell-node">

    <shell xmlns="uri:oozie:shell-action:0.2">

        <job-tracker>$jobTracker</job-tracker>

        <name-node>$nameNode</name-node>

        <configuration>

            <property>

                <name>mapred.job.queue.name</name>

                <value>$queueName</value>

            </property>

        </configuration>

        <exec>$EXEC</exec>

        <!-- <argument>my_output=Hello Oozie</argument> -->

        <file>/user/atguigu/oozie-apps/shell/$EXEC#$EXEC</file>

 

        <capture-output/>

    </shell>

    <ok to="end"/>

    <error to="fail"/>

</action>

<decision name="check-output">

    <switch>

        <case to="end">

            $wf:actionData(‘shell-node‘)[‘my_output‘] eq ‘Hello Oozie‘

        </case>

        <default to="fail-output"/>

    </switch>

</decision>

<kill name="fail">

    <message>Shell action failed, error message[$wf:errorMessage(wf:lastErrorNode())]</message>

</kill>

<kill name="fail-output">

    <message>Incorrect output, expected [Hello Oozie] but was [$wf:actionData(‘shell-node‘)[‘my_output‘]]</message>

</kill>

<end name="end"/>

</workflow-app>

6)上传任务配置

[[email protected] oozie-4.0.0-cdh5.3.6]$ /opt/module/cdh/hadoop-2.5.0-cdh5.3.6/bin/hadoop fs -put oozie-apps/ /user/atguigu

7)执行任务

[[email protected] oozie-4.0.0-cdh5.3.6]$ bin/oozie job -oozie http://hadoop102:11000/oozie -config oozie-apps/shell/job.properties -run

8)杀死某个任务

[[email protected] oozie-4.0.0-cdh5.3.6]$ bin/oozie job -oozie http://hadoop102:11000/oozie -kill 0000004-170425105153692-oozie-z-W

4.2 案例二:Oozie逻辑调度执行多个Job

目标:使用Oozie执行多个Job调度

分步执行:

1) 解压官方案例模板

[[email protected] oozie-4.0.0-cdh5.3.6]$ tar -zxf oozie-examples.tar.gz

2) 编写脚本

[[email protected] oozie-4.0.0-cdh5.3.6]$ vi oozie-apps/shell/p2.sh

内容如下:

#!/bin/bash

/bin/date > /opt/module/p2.log

3)修改job.propertiesworkflow.xml文件

job.properties

nameNode=hdfs://hadoop102:8020

jobTracker=hadoop103:8032

queueName=default

examplesRoot=oozie-apps

 

oozie.wf.application.path=$nameNode/user/$user.name/$examplesRoot/shell

EXEC1=p1.sh

EXEC2=p2.sh

workflow.xml

<workflow-app xmlns="uri:oozie:workflow:0.4" name="shell-wf">

    <start to="p1-shell-node"/>

    <action name="p1-shell-node">

        <shell xmlns="uri:oozie:shell-action:0.2">

            <job-tracker>$jobTracker</job-tracker>

            <name-node>$nameNode</name-node>

            <configuration>

                <property>

                    <name>mapred.job.queue.name</name>

                    <value>$queueName</value>

                </property>

            </configuration>

            <exec>$EXEC1</exec>

            <file>/user/atguigu/oozie-apps/shell/$EXEC1#$EXEC1</file>

            <!-- <argument>my_output=Hello Oozie</argument>-->

            <capture-output/>

        </shell>

        <ok to="p2-shell-node"/>

        <error to="fail"/>

    </action>

 

    <action name="p2-shell-node">

        <shell xmlns="uri:oozie:shell-action:0.2">

            <job-tracker>$jobTracker</job-tracker>

            <name-node>$nameNode</name-node>

            <configuration>

                <property>

                    <name>mapred.job.queue.name</name>

                    <value>$queueName</value>

                </property>

            </configuration>

            <exec>$EXEC2</exec>

            <file>/user/admin/oozie-apps/shell/$EXEC2#$EXEC2</file>

            <!-- <argument>my_output=Hello Oozie</argument>-->

            <capture-output/>

        </shell>

        <ok to="end"/>

        <error to="fail"/>

    </action>

    <decision name="check-output">

        <switch>

            <case to="end">

                $wf:actionData(‘shell-node‘)[‘my_output‘] eq ‘Hello Oozie‘

            </case>

            <default to="fail-output"/>

        </switch>

    </decision>

    <kill name="fail">

        <message>Shell action failed, error message[$wf:errorMessage(wf:lastErrorNode())]</message>

    </kill>

    <kill name="fail-output">

        <message>Incorrect output, expected [Hello Oozie] but was [$wf:actionData(‘shell-node‘)[‘my_output‘]]</message>

    </kill>

    <end name="end"/>

</workflow-app>

3) 上传任务配置

$ bin/hadoop fs -rmr /user/atguigu/oozie-apps/

$ bin/hadoop fs -put oozie-apps/map-reduce /user/atguigu/oozie-apps

4) 执行任务

[[email protected] oozie-4.0.0-cdh5.3.6]$ bin/oozie job -oozie http://hadoop102:11000/oozie -config oozie-apps/shell/job.properties -run

4.3 案例三:Oozie调度MapReduce任务

目标:使用Oozie调度MapReduce任务

分步执行:

1)找到一个可以运行的mapreduce任务的jar包(可以用官方的,也可以是自己写的)

2)拷贝官方模板到oozie-apps

[[email protected] oozie-4.0.0-cdh5.3.6]$ cp -r /opt/module/cdh/ oozie-4.0.0-cdh5.3.6/examples/apps/map-reduce/ oozie-apps/

1) 测试一下wordcountyarn中的运行

[[email protected] oozie-4.0.0-cdh5.3.6]$ /opt/module/cdh/hadoop-2.5.0-cdh5.3.6/bin/yarn jar /opt/module/cdh/hadoop-2.5.0-cdh5.3.6/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.5.0-cdh5.3.6.jar wordcount /input/ /output/

4) 配置map-reduce任务的job.properties以及workflow.xml

job.properties

nameNode=hdfs://hadoop102:8020

jobTracker=hadoop103:8032

queueName=default

examplesRoot=oozie-apps

#hdfs://hadoop102:8020/user/admin/oozie-apps/map-reduce/workflow.xml

oozie.wf.application.path=$nameNode/user/$user.name/$examplesRoot/map-reduce/workflow.xml

outputDir=map-reduce

workflow.xml

<workflow-app xmlns="uri:oozie:workflow:0.2" name="map-reduce-wf">

    <start to="mr-node"/>

    <action name="mr-node">

        <map-reduce>

            <job-tracker>$jobTracker</job-tracker>

            <name-node>$nameNode</name-node>

            <prepare>

                <delete path="$nameNode/output/"/>

            </prepare>

            <configuration>

                <property>

                    <name>mapred.job.queue.name</name>

                    <value>$queueName</value>

                </property>

                <!-- 配置调度MR任务时,使用新的API -->

                <property>

                    <name>mapred.mapper.new-api</name>

                    <value>true</value>

                </property>

 

                <property>

                    <name>mapred.reducer.new-api</name>

                    <value>true</value>

                </property>

 

                <!-- 指定Job Key输出类型 -->

                <property>

                    <name>mapreduce.job.output.key.class</name>

                    <value>org.apache.hadoop.io.Text</value>

                </property>

 

                <!-- 指定Job Value输出类型 -->

                <property>

                    <name>mapreduce.job.output.value.class</name>

                    <value>org.apache.hadoop.io.IntWritable</value>

                </property>

 

                <!-- 指定输入路径 -->

                <property>

                    <name>mapred.input.dir</name>

                    <value>/input/</value>

                </property>

 

                <!-- 指定输出路径 -->

                <property>

                    <name>mapred.output.dir</name>

                    <value>/output/</value>

                </property>

 

                <!-- 指定Map-->

                <property>

                    <name>mapreduce.job.map.class</name>

                    <value>org.apache.hadoop.examples.WordCount$TokenizerMapper</value>

                </property>

 

                <!-- 指定Reduce-->

                <property>

                    <name>mapreduce.job.reduce.class</name>

                    <value>org.apache.hadoop.examples.WordCount$IntSumReducer</value>

                </property>

 

                <property>

                    <name>mapred.map.tasks</name>

                    <value>1</value>

                </property>

            </configuration>

        </map-reduce>

        <ok to="end"/>

        <error to="fail"/>

    </action>

    <kill name="fail">

        <message>Map/Reduce failed, error message[$wf:errorMessage(wf:lastErrorNode())]</message>

    </kill>

    <end name="end"/>

</workflow-app>

5)拷贝待执行的jar包到map-reducelib目录下

[[email protected] oozie-4.0.0-cdh5.3.6]$ cp -a  /opt /module/cdh/hadoop-2.5.0-cdh5.3.6/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.5.0-cdh5.3.6.jar oozie-apps/map-reduce/lib

6)上传配置好的app文件夹到HDFS

[[email protected] oozie-4.0.0-cdh5.3.6]$ /opt/module/cdh/hadoop-2.5.0-cdh5.3.6/bin/hdfs dfs -put oozie-apps/map-reduce/ /user/admin/oozie-apps

7)执行任务

[[email protected] oozie-4.0.0-cdh5.3.6]$ bin/oozie job -oozie http://hadoop102:11000/oozie -config oozie-apps/map-reduce/job.properties -run

4.4 案例四:Oozie定时任务/循环任务

目标:Coordinator周期性调度任务

分步实现:

1) 配置Linux时区以及时间服务器

2) 检查系统当前时区:

# date -R

注意:如果显示的时区不是+0800,删除localtime文件夹后,再关联一个正确时区的链接过去,命令如下:

# rm -rf /etc/localtime

# ln -s /usr/share/zoneinfo/Asia/Shanghai /etc/localtime

同步时间:

# ntpdate pool.ntp.org

修改NTP配置文件:

# vi /etc/ntp.conf

去掉下面这行前面的# ,并把网段修改成自己的网段:

restrict 192.168.122.0 mask 255.255.255.0 nomodify notrap

注释掉以下几行:

#server 0.centos.pool.ntp.org

#server 1.centos.pool.ntp.org

#server 2.centos.pool.ntp.org

把下面两行前面的#号去掉,如果没有这两行内容,需要手动添加

server  127.127.1.0    # local clock

fudge  127.127.1.0 stratum 10

重启NTP服务:

# systemctl start ntpd.service

注意,如果是centOS7以下的版本,使用命令:service ntpd start

# systemctl enable ntpd.service

注意,如果是centOS7以下的版本,使用命令:chkconfig ntpd on

集群其他节点去同步这台时间服务器时间:

首先需要关闭这两台计算机的ntp服务

# systemctl stop ntpd.service

centOS7以下,则:service ntpd stop

# systemctl disable ntpd.service

centOS7以下,则:chkconfig ntpd off

# systemctl status ntpd,查看ntp服务状态

# pgrep ntpd,查看ntp服务进程id

同步第一台服务器linux01的时间:

# ntpdate hadoop102

使用root用户制定计划任务,周期性同步时间:

# crontab -e

*/10 * * * * /usr/sbin/ntpdate hadoop102

重启定时任务:

# systemctl restart crond.service

centOS7以下使用:service crond restart

其他台机器的配置同理。

3) 配置oozie-site.xml文件

属性:oozie.processing.timezone

属性值:GMT+0800

解释:修改时区为东八区区时

注:该属性去oozie-default.xml中找到即可

4) 修改js框架中的关于时间设置的代码

$ vi /opt/module/cdh/oozie-4.0.0-cdh5.3.6/oozie-server/webapps/oozie/oozie-console.js

修改如下:

function getTimeZone()

    Ext.state.Manager.setProvider(new Ext.state.CookieProvider());

    return Ext.state.Manager.get("TimezoneId","GMT+0800");

5)重启oozie服务,并重启浏览器(一定要注意清除缓存)

[[email protected] oozie-4.0.0-cdh5.3.6]$ bin/oozied.sh stop

[[email protected] oozie-4.0.0-cdh5.3.6]$ bin/oozied.sh start

6)拷贝官方模板配置定时任务\

$ cp -r examples/apps/cron/ oozie-apps/

7)修改模板job.properties和coordinator.xml以及workflow.xml

job.properties

nameNode=hdfs://hadoop102:8020

jobTracker=hadoop103:8032

queueName=default

examplesRoot=oozie-apps

 

oozie.coord.application.path=$nameNode/user/$user.name/$examplesRoot/cron

#start:必须设置为未来时间,否则任务失败

start=2017-07-29T17:00+0800

end=2017-07-30T17:00+0800

workflowAppUri=$nameNode/user/$user.name/$examplesRoot/cron

 

EXEC3=p3.sh

coordinator.xml

<coordinator-app name="cron-coord" frequency="$coord:minutes(5)" start="$start" end="$end" timezone="GMT+0800" xmlns="uri:oozie:coordinator:0.2">

<action>

<workflow>

    <app-path>$workflowAppUri</app-path>

    <configuration>

        <property>

            <name>jobTracker</name>

            <value>$jobTracker</value>

        </property>

        <property>

            <name>nameNode</name>

            <value>$nameNode</value>

        </property>

        <property>

            <name>queueName</name>

            <value>$queueName</value>

        </property>

    </configuration>

</workflow>

</action>

</coordinator-app>

workflow.xml

<workflow-app xmlns="uri:oozie:workflow:0.5" name="one-op-wf">

<start to="p3-shell-node"/>

  <action name="p3-shell-node">

      <shell xmlns="uri:oozie:shell-action:0.2">

          <job-tracker>$jobTracker</job-tracker>

          <name-node>$nameNode</name-node>

          <configuration>

              <property>

                  <name>mapred.job.queue.name</name>

                  <value>$queueName</value>

              </property>

          </configuration>

          <exec>$EXEC3</exec>

          <file>/user/atguigu/oozie-apps/cron/$EXEC3#$EXEC3</file>

          <!-- <argument>my_output=Hello Oozie</argument>-->

          <capture-output/>

      </shell>

      <ok to="end"/>

      <error to="fail"/>

  </action>

<kill name="fail">

    <message>Shell action failed, error message[$wf:errorMessage(wf:lastErrorNode())]</message>

</kill>

<kill name="fail-output">

    <message>Incorrect output, expected [Hello Oozie] but was [$wf:actionData(‘shell-node‘)[‘my_output‘]]</message>

</kill>

<end name="end"/>

</workflow-app>

8)上传配置

[[email protected] oozie-4.0.0-cdh5.3.6]$ /opt/module/cdh/hadoop-2.5.0-cdh5.3.6/bin/hdfs dfs -put oozie-apps/cron/ /user/admin/oozie-apps

9)启动任务

[[email protected] oozie-4.0.0-cdh5.3.6]$ bin/oozie job -oozie http://hadoop102:11000/oozie -config oozie-apps/cron/job.properties -run

注意:Oozie允许的最小执行任务的频率是5分钟

5 常见问题总结

1Mysql权限配置

授权所有主机可以使用root用户操作所有数据库和数据表

mysql> grant all on *.* to [email protected]‘%‘ identified by ‘000000‘;

mysql> flush privileges;

mysql> exit;

2workflow.xml配置的时候不要忽略file属性

3jps查看进程时,注意有没有bootstrap

4)关闭oozie

如果bin/oozied.sh stop无法关闭,则可以使用kill -9 [pid],之后oozie-server/temp/xxx.pid文件一定要删除。

5Oozie重新打包时,一定要注意先关闭进程,删除对应文件夹下面的pid文件。(可以参考第4条目)

6)配置文件一定要生效

起始标签和结束标签无对应则不生效,配置文件的属性写错了,那么则执行默认的属性。

7libext下边的jar存放于某个文件夹中,导致share/lib创建不成功。

8)调度任务时,找不到指定的脚本,可能是oozie-site.xml里面的Hadoop配置文件没有关联上。

9)修改Hadoop配置文件,需要重启集群。一定要记得scp到其他节点。

10JobHistoryServer必须开启,集群要重启的。

11Mysql配置如果没有生效的话,默认使用derby数据库。

12)在本地修改完成的job配置,必须重新上传到HDFS

13)将HDFS中上传的oozie配置文件下载下来查看是否有错误。

14Linux用户名和Hadoop的用户名不一致。

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