尚硅谷大數據技術之Oozie前端
Oozie英文翻譯爲:馴象人。一個基於工做流引擎的開源框架,由Cloudera公司貢獻給Apache,提供對Hadoop MapReduce、Pig Jobs的任務調度與協調。Oozie須要部署到Java Servlet容器中運行。主要用於定時調度任務,多任務能夠按照執行的邏輯順序調度。java
1) Workflownode
順序執行流程節點,支持fork(分支多個節點),join(合併多個節點爲一個)mysql
2) Coordinatorlinux
定時觸發workflowweb
3) Bundle Jobsql
綁定多個Coordinatorshell
1) 控制流節點(Control Flow Nodes)數據庫
控制流節點通常都是定義在工做流開始或者結束的位置,好比start,end,kill等。以及提供工做流的執行路徑機制,如decision,fork,join等。apache
2) 動做節點(Action Nodes)
負責執行具體動做的節點,好比:拷貝文件,執行某個Shell腳本等等。
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運行時產生文件的存儲目錄 --> <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> <!-- 容許被Oozie代理的用戶組 --> <property> <name>hadoop.proxyuser.lxl.groups</name> <value>*</value> </property>
hdfs-site.xml
<!-- 指定HDFS副本的數量 -->
<property>
<name>dfs.replication</name>
<value>1</value>
</property>
<!-- 指定Hadoop輔助名稱節點主機配置 -->
<property>
<name>dfs.namenode.secondary.http-address</name>
<value>hadoop104:50090</value>
</property>
mapred-site.xml
<!-- 指定MR運行在YARN上 --> <property> <name>mapreduce.framework.name</name> <value>yarn</value> </property> <!-- 歷史服務器端地址 --> <property> <name>mapreduce.jobhistory.address</name> <value>hadoop102:10020</value> </property> <!-- 歷史服務器web端地址 --> <property> <name>mapreduce.jobhistory.webapp.address</name> <value>hadoop102:19888</value> </property>
yarn-site.xml
<!-- Reducer獲取數據的方式 --> <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> <!-- 日誌彙集功能使能 --> <property> <name>yarn.log-aggregation-enable</name> <value>true</value> </property> <!-- 日誌保留時間設置7天 --> <property> <name>yarn.log-aggregation.retain-seconds</name> <value>604800</value> </property>
slaves
hadoop102
hadoop103
hadoop104
完成後:記得scp同步到其餘機器節點
[lxl@hadoop102 module]$ xsync cdh/
格式化:
[lxl@hadoop102 hadoop-2.5.0-cdh5.3.6]$ bin/hdfs namenode -format
啓動任務
[lxl@hadoop102 hadoop-2.5.0-cdh5.3.6]$ sbin/start-dfs.sh
[lxl@hadoop103 hadoop-2.5.0-cdh5.3.6]$ sbin/start-yarn.sh
[lxl@hadoop102 hadoop-2.5.0-cdh5.3.6]$ sbin/mr-jobhistory-daemon.sh start historyserver
注意:須要開啓JobHistoryServer, 最好執行一個MR任務進行測試。
[lxl@hadoop102 software]$ tar -zxvf /opt/software/cdh/oozie-4.0.0-cdh5.3.6.tar.gz -C ./
[lxl@hadoop102 oozie-4.0.0-cdh5.3.6]$ tar -zxvf oozie-hadooplibs-4.0.0-cdh5.3.6.tar.gz -C ../
完成後Oozie目錄下會出現hadooplibs目錄。
[lxl@hadoop102 oozie-4.0.0-cdh5.3.6]$ mkdir libext/
1)將hadooplibs裏面的jar包,拷貝到libext目錄下:
[lxl@hadoop102 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)拷貝Mysql驅動包到libext目錄下:
[lxl@hadoop102 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/
ext是一個js框架,用於展現oozie前端頁面:
[lxl@hadoop102 oozie-4.0.0-cdh5.3.6]$ cp /opt/software/ext-2.2.zip ./libext/
oozie-site.xml
屬性:oozie.service.JPAService.jdbc.driver 屬性值:com.mysql.jdbc.Driver 解釋:JDBC的驅動 屬性:oozie.service.JPAService.jdbc.url 屬性值:jdbc:mysql://hadoop102:3306/oozie 解釋:oozie所需的數據庫地址 屬性:oozie.service.JPAService.jdbc.username 屬性值:root 解釋:數據庫用戶名 屬性:oozie.service.JPAService.jdbc.password 屬性值:000000 解釋:數據庫密碼 屬性:oozie.service.HadoopAccessorService.hadoop.configurations 屬性值:*=/opt/module/cdh/hadoop-2.5.0-cdh5.3.6/etc/hadoop 解釋:讓Oozie引用Hadoop的配置文件
進入Mysql並建立oozie數據庫:
$ mysql -uroot -p000000
mysql> create database oozie;
1) 上傳Oozie目錄下的yarn.tar.gz文件到HDFS:
提示:yarn.tar.gz文件會自行解壓
[lxl@hadoop102 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
執行成功以後,去50070檢查對應目錄有沒有文件生成。
2) 建立oozie.sql文件
[lxl@hadoop102 oozie-4.0.0-cdh5.3.6]$ bin/ooziedb.sh create -sqlfile oozie.sql -run
setting CATALINA_OPTS="$CATALINA_OPTS -Xmx1024m" Validate DB Connection DONE Check DB schema does not exist DONE Check OOZIE_SYS table does not exist DONE Create SQL schema DONE Create OOZIE_SYS table DONE Oozie DB has been created for Oozie version '4.0.0-cdh5.3.6'
3) 打包項目,生成war包
[lxl@hadoop102 oozie-4.0.0-cdh5.3.6]$ bin/oozie-setup.sh prepare-war
啓動命令以下:
[atguigu@hadoop102 oozie-4.0.0-cdh5.3.6]$ bin/oozied.sh start
關閉命令以下:
[atguigu@hadoop102 oozie-4.0.0-cdh5.3.6]$ bin/oozied.sh stop
目標:使用Oozie調度Shell腳本
分步實現:
1)解壓官方案例模板
[lxl@hadoop102 oozie-4.0.0-cdh5.3.6]$ tar -zxvf oozie-examples.tar.gz
2)建立工做目錄
[lxl@hadoop102 oozie-4.0.0-cdh5.3.6]$ mkdir oozie-apps/
3)拷貝任務模板到oozie-apps/目錄
[lxl@hadoop102 oozie-4.0.0-cdh5.3.6]$ cp -r examples/apps/shell/ oozie-apps
4)編寫腳本p1.sh
[lxl@hadoop102 oozie-4.0.0-cdh5.3.6]$ vi oozie-apps/shell/p1.sh
內容以下:
#!/bin/bash
date > /opt/module/p1.log
5)修改job.properties和workflow.xml文件
job.properties
#HDFS地址 nameNode=hdfs://hadoop102:8020 #ResourceManager地址 jobTracker=hadoop103:8032 #隊列名稱 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>${EXEC}</exec> <!-- <argument>my_output=Hello Oozie</argument> --> <file>/user/lxl/oozie-apps/shell/${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 [${wf:actionData('shell-node')['my_output']}]</message> </kill> <end name="end"/> </workflow-app>
6)上傳任務配置
[lxl@hadoop102 oozie-4.0.0-cdh5.3.6]$ /opt/module/cdh/hadoop-2.5.0-cdh5.3.6/bin/hadoop fs -put oozie-apps/ /user/atguigu
7)執行任務
[lxl@hadoop102 oozie-4.0.0-cdh5.3.6]$ bin/oozie job -oozie http://hadoop102:11000/oozie -config oozie-apps/shell/job.properties -run
8)殺死某個任務
[lxl@hadoop102 oozie-4.0.0-cdh5.3.6]$ bin/oozie job -oozie http://hadoop102:11000/oozie -kill 0000004-170425105153692-oozie-z-W
若是任務配置文件出錯須要修改hdfs上的文件再從新執行!
[lxl@hadoop102 oozie-4.0.0-cdh5.3.6]$ /opt/module/cdh/hadoop-2.5.0-cdh5.3.6/bin/hadoop fs -rm -r /user/lxl/oozie-apps/shell/job.properties 19/06/17 04:10:13 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable 19/06/17 04:10:14 INFO fs.TrashPolicyDefault: Namenode trash configuration: Deletion interval = 0 minutes, Emptier interval = 0 minutes. Deleted /user/lxl/oozie-apps/shell/job.properties [lxl@hadoop102 oozie-4.0.0-cdh5.3.6]$ /opt/module/cdh/hadoop-2.5.0-cdh5.3.6/bin/hadoop fs -put ./oozie-apps/shell/job.properties /user/lxl/oozie-apps/shell/ 19/06/17 04:10:39 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable [lxl@hadoop102 oozie-4.0.0-cdh5.3.6]$ bin/oozie job -oozie http://hadoop102:11000/oozie -config oozie-apps/shell/job.properties -run
目標:使用Oozie執行多個Job調度
分步執行:
1) 解壓官方案例模板
[lxl@hadoop102 oozie-4.0.0-cdh5.3.6]$ tar -zxf oozie-examples.tar.gz
2) 編寫腳本
[lxl@hadoop102 oozie-4.0.0-cdh5.3.6]$ vi oozie-apps/shell/p2.sh
內容以下:
#!/bin/bash /bin/date > /opt/module/p2.log
3)修改job.properties和workflow.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>${EXEC1}</exec> <file>/user/lxl/oozie-apps/shell/${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>${EXEC2}</exec> <file>/user/lxl/oozie-apps/shell/${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 [${wf:actionData('shell-node')['my_output']}]</message> </kill> <end name="end"/> </workflow-app>
3) 上傳任務配置
[lxl@hadoop102 hadoop-2.5.0-cdh5.3.6]$ bin/hadoop fs -rm -r /user/lxl/oozie-apps/shell/* [lxl@hadoop102 oozie-apps]$ /opt/module/cdh/hadoop-2.5.0-cdh5.3.6//bin/hadoop fs -put ./shell/* /user/lxl/oozie-apps/shell/
4) 執行任務
[lxl@hadoop102 oozie-4.0.0-cdh5.3.6]$ bin/oozie job -oozie http://hadoop102:11000/oozie -config oozie-apps/shell/job.properties -run
目標:使用Oozie調度MapReduce任務
分步執行:
1)找到一個能夠運行的mapreduce任務的jar包(能夠用官方的,也能夠是本身寫的)
2)拷貝官方模板到oozie-apps
[lxl@hadoop102 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) 測試一下wordcount在yarn中的運行
[lxl@hadoop102 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任務的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>${queueName}</value> </property> <!-- 配置調度MR任務時,使用新的API --> <property> <name>mapred.mapper.new-api</name> <value>true</value> </property> <property> <name>mapred.reducer.new-api</name> <value>true</value> </property> <!-- 指定Job Key輸出類型 --> <property> <name>mapreduce.job.output.key.class</name> <value>org.apache.hadoop.io.Text</value> </property> <!-- 指定Job Value輸出類型 --> <property> <name>mapreduce.job.output.value.class</name> <value>org.apache.hadoop.io.IntWritable</value> </property> <!-- 指定輸入路徑 --> <property> <name>mapred.input.dir</name> <value>/input/</value> </property> <!-- 指定輸出路徑 --> <property> <name>mapred.output.dir</name> <value>/output/</value> </property> <!-- 指定Map類 --> <property> <name>mapreduce.job.map.class</name> <value>org.apache.hadoop.examples.WordCount$TokenizerMapper</value> </property> <!-- 指定Reduce類 --> <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)拷貝待執行的jar包到map-reduce的lib目錄下(先清空lib下的全部文件)
[lxl@hadoop102 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)上傳配置好的app文件夾到HDFS
[lxl@hadoop102 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/lxl/oozie-apps
或:
[lxl@hadoop102 oozie-apps]$ /opt/module/cdh/hadoop-2.5.0-cdh5.3.6/bin/hadoop fs -put map-reduce/ /user/lxl/oozie-apps
7)執行任務
[lxl@hadoop102 oozie-4.0.0-cdh5.3.6]$ bin/oozie job -oozie http://hadoop102:11000/oozie -config oozie-apps/map-reduce/job.properties -run
目標:Coordinator週期性調度任務
分步實現:
1) 配置Linux時區以及時間服務器
2) 檢查系統當前時區:
[lxl@hadoop102 shell]$ date -R Mon, 17 Jun 2019 09:01:44 +0800
注意:若是顯示的時區不是+0800,刪除localtime文件夾後,再關聯一個正確時區的連接過去,命令以下:
# rm -rf /etc/localtime # ln -s /usr/share/zoneinfo/Asia/Shanghai /etc/localtime
同步時間:
# ntpdate pool.ntp.org
修改NTP配置文件:
# vi /etc/ntp.conf 去掉下面這行前面的# ,並把網段修改爲本身的網段: restrict 192.168.122.0 mask 255.255.255.0 nomodify notrap 註釋掉如下幾行: #server 0.centos.pool.ntp.org #server 1.centos.pool.ntp.org #server 2.centos.pool.ntp.org 把下面兩行前面的#號去掉,若是沒有這兩行內容,須要手動添加 server 127.127.1.0 # local clock fudge 127.127.1.0 stratum 10
重啓NTP服務:
# systemctl start ntpd.service,
注意,若是是centOS7如下的版本,使用命令:service ntpd start
# systemctl enable ntpd.service,
注意,若是是centOS7如下的版本,使用命令:chkconfig ntpd on
集羣其餘節點去同步這臺時間服務器時間:
首先須要關閉這兩臺計算機的ntp服務
# systemctl stop ntpd.service,
centOS7如下,則:service ntpd stop
# systemctl disable ntpd.service,
centOS7如下,則:chkconfig ntpd off
# systemctl status ntpd,查看ntp服務狀態
# pgrep ntpd,查看ntp服務進程id
同步第一臺服務器linux01的時間:
# ntpdate hadoop102
使用root用戶制定計劃任務,週期性同步時間:
# crontab -e */10 * * * * /usr/sbin/ntpdate hadoop102
重啓定時任務:
# systemctl restart crond.service,
centOS7如下使用:service crond restart,
其餘臺機器的配置同理。
3) 配置oozie-site.xml文件
屬性:oozie.processing.timezone 屬性值:GMT+0800 解釋:修改時區爲東八區區時
注:該屬性去oozie-default.xml中找到便可(而後把這個屬性配置黏貼到oozie-site.xml中進行修改)
4) 修改js框架中的關於時間設置的代碼
$ vi /opt/module/cdh/oozie-4.0.0-cdh5.3.6/oozie-server/webapps/oozie/oozie-console.js 修改以下: function getTimeZone() { Ext.state.Manager.setProvider(new Ext.state.CookieProvider()); return Ext.state.Manager.get("TimezoneId","GMT+0800"); }
5)重啓oozie服務,並重啓瀏覽器(必定要注意清除緩存)
[atguigu@hadoop102 oozie-4.0.0-cdh5.3.6]$ bin/oozied.sh stop [atguigu@hadoop102 oozie-4.0.0-cdh5.3.6]$ bin/oozied.sh start
效果:
6)拷貝官方模板配置定時任務
[lxl@hadoop102 apps]$ pwd /opt/module/oozie-4.0.0-cdh5.3.6/examples/apps [lxl@hadoop102 apps]$ cp -r cron /opt/module/oozie-4.0.0-cdh5.3.6/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}/${examplesRoot}/cron #start:必須設置爲將來時間,不然任務失敗 start=2017-07-29T17:00+0800 end=2017-07-30T17:00+0800 workflowAppUri=${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 [${wf:actionData('shell-node')['my_output']}]</message> </kill> <end name="end"/> </workflow-app>
8)上傳配置
[lxl@hadoop102 oozie-4.0.0-cdh5.3.6]$ /opt/module/cdh/hadoop-2.5.0-cdh5.3.6/bin/hdfs dfs -put oozie-apps/cron/ /user/admin/oozie-apps
或:
[lxl@hadoop102 oozie-apps]$ /opt/module/cdh/hadoop-2.5.0-cdh5.3.6/bin/hadoop fs -put cron/ /user/lxl/oozie-apps/
9)啓動任務
[lxl@hadoop102 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容許的最小執行任務的頻率是5分鐘
1)Mysql權限配置
受權全部主機可使用root用戶操做全部數據庫和數據表
mysql> grant all on *.* to root@'%' identified by '000000'; mysql> flush privileges; mysql> exit;
2)workflow.xml配置的時候不要忽略file屬性
3)jps查看進程時,注意有沒有bootstrap
4)關閉oozie
若是bin/oozied.sh stop沒法關閉,則可使用kill -9 [pid],以後oozie-server/temp/xxx.pid文件必定要刪除。
5)Oozie從新打包時,必定要注意先關閉進程,刪除對應文件夾下面的pid文件。(能夠參考第4條目)
6)配置文件必定要生效
起始標籤和結束標籤無對應則不生效,配置文件的屬性寫錯了,那麼則執行默認的屬性。
7)libext下邊的jar存放於某個文件夾中,致使share/lib建立不成功。
8)調度任務時,找不到指定的腳本,多是oozie-site.xml裏面的Hadoop配置文件沒有關聯上。
9)修改Hadoop配置文件,須要重啓集羣。必定要記得scp到其餘節點。
10)JobHistoryServer必須開啓,集羣要重啓的。
11)Mysql配置若是沒有生效的話,默認使用derby數據庫。
12)在本地修改完成的job配置,必須從新上傳到HDFS。
13)將HDFS中上傳的oozie配置文件下載下來查看是否有錯誤。
14)Linux用戶名和Hadoop的用戶名不一致。