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。 前端
1) Workflow java
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) node
2) Coordinator mysql
定時觸發workflow linux
3) Bundle Job web
綁定多個Coordinator sql
1) 控制流節點(Control Flow Nodes) shell
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。 數據庫
2) 動做節點(Action Nodes) apache
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。
core-site.xml
<!-- Oozie Server的Hostname -->
<property>
<name>hadoop.proxyuser.atguigu.hosts</name>
<value>*</value>
</property>
<!-- 容許被Oozie代理的用戶組 -->
<property>
<name>hadoop.proxyuser.atguigu.groups</name>
<value>*</value>
</property>
mapred-site.xml
<!-- 配置 MapReduce JobHistory Server 地址 ,默認端口10020 -->
<property>
<name>mapreduce.jobhistory.address</name>
<value>hadoop102:10020</value>
</property>
<!-- 配置 MapReduce JobHistory Server web ui 地址, 默認端口19888 -->
<property>
<name>mapreduce.jobhistory.webapp.address</name>
<value>hadoop102:19888</value>
</property>
yarn-site.xml
<!-- 任務歷史服務 -->
<property>
<name>yarn.log.server.url</name>
<value>http://hadoop102:19888/jobhistory/logs/</value>
</property>
完成後:記得scp同步到其餘機器節點
[atguigu@hadoop102 hadoop-2.7.2]$ sbin/start-dfs.sh
[atguigu@hadoop103 hadoop-2.7.2]$ sbin/start-yarn.sh
[atguigu@hadoop102 hadoop-2.7.2]$ 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。
[atguigu@hadoop102 software]$ tar -zxvf /opt/software/cdh/oozie-4.0.0-cdh5.3.6.tar.gz -C ./
[atguigu@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。
[atguigu@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:
[atguigu@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:
[atguigu@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:
[atguigu@hadoop102 oozie-4.0.0-cdh5.3.6]$ cp -a /opt/software/cdh/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
[atguigu@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
[atguigu@hadoop102 oozie-4.0.0-cdh5.3.6]$ bin/ooziedb.sh create -sqlfile oozie.sql -run
3) 打包項目,生成war包
[atguigu@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
[atguigu@hadoop102 oozie-4.0.0-cdh5.3.6]$ tar -zxvf oozie-examples.tar.gz
2)建立工做目錄
[atguigu@hadoop102 oozie-4.0.0-cdh5.3.6]$ mkdir oozie-apps/
3)拷貝任務模板到oozie-apps/目錄
[atguigu@hadoop102 oozie-4.0.0-cdh5.3.6]$ cp -r examples/apps/shell/ oozie-apps
4)編寫腳本p1.sh
[atguigu@hadoop102 oozie-4.0.0-cdh5.3.6]$ vi oozie-apps/shell/p1.sh
內容以下:
#!/bin/bash
/sbin/ifconfig > /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>${EXEC}</exec>
<!-- <argument>my_output=Hello Oozie</argument> -->
<file>/user/atguigu/oozie-apps/shell/${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 [${wf:actionData('shell-node')['my_output']}]</message>
</kill>
<end name="end"/>
</workflow-app>
6)上傳任務配置
[atguigu@hadoop102 oozie-4.0.0-cdh5.3.6]$ /opt/module/cdh/hadoop-2.5.0-cdh5.3.6/bin/hadoop fs -put oozie-apps/ /user/atguigu
7)執行任務
[atguigu@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
[atguigu@hadoop102 oozie-4.0.0-cdh5.3.6]$ bin/oozie job -oozie http://hadoop102:11000/oozie -kill 0000004-170425105153692-oozie-z-W
目標:使用Oozie執行多個Job調度
分步執行:
[atguigu@hadoop102 oozie-4.0.0-cdh5.3.6]$ tar -zxf oozie-examples.tar.gz
[atguigu@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>${EXEC1}</exec>
<file>/user/atguigu/oozie-apps/shell/${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>
$ bin/hadoop fs -rmr /user/atguigu/oozie-apps/
$ bin/hadoop fs -put oozie-apps/map-reduce /user/atguigu/oozie-apps
[atguigu@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
[atguigu@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/
[atguigu@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
[atguigu@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
[atguigu@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/admin/oozie-apps
7)執行任務
[atguigu@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:
# date -R
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。
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
$ 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
6)拷貝官方模板配置定時任務\
$ 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 [${wf:actionData('shell-node')['my_output']}]</message>
</kill>
<end name="end"/>
</workflow-app>
8)上傳配置
[atguigu@hadoop102 oozie-4.0.0-cdh5.3.6]$ /opt/module/cdh/hadoop-2.5.0-cdh5.3.6/bin/hdfs dfs -put oozie-apps/cron/ /user/admin/oozie-apps
9)啓動任務
[atguigu@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。