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1548 lines
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1548 lines
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系统参数 |
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创建部署用户 |
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配置文件 |
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escheduler-common |
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escheduler-dao |
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escheduler-server |
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escheduler-web |
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启动停止命令 |
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一键启停脚本 |
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监控服务 |
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日志查看 |
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前端开发文档 |
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安装 |
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后端开发文档 |
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后端说明2 |
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本书使用 GitBook 发布 |
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<div class="page-wrapper" tabindex="-1" role="main"> |
|
<div class="page-inner"> |
|
|
|
<div id="book-search-results"> |
|
<div class="search-noresults"> |
|
|
|
<section class="normal markdown-section"> |
|
|
|
<p>​</p> |
|
<h1 id="部署文档">部署文档</h1> |
|
<h2 id="软件要求">软件要求</h2> |
|
<ul> |
|
<li><a href="https://blog.csdn.net/u011886447/article/details/79796802" target="_blank">Mysql</a> (5.5+) : 必装</li> |
|
<li><a href="http://www.oracle.com/technetwork/java/javase/downloads/index.html" target="_blank">JDK</a> (1.8+) ：必装 </li> |
|
<li><a href="https://www.jianshu.com/p/de90172ea680" target="_blank">Zookeeper</a> (3.4.6) ：必装 </li> |
|
<li><a href="https://blog.csdn.net/Evankaka/article/details/51612437" target="_blank">Hadoop</a> (2.7+) ：选装， 如果需要使用到EasyScheduler的资源上传，MapReduce任务在线提交则需要安装(上传的资源文件目前保存在Hdfs上)</li> |
|
<li><a href="https://staroon.pro/2017/12/09/HiveInstall/" target="_blank">Hive</a> (1.2.1+) : 选装，如果跑Hive任务需要安装(</li> |
|
<li><a href="https://www.cnblogs.com/caoguo/p/4625662.html" target="_blank">Reids安装</a> (2.7.0+) : 选装， 任务队列选择Redis时需要安装</li> |
|
<li>Spark(1.x,2.x) : 选装，Spark任务提交需要安装</li> |
|
<li><p>PostgreSQL(8.2.15+) : 选装，PostgreSQL存储过程需要安装</p> |
|
<blockquote> |
|
<p>注意：EasyScheduler本身不依赖Hadoop、Hive、Spark、PostgreSQL、Redis,仅是用到了他们的Client jar，用于对应任务的运行。</p> |
|
</blockquote> |
|
</li> |
|
</ul> |
|
<h2 id="项目编译">项目编译</h2> |
|
<ul> |
|
<li>执行编译命令：</li> |
|
</ul> |
|
<blockquote> |
|
<p><code>mvn -U clean package assembly:assembly -Dmaven.test.skip=true</code> </p> |
|
</blockquote> |
|
<ul> |
|
<li>查看目录</li> |
|
</ul> |
|
<p>正常编译完后，会在当前目录生成 target/escheduler-{version}-SNAPSHOT/</p> |
|
<pre><code> bin |
|
conf |
|
lib |
|
script |
|
sql |
|
</code></pre><ul> |
|
<li><p>说明</p> |
|
<pre><code>bin : 工程服务启动脚本 |
|
conf : 工程配置文件 |
|
lib : 工程依赖jar包，包括各个模块jar和第三方jar |
|
script : 工程自动化部署、启动脚本 |
|
sql : 工程依赖sql文件 |
|
</code></pre></li> |
|
</ul> |
|
<h2 id="数据库初始化">数据库初始化</h2> |
|
<ul> |
|
<li>创建database和账号</li> |
|
</ul> |
|
<pre><code>mysql -h {host} -u {user} -p{password} |
|
mysql> CREATE DATABASE escheduler DEFAULT CHARACTER SET utf8 DEFAULT COLLATE utf8_general_ci; |
|
mysql> GRANT ALL PRIVILEGES ON escheduler.* TO '{user}'@'%' IDENTIFIED BY '{password}'; |
|
mysql> GRANT ALL PRIVILEGES ON escheduler.* TO '{user}'@'localhost' IDENTIFIED BY '{password}'; |
|
mysql> flush privileges; |
|
</code></pre><ul> |
|
<li>创建表</li> |
|
</ul> |
|
<pre><code>说明：在target/escheduler-{version}-SNAPSHOT/sql/有两个sql创建表文件：escheduler.sql和quartz.sql |
|
执行： |
|
mysql -h {host} -u {user} -p{password} -D {db} < escheduler.sql |
|
mysql -h {host} -u {user} -p{password} -D {db} < quartz.sql |
|
</code></pre><h2 id="创建部署用户">创建部署用户</h2> |
|
<p>因为easyscheduler worker都是以 sudo -u {linux-user} 方式来执行作业，所以部署用户需要有 sudo 权限，而且是免密的。</p> |
|
<pre><code>部署账号 |
|
vi /etc/sudoers |
|
|
|
# 部署用户是 escheduler 账号 |
|
escheduler ALL=(ALL) NOPASSWD: NOPASSWD: ALL |
|
|
|
# 并且需要注释掉 Default requiretty 一行 |
|
#Default requiretty |
|
</code></pre><h2 id="配置文件">配置文件</h2> |
|
<p><code>说明：配置文件位于 target/escheduler-{version}-SNAPSHOT/conf 下面</code></p> |
|
<h3 id="escheduler-alert">escheduler-alert</h3> |
|
<p>配置邮件告警信息</p> |
|
<ul> |
|
<li>alert.properties </li> |
|
</ul> |
|
<pre><code>#以qq邮箱为例，如果是别的邮箱，请更改对应配置 |
|
#alert type is EMAIL/SMS |
|
alert.type=EMAIL |
|
|
|
# mail server configuration |
|
mail.protocol=SMTP |
|
mail.server.host=smtp.exmail.qq.com |
|
mail.server.port=25 |
|
mail.sender=xxxxxx@qq.com |
|
mail.passwd=xxxxxxx |
|
|
|
# xls file path, need manually create it before use if not exist |
|
xls.file.path=/opt/xls |
|
</code></pre><p>配置告警数据源信息</p> |
|
<ul> |
|
<li>alert/data_source.properties </li> |
|
</ul> |
|
<pre><code>#注意：请替换${xxx}里的内容 |
|
|
|
# common configuration |
|
spring.datasource.type=com.alibaba.druid.pool.DruidDataSource |
|
spring.datasource.driver-class-name=com.mysql.jdbc.Driver |
|
spring.datasource.url=jdbc:mysql://${ip}:3306/escheduler?characterEncoding=UTF-8 |
|
spring.datasource.username=${username} |
|
spring.datasource.password=${password} |
|
|
|
# supplement configuration |
|
spring.datasource.initialSize=5 |
|
# min connection number |
|
spring.datasource.minIdle=5 |
|
# max connection number |
|
spring.datasource.maxActive=20 |
|
|
|
# max wait time for get connection |
|
spring.datasource.maxWait=60000 |
|
|
|
# idle connections closed，unit milliseconds |
|
spring.datasource.timeBetweenEvictionRunsMillis=60000 |
|
|
|
# connection minimum survival time，unit milliseconds |
|
spring.datasource.minEvictableIdleTimeMillis=300000 |
|
spring.datasource.validationQuery=SELECT 1 |
|
spring.datasource.validationQueryTimeout=3 |
|
spring.datasource.testWhileIdle=true |
|
spring.datasource.testOnBorrow=true |
|
spring.datasource.testOnReturn=false |
|
spring.datasource.defaultAutoCommit=true |
|
|
|
# open PSCache，set PSCache size |
|
spring.datasource.poolPreparedStatements=false |
|
spring.datasource.maxPoolPreparedStatementPerConnectionSize=20 |
|
</code></pre><p>日志配置文件</p> |
|
<ul> |
|
<li>alert_logback.xml</li> |
|
</ul> |
|
<pre><code><!-- Logback configuration. See http://logback.qos.ch/manual/index.html --> |
|
<configuration scan="true" scanPeriod="120 seconds"> <!--debug="true" --> |
|
<property name="log.base" value="logs" /> |
|
<appender name="STDOUT" class="ch.qos.logback.core.ConsoleAppender"> |
|
<encoder> |
|
<pattern> |
|
[%level] %date{yyyy-MM-dd HH:mm:ss.SSS} %logger{96}:[%line] - %msg%n |
|
</pattern> |
|
<charset>UTF-8</charset> |
|
</encoder> |
|
</appender> |
|
|
|
<appender name="ALERTLOGFILE" class="ch.qos.logback.core.rolling.RollingFileAppender"> |
|
<file>${log.base}/escheduler-alert.log</file> |
|
<rollingPolicy class="ch.qos.logback.core.rolling.SizeAndTimeBasedRollingPolicy"> |
|
<fileNamePattern>${log.base}/escheduler-alert.%d{yyyy-MM-dd_HH}.%i.log</fileNamePattern> |
|
<maxHistory>20</maxHistory> |
|
<maxFileSize>64MB</maxFileSize> |
|
</rollingPolicy> |
|
<encoder> |
|
<pattern> |
|
[%level] %date{yyyy-MM-dd HH:mm:ss.SSS} %logger{96}:[%line] - %msg%n |
|
</pattern> |
|
<charset>UTF-8</charset> |
|
</encoder> |
|
</appender> |
|
|
|
<root level="INFO"> |
|
<appender-ref ref="ALERTLOGFILE"/> |
|
</root> |
|
</configuration> |
|
</code></pre><h3 id="escheduler-common">escheduler-common</h3> |
|
<p>通用配置文件配置，队列选择及地址配置，通用文件目录配置。</p> |
|
<ul> |
|
<li>common/common.properties</li> |
|
</ul> |
|
<pre><code>#task queue implementation, can choose "redis" or "zookeeper", default "zookeeper" |
|
escheduler.queue.impl=zookeeper |
|
|
|
#if escheduler.queue.impl=redis, you need to configuration relevant information with redis. redis configuration start |
|
spring.redis.host=${redis_ip} |
|
spring.redis.port=6379 |
|
spring.redis.maxIdle=1000 |
|
spring.redis.maxTotal=10000 |
|
#redis configuration end |
|
|
|
# user data directory path, self configuration, please make sure the directory exists and have read write permissions |
|
data.basedir.path=/xxx/xxx |
|
|
|
# directory path for user data download. self configuration, please make sure the directory exists and have read write permissions |
|
data.download.basedir.path=/xxx/xxx |
|
|
|
# process execute directory. self configuration, please make sure the directory exists and have read write permissions |
|
process.exec.basepath=/xxx/xxx |
|
|
|
# data base dir, resource file will store to this hadoop hdfs path, self configuration, please make sure the directory exists on hdfs and have read write permissions。"/escheduler" is recommended |
|
data.store2hdfs.basepath=/escheduler |
|
|
|
# system env path. self configuration, please make sure the directory and file exists and have read write execute permissions |
|
escheduler.env.path=/xxx/xxx/.escheduler_env.sh |
|
escheduler.env.py=/xxx/xxx/escheduler_env.py |
|
|
|
#resource.view.suffixs |
|
resource.view.suffixs=txt,log,sh,conf,cfg,py,java,sql,hql,xml |
|
|
|
# is development state? default "false" |
|
development.state=false |
|
</code></pre><p>SHELL任务 环境变量配置</p> |
|
<p>.escheduler_env.sh </p> |
|
<pre><code>#self configuration, please make sure the directory exists and have read write permissions |
|
export HADOOP_HOME=/opt/soft/hadoop |
|
export HADOOP_CONF_DIR=/opt/soft/hadoop/etc/hadoop |
|
export SPARK_HOME1=/opt/soft/spark1 |
|
export SPARK_HOME2=/opt/soft/spark2 |
|
export PYTHON_HOME=/opt/soft/python |
|
export JAVA_HOME=/opt/soft/java |
|
export HIVE_HOME=/opt/soft/hive |
|
|
|
export PATH=$HADOOP_HOME/bin:$SPARK_HOME1/bin:$SPARK_HOME2/bin:$PYTHON_HOME/bin:$JAVA_HOME/bin:$HIVE_HOME/bin:$PATH |
|
</code></pre><p>​ </p> |
|
<p>Python任务 环境变量配置</p> |
|
<p>escheduler_env.py</p> |
|
<pre><code>#self configuration, please make sure the directory exists and have read write execute permissions |
|
|
|
import os |
|
|
|
HADOOP_HOME="/opt/soft/hadoop" |
|
PYTHON_HOME="/opt/soft/python" |
|
JAVA_HOME="/opt/soft/java" |
|
PATH=os.environ['PATH'] |
|
PATH="%s/bin:%s/bin:%s/bin:%s"%(HADOOP_HOME,JAVA_HOME,PYTHON_HOME,PATH) |
|
|
|
os.putenv('PATH','%s'%PATH) |
|
</code></pre><p>hadoop 配置文件</p> |
|
<ul> |
|
<li>common/hadoop/hadoop.properties</li> |
|
</ul> |
|
<pre><code>#please replace the content in ${xxx} |
|
# ha or single namenode |
|
fs.defaultFS=hdfs://${cluster_ipOrName}:8020 |
|
|
|
#resourcemanager ha note this need ips , eg. 192.168.220.188,192.168.220.189 |
|
yarn.resourcemanager.ha.rm.ids=${ip1},${ip2} |
|
|
|
# reousrcemanager path |
|
yarn.application.status.address=http://${ip1}:8088/ws/v1/cluster/apps/%s |
|
</code></pre><p>定时器配置文件</p> |
|
<ul> |
|
<li>quartz.properties</li> |
|
</ul> |
|
<pre><code>#please replace the content in ${xxx} |
|
#============================================================================ |
|
# Configure Main Scheduler Properties |
|
#============================================================================ |
|
org.quartz.scheduler.instanceName = EasyScheduler |
|
org.quartz.scheduler.instanceId = AUTO |
|
org.quartz.scheduler.makeSchedulerThreadDaemon = true |
|
org.quartz.jobStore.useProperties = false |
|
|
|
#============================================================================ |
|
# Configure ThreadPool |
|
#============================================================================ |
|
|
|
org.quartz.threadPool.class = org.quartz.simpl.SimpleThreadPool |
|
org.quartz.threadPool.makeThreadsDaemons = true |
|
org.quartz.threadPool.threadCount = 25 |
|
org.quartz.threadPool.threadPriority = 5 |
|
|
|
#============================================================================ |
|
# Configure JobStore |
|
#============================================================================ |
|
|
|
org.quartz.jobStore.class = org.quartz.impl.jdbcjobstore.JobStoreTX |
|
org.quartz.jobStore.driverDelegateClass = org.quartz.impl.jdbcjobstore.StdJDBCDelegate |
|
org.quartz.jobStore.tablePrefix = QRTZ_ |
|
org.quartz.jobStore.isClustered = true |
|
org.quartz.jobStore.misfireThreshold = 60000 |
|
org.quartz.jobStore.clusterCheckinInterval = 5000 |
|
org.quartz.jobStore.dataSource = myDs |
|
|
|
#============================================================================ |
|
# Configure Datasources |
|
#============================================================================ |
|
|
|
org.quartz.dataSource.myDs.driver = com.mysql.jdbc.Driver |
|
org.quartz.dataSource.myDs.URL = jdbc:mysql://${ip}:3306/escheduler?characterEncoding=utf8&useSSL=false |
|
org.quartz.dataSource.myDs.user = ${username} |
|
org.quartz.dataSource.myDs.password = ${password} |
|
org.quartz.dataSource.myDs.maxConnections = 10 |
|
org.quartz.dataSource.myDs.validationQuery = select 1 |
|
</code></pre><p>zookeeper 配置文件</p> |
|
<ul> |
|
<li>zookeeper.properties</li> |
|
</ul> |
|
<pre><code>#zookeeper cluster. eg. 192.168.220.188:2181,192.168.220.189:2181,192.168.220.190:2181 |
|
zookeeper.quorum=${ip1}:2181,${ip2}:2181,${ip3}:2181 |
|
|
|
#zookeeper server dirctory |
|
zookeeper.escheduler.master=/escheduler/masters |
|
zookeeper.escheduler.worker=/escheduler/workers |
|
|
|
#zookeeper lock dirctory |
|
zookeeper.escheduler.lock.master=/escheduler/lock/master |
|
zookeeper.escheduler.lock.worker=/escheduler/lock/worker |
|
|
|
#escheduler root directory |
|
zookeeper.escheduler.root=/escheduler |
|
|
|
#escheduler failover directory |
|
zookeeper.escheduler.lock.master.failover=/escheduler/lock/failover/master |
|
zookeeper.escheduler.lock.worker.failover=/escheduler/lock/failover/worker |
|
|
|
#escheduler failover directory |
|
zookeeper.session.timeout=300 |
|
zookeeper.connection.timeout=300 |
|
zookeeper.retry.sleep=1000 |
|
zookeeper.retry.maxtime=5 |
|
</code></pre><h3 id="escheduler-dao">escheduler-dao</h3> |
|
<p>dao数据源配置</p> |
|
<ul> |
|
<li>dao/data_source.properties</li> |
|
</ul> |
|
<pre><code>#please replace the content in ${xxx} |
|
|
|
# base spring data source configuration |
|
spring.datasource.type=com.alibaba.druid.pool.DruidDataSource |
|
spring.datasource.driver-class-name=com.mysql.jdbc.Driver |
|
spring.datasource.url=jdbc:mysql://${ip}:3306/escheduler?characterEncoding=UTF-8 |
|
spring.datasource.username=${username} |
|
spring.datasource.password=${password} |
|
|
|
# connection configuration |
|
spring.datasource.initialSize=5 |
|
spring.datasource.minIdle=5 |
|
spring.datasource.maxActive=20 |
|
|
|
# max seconds wait connection timeout |
|
spring.datasource.maxWait=60000 |
|
|
|
# milliseconds for check to close free connections |
|
spring.datasource.timeBetweenEvictionRunsMillis=60000 |
|
|
|
# connection minimum survival time(milliseconds) |
|
spring.datasource.minEvictableIdleTimeMillis=300000 |
|
spring.datasource.validationQuery=SELECT 1 |
|
spring.datasource.validationQueryTimeout=3 |
|
spring.datasource.testWhileIdle=true |
|
spring.datasource.testOnBorrow=true |
|
spring.datasource.testOnReturn=false |
|
spring.datasource.defaultAutoCommit=true |
|
|
|
# open PSCache, specify count PSCache for every connection |
|
spring.datasource.poolPreparedStatements=true |
|
spring.datasource.maxPoolPreparedStatementPerConnectionSize=20 |
|
|
|
|
|
# data quality analysis is not currently in use. please ignore the following configuration |
|
# task record flag |
|
task.record.flag=false |
|
task.record.datasource.url=jdbc:mysql://${ip}:3306/etl?characterEncoding=UTF-8 |
|
task.record.datasource.username=etl |
|
task.record.datasource.password=xxxxx |
|
</code></pre><h3 id="escheduler-server">escheduler-server</h3> |
|
<p>master配置文件</p> |
|
<ul> |
|
<li>master.properties</li> |
|
</ul> |
|
<pre><code># master execute thread num |
|
master.exec.threads=100 |
|
|
|
# master execute task number in parallel |
|
master.exec.task.number=20 |
|
|
|
# master heartbeat interval |
|
master.heartbeat.interval=8 |
|
|
|
# master commit task retry times |
|
master.task.commit.retryTimes=5 |
|
|
|
# master commit task interval |
|
master.task.commit.interval=100 |
|
|
|
|
|
# only less than cpu avg load, master server can work. default value : the number of cpu cores * 2 |
|
master.max.cpuload.avg=10 |
|
|
|
# only larger than reserved memory, master server can work. default value : physical memory * 1/10, unit is G. |
|
master.reserved.memory=1 |
|
</code></pre><p>master日志文件</p> |
|
<p><strong>注意：</strong>对MASTERLOGFILE，自定义了MasterLogFilter</p> |
|
<ul> |
|
<li>master_logback.xml</li> |
|
</ul> |
|
<pre><code><!-- Logback configuration. See http://logback.qos.ch/manual/index.html --> |
|
<configuration scan="true" scanPeriod="120 seconds"> <!--debug="true" --> |
|
<property name="log.base" value="logs" /> |
|
<appender name="STDOUT" class="ch.qos.logback.core.ConsoleAppender"> |
|
<encoder> |
|
<pattern> |
|
[%level] %date{yyyy-MM-dd HH:mm:ss.SSS} %logger{96}:[%line] - %msg%n |
|
</pattern> |
|
<charset>UTF-8</charset> |
|
</encoder> |
|
</appender> |
|
|
|
<appender name="MASTERLOGFILE" class="ch.qos.logback.core.rolling.RollingFileAppender"> |
|
<file>${log.base}/escheduler-master.log</file> |
|
<filter class="cn.escheduler.server.master.log.MasterLogFilter"> |
|
<level>INFO</level> |
|
</filter> |
|
<rollingPolicy class="ch.qos.logback.core.rolling.SizeAndTimeBasedRollingPolicy"> |
|
<fileNamePattern>${log.base}/escheduler-master.%d{yyyy-MM-dd_HH}.%i.log</fileNamePattern> |
|
<maxHistory>20</maxHistory> |
|
<maxFileSize>200MB</maxFileSize> |
|
</rollingPolicy> |
|
<encoder> |
|
<pattern> |
|
[%level] %date{yyyy-MM-dd HH:mm:ss.SSS} %logger{96}:[%line] - %msg%n |
|
</pattern> |
|
<charset>UTF-8</charset> |
|
</encoder> |
|
</appender> |
|
|
|
<root level="INFO"> |
|
<appender-ref ref="MASTERLOGFILE"/> |
|
</root> |
|
</configuration> |
|
</code></pre><p>worker配置文件</p> |
|
<ul> |
|
<li>worker.properties</li> |
|
</ul> |
|
<pre><code># worker execute thread num |
|
worker.exec.threads=100 |
|
|
|
# worker heartbeat interval |
|
worker.heartbeat.interval=8 |
|
|
|
# submit the number of tasks at a time |
|
worker.fetch.task.num = 10 |
|
|
|
# only less than cpu avg load, worker server can work. default value : the number of cpu cores * 2 |
|
worker.max.cpuload.avg=10 |
|
|
|
# only larger than reserved memory, worker server can work. default value : physical memory * 1/6, unit is G. |
|
worker.reserved.memory=1 |
|
</code></pre><p>worker日志文件</p> |
|
<p><strong>注意：</strong>对WORKERLOGFILE，自定义了WorkerLogFilter</p> |
|
<p>对于 TASKLOGFILE ， 自定义了TaskLogAppender和TaskLogFilter</p> |
|
<ul> |
|
<li>worker_logback.xml</li> |
|
</ul> |
|
<pre><code><!-- Logback configuration. See http://logback.qos.ch/manual/index.html --> |
|
<configuration scan="true" scanPeriod="120 seconds"> |
|
<property name="log.base" value="logs"/> |
|
<appender name="STDOUT" class="ch.qos.logback.core.ConsoleAppender"> |
|
<encoder> |
|
<pattern> |
|
[%level] %date{yyyy-MM-dd HH:mm:ss.SSS} %logger{96}:[%line] - %msg%n |
|
</pattern> |
|
<charset>UTF-8</charset> |
|
</encoder> |
|
</appender> |
|
<appender name="TASKLOGFILE" class="cn.escheduler.server.worker.log.TaskLogAppender"> |
|
<filter class="ch.qos.logback.classic.filter.ThresholdFilter"> |
|
<level>INFO</level> |
|
</filter> |
|
<filter class="cn.escheduler.server.worker.log.TaskLogFilter"></filter> |
|
<file>${log.base}/{processDefinitionId}/{processInstanceId}/{taskInstanceId}.log</file> |
|
<encoder> |
|
<pattern> |
|
[%level] %date{yyyy-MM-dd HH:mm:ss.SSS} %logger{96}:[%line] - %msg%n |
|
</pattern> |
|
<charset>UTF-8</charset> |
|
</encoder> |
|
<append>true</append> |
|
</appender> |
|
|
|
<appender name="WORKERLOGFILE" class="ch.qos.logback.core.rolling.RollingFileAppender"> |
|
<file>${log.base}/escheduler-worker.log</file> |
|
<filter class="cn.escheduler.server.worker.log.WorkerLogFilter"> |
|
<level>INFO</level> |
|
</filter> |
|
|
|
<rollingPolicy class="ch.qos.logback.core.rolling.SizeAndTimeBasedRollingPolicy"> |
|
<fileNamePattern>${log.base}/escheduler-worker.%d{yyyy-MM-dd_HH}.%i.log</fileNamePattern> |
|
<maxHistory>20</maxHistory> |
|
<maxFileSize>200MB</maxFileSize> |
|
</rollingPolicy> |
|
　　　　　 |
|
<encoder> |
|
<pattern> |
|
[%level] %date{yyyy-MM-dd HH:mm:ss.SSS} %logger{96}:[%line] - %msg%n |
|
</pattern> |
|
<charset>UTF-8</charset> |
|
</encoder> |
|
　　 |
|
</appender> |
|
|
|
|
|
<root level="INFO"> |
|
<appender-ref ref="TASKLOGFILE"/> |
|
<appender-ref ref="WORKERLOGFILE"/> |
|
</root> |
|
</configuration> |
|
</code></pre><h3 id="escheduler-web">escheduler-web</h3> |
|
<p>web配置文件</p> |
|
<ul> |
|
<li>application.properties</li> |
|
</ul> |
|
<pre><code># server port |
|
server.port=12345 |
|
|
|
# session config |
|
server.session.timeout=7200 |
|
|
|
|
|
server.context-path=/escheduler/ |
|
|
|
# file size limit for upload |
|
spring.http.multipart.max-file-size=1024MB |
|
spring.http.multipart.max-request-size=1024MB |
|
|
|
#post content |
|
server.max-http-post-size=5000000 |
|
</code></pre><p>web日志文件</p> |
|
<ul> |
|
<li>webserver_logback.xml</li> |
|
</ul> |
|
<pre><code> <!-- Logback configuration. See http://logback.qos.ch/manual/index.html --> |
|
<configuration scan="true" scanPeriod="120 seconds"> |
|
<logger name="org.apache.zookeeper" level="WARN"/> |
|
<logger name="org.apache.hbase" level="WARN"/> |
|
<logger name="org.apache.hadoop" level="WARN"/> |
|
|
|
<property name="log.base" value="logs" /> |
|
|
|
<appender name="STDOUT" class="ch.qos.logback.core.ConsoleAppender"> |
|
<encoder> |
|
<pattern> |
|
[%level] %date{yyyy-MM-dd HH:mm:ss.SSS} %logger{96}:[%line] - %msg%n |
|
</pattern> |
|
<charset>UTF-8</charset> |
|
</encoder> |
|
</appender> |
|
|
|
<appender name="WEBSERVERLOGFILE" class="ch.qos.logback.core.rolling.RollingFileAppender"> |
|
<!-- Log level filter --> |
|
<filter class="ch.qos.logback.classic.filter.ThresholdFilter"> |
|
<level>INFO</level> |
|
</filter> |
|
<file>${log.base}/escheduler-web-server.log</file> |
|
<rollingPolicy class="ch.qos.logback.core.rolling.SizeAndTimeBasedRollingPolicy"> |
|
<fileNamePattern>${log.base}/escheduler-web-server.%d{yyyy-MM-dd_HH}.%i.log</fileNamePattern> |
|
<maxHistory>20</maxHistory> |
|
<maxFileSize>64MB</maxFileSize> |
|
</rollingPolicy> |
|
|
|
<encoder> |
|
<pattern> |
|
[%level] %date{yyyy-MM-dd HH:mm:ss.SSS} %logger{96}:[%line] - %msg%n |
|
</pattern> |
|
<charset>UTF-8</charset> |
|
</encoder> |
|
|
|
</appender> |
|
|
|
<root level="INFO"> |
|
<appender-ref ref="WEBSERVERLOGFILE" /> |
|
</root> |
|
</configuration> |
|
</code></pre><h2 id="启动停止命令">启动停止命令</h2> |
|
<ul> |
|
<li>启停Master</li> |
|
</ul> |
|
<pre><code>sh ./bin/arklifter-daemon.sh start master-server |
|
sh ./bin/arklifter-daemon.sh stop master-server |
|
</code></pre><ul> |
|
<li>启停Worker</li> |
|
</ul> |
|
<pre><code>sh ./bin/arklifter-daemon.sh start worker-server |
|
sh ./bin/arklifter-daemon.sh stop worker-server |
|
</code></pre><ul> |
|
<li>启停Web</li> |
|
</ul> |
|
<pre><code>sh ./bin/arklifter-daemon.sh start web-server |
|
sh ./bin/arklifter-daemon.sh stop web-server |
|
</code></pre><ul> |
|
<li>启停Logger<pre><code>sh ./bin/arklifter-daemon.sh start logger-server |
|
sh ./bin/arklifter-daemon.sh stop logger-server |
|
</code></pre></li> |
|
<li>启停Alert<pre><code>sh ./bin/arklifter-daemon.sh start alert-server |
|
sh ./bin/arklifter-daemon.sh stop alert-server |
|
</code></pre></li> |
|
</ul> |
|
<h2 id="一键启停脚本">一键启停脚本</h2> |
|
<ul> |
|
<li><p>部署用户配置</p> |
|
<ol> |
|
<li><p>创建部署用户</p> |
|
<p>target/escheduler-{version}-SNAPSHOT/script/init_deploy_user.sh</p> |
|
</li> |
|
<li><p>配置</p> |
|
<p>因为escheduler worker 都是以 sudo -u {linux-user} 方式来执行作业，所以部署用户需要有 sudo 权限，而且是免密的</p> |
|
</li> |
|
</ol> |
|
</li> |
|
</ul> |
|
<pre><code> vi /etc/sudoers |
|
|
|
# 部署用户是 escheduler 账号 |
|
escheduler ALL=(ALL) NOPASSWD: NOPASSWD: ALL |
|
|
|
# 并且需要注释掉 Default requiretty 一行 |
|
#Default requiretty |
|
</code></pre><ul> |
|
<li>初始化 hdfs</li> |
|
</ul> |
|
<p>​ target/escheduler-{version}-SNAPSHOT/script/init_hdfs.sh</p> |
|
<ul> |
|
<li>安装配置文件 install_config</li> |
|
</ul> |
|
<pre><code> # 项目所在目录 |
|
BASE_PATH=/opt/soft/program |
|
# 部署的机器 |
|
IPS=ark0,ark1,ark2,ark3,ark4 |
|
</code></pre><ul> |
|
<li><p>运行配置文件 run_config</p> |
|
<pre><code> # master服务所在机器,>=1个 |
|
MASTERS=ark0,ark1 |
|
# worker服务所在机器,>=1个 |
|
WORKERS=ark2,ark3,ark4 |
|
# alert服务所在机器,1个 |
|
ALERTS=ark3 |
|
# web服务所在机器,1个 |
|
WEBSERVER=ark1 |
|
</code></pre></li> |
|
<li><p>初始化安装目录</p> |
|
<p> target/escheduler-{version}-SNAPSHOT/script/init_install_path.sh</p> |
|
</li> |
|
<li><p>将 target/escheduler-{version}-SNAPSHOT 下配置好的conf文件夹和编译好的escheduler-{version}-SNAPSHOT.tar.gz 复制到 <strong>主机器</strong>的 BASE_PATH 目录下 </p> |
|
<p> 说明：<strong>主机器</strong>需要能免密ssh登录到其它机器上</p> |
|
</li> |
|
<li><p>启动所有服务</p> |
|
</li> |
|
</ul> |
|
<pre><code class="lang-启动所有服务">sh ./deploy/start_all.sh |
|
</code></pre> |
|
<ul> |
|
<li>关闭所有服务</li> |
|
</ul> |
|
<pre><code class="lang-关闭所有服务">sh ./deploy/stop_all.sh |
|
</code></pre> |
|
<h2 id="监控服务">监控服务</h2> |
|
<p>monitor_server.py 脚本是监听，master和worker服务挂掉重启的脚本</p> |
|
<p>注意：在全部服务都启动之后启动</p> |
|
<p>nohup python -u monitor_server.py > nohup.out 2>&1 &</p> |
|
<h2 id="日志查看">日志查看</h2> |
|
<p>日志统一存放于指定文件夹内</p> |
|
<pre><code class="lang-日志路径"> logs/ |
|
├── escheduler-alert-server.log |
|
├── escheduler-master-server.log |
|
|—— escheduler-worker-server.log |
|
|—— escheduler-web-server.log |
|
|—— escheduler-logger-server.log |
|
</code></pre> |
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