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优化文档和配置
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@ -21,6 +21,7 @@ Lodash 高性能的 JavaScript 实用工具库
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- #### Node安装
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Node包下载 (注意版本 8.9.4) `https://nodejs.org/download/release/v8.9.4/`
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- #### 前端项目构建
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用命令行模式 `cd` 进入 `escheduler-ui`项目目录并执行 `npm install` 拉取项目依赖包
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@ -31,6 +32,16 @@ Node包下载 (注意版本 8.9.4) `https://nodejs.org/download/release/v8.9.4/`
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> 运行 `cnpm install`
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- 新建一个`.env`文件,用于跟后端交互的接口
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在`escheduler-ui`目录下新建一个`.env`文件,在文件里添加后端服务的ip地址和端口,用于跟后端交互,`.env`文件内容如下:
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```
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# 代理的接口地址(自行修改)
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API_BASE = http://192.168.xx.xx:12345
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# 如果您需要用ip访问项目可以把 "#" 号去掉(例)
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#DEV_HOST = 192.168.xx.xx
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```
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> ##### !!!这里特别注意 项目如果在拉取依赖包的过程中报 " node-sass error " 错误,请在执行完后再次执行以下命令
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```
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@ -49,6 +60,7 @@ npm install node-sass --unsafe-perm //单独安装node-sass依赖
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再拷贝到服务器对应的目录下(前端服务静态页面存放目录)
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访问地址 `http://localhost:8888/#/`
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@ -3,23 +3,14 @@
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前端有3种部署方式,分别为自动化部署,手动部署和编译源码部署
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## 1、准备工作
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#### 准备一:下载安装包
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#### 下载安装包
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目前最新安装包版本是1.0.1,下载地址: [码云下载](https://gitee.com/easyscheduler/EasyScheduler/attach_files/)
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下载escheduler-ui-1.0.1.tar.gz后,解压后会产生dist目录,进入dist目录
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> cd dist
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#### 准备二:新建一个`.env`文件
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在dist目录下新建一个`.env`文件,在文件里添加后端服务的ip地址和端口,用于跟后端交互,`.env`文件内容如下:
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```
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# 代理的接口地址(自行修改)
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API_BASE = http://192.168.xx.xx:12345
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# 如果您需要用ip访问项目可以把 "#" 号去掉(例)
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#DEV_HOST = 192.168.xx.xx
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```
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## 2、部署
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以下两种方式任选其一部署即可,推荐自动化部署
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@ -89,7 +89,7 @@ install.sh : 一键部署脚本
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- 修改 **install.sh**中的各参数,替换成自身业务所需的值
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- 如果使用hdfs相关功能,需要拷贝**hdfs-site.xml**和**core-site.xml**到conf目录下
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- 如果使用hdfs相关功能,需要拷贝**hdfs-site.xml**和**core-site.xml**到conf目录下
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## 2、部署
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@ -148,11 +148,11 @@ install.sh : 一键部署脚本
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* 一键停止集群所有服务
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` sh ./script/stop_all.sh`
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` sh ./bin/stop_all.sh`
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* 一键开启集群所有服务
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` sh ./script/start_all.sh`
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` sh ./bin/start_all.sh`
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* 启停Master
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@ -9,7 +9,7 @@ worker.fetch.task.num = 3
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# only less than cpu avg load, worker server can work. default value : the number of cpu cores * 2
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worker.max.cpuload.avg=10
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#worker.max.cpuload.avg=10
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# only larger than reserved memory, worker server can work. default value : physical memory * 1/6, unit is G.
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worker.reserved.memory=1
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@ -201,10 +201,10 @@ workerExecThreads="100"
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workerHeartbeatInterval="10"
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# worker一次抓取任务数
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workerFetchTaskNum="10"
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workerFetchTaskNum="3"
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# worker最大cpu平均负载,用来判断master是否还有执行能力
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workerMaxCupLoadAvg="10"
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# worker最大cpu平均负载,用来判断worker是否还有执行能力,保持系统默认,默认为cpu核数的2倍,当负载达到2倍时,
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#workerMaxCupLoadAvg="10"
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# worker预留内存,用来判断master是否还有执行能力
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workerReservedMemory="1"
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@ -279,7 +279,7 @@ sed -i ${txt} "s#master.reserved.memory.*#master.reserved.memory=${masterReserve
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sed -i ${txt} "s#worker.exec.threads.*#worker.exec.threads=${workerExecThreads}#g" conf/worker.properties
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sed -i ${txt} "s#worker.heartbeat.interval.*#worker.heartbeat.interval=${workerHeartbeatInterval}#g" conf/worker.properties
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sed -i ${txt} "s#worker.fetch.task.num.*#worker.fetch.task.num=${workerFetchTaskNum}#g" conf/worker.properties
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sed -i ${txt} "s#worker.max.cpuload.avg.*#worker.max.cpuload.avg=${workerMaxCupLoadAvg}#g" conf/worker.properties
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#sed -i ${txt} "s#worker.max.cpuload.avg.*#worker.max.cpuload.avg=${workerMaxCupLoadAvg}#g" conf/worker.properties
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sed -i ${txt} "s#worker.reserved.memory.*#worker.reserved.memory=${workerReservedMemory}#g" conf/worker.properties
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