299 lines
9.4 KiB
Markdown
299 lines
9.4 KiB
Markdown
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PiFlow是一个简单易用，功能强大的大数据流水线系统。
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## 目录
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- [特性](#特性)
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- [架构](#架构)
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- [要求](#要求)
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- [开始](#开始)
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- [Docker镜像](#Docker镜像)
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- [页面展示](#页面展示)
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- [联系我们](#联系我们)
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## 特性
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- 简单易用
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- 可视化配置流水线
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- 监控流水线
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- 查看流水线日志
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- 检查点功能
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- 扩展性强:
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- 支持自定义开发数据处理组件
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- 性能优越：
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- 基于分布式计算引擎Spark开发
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- 功能强大：
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- 提供100+的数据处理组件
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- 包括Hadoop 、Spark、MLlib、Hive、Solr、Redis、MemCache、ElasticSearch、JDBC、MongoDB、HTTP、FTP、XML、CSV、JSON等
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- 集成了微生物领域的相关算法
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## 架构
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## 要求
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* JDK 1.8
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* Spark-2.11.8
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* Apache Maven 3.1.0
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* Spark-2.1.0 及以上版本
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* Hadoop-2.6.0
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## 开始
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### Build PiFlow:
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- `install external package`
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mvn install:install-file -Dfile=/../piflow/piflow-bundle/lib/spark-xml_2.11-0.4.2.jar -DgroupId=com.databricks -DartifactId=spark-xml_2.11 -Dversion=0.4.2 -Dpackaging=jar
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mvn install:install-file -Dfile=/../piflow/piflow-bundle/lib/java_memcached-release_2.6.6.jar -DgroupId=com.memcached -DartifactId=java_memcached-release -Dversion=2.6.6 -Dpackaging=jar
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mvn install:install-file -Dfile=/../piflow/piflow-bundle/lib/ojdbc6-11.2.0.3.jar -DgroupId=oracle -DartifactId=ojdbc6 -Dversion=11.2.0.3 -Dpackaging=jar
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mvn install:install-file -Dfile=/../piflow/piflow-bundle/lib/edtftpj.jar -DgroupId=ftpClient -DartifactId=edtftp -Dversion=1.0.0 -Dpackaging=jar
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- `mvn clean package -Dmaven.test.skip=true`
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[INFO] Replacing original artifact with shaded artifact.
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[INFO] Reactor Summary:
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[INFO]
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[INFO] piflow-project ..................................... SUCCESS [ 4.369 s]
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[INFO] piflow-core ........................................ SUCCESS [01:23 min]
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[INFO] piflow-configure ................................... SUCCESS [ 12.418 s]
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[INFO] piflow-bundle ...................................... SUCCESS [02:15 min]
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[INFO] piflow-server ...................................... SUCCESS [02:05 min]
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[INFO] ------------------------------------------------------------------------
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[INFO] BUILD SUCCESS
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[INFO] ------------------------------------------------------------------------
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[INFO] Total time: 06:01 min
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[INFO] Finished at: 2020-05-21T15:22:58+08:00
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[INFO] Final Memory: 118M/691M
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[INFO] ------------------------------------------------------------------------
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### 运行 Piflow Server：
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- `Intellij上运行PiFlow Server`:
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- 下载 piflow: git clone https://github.com/cas-bigdatalab/piflow.git
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- 将PiFlow导入到Intellij
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- 编辑配置文件config.properties
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- Build PiFlow jar包:
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- Run --> Edit Configurations --> Add New Configuration --> Maven
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- Name: package
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- Command line: clean package -Dmaven.test.skip=true -X
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- run 'package' (piflow jar file will be built in ../piflow/piflow-server/target/piflow-server-0.9.jar)
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- 运行 HttpService:
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- Edit Configurations --> Add New Configuration --> Application
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- Name: HttpService
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- Main class : cn.piflow.api.Main
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- Environment Variable: SPARK_HOME=/opt/spark-2.2.0-bin-hadoop2.6(change the path to your spark home)
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- run 'HttpService'
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- 测试 HttpService:
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- run /../piflow/piflow-server/src/main/scala/cn/piflow/api/HTTPClientStartMockDataFlow.scala
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- change the piflow server ip and port to your configure
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- `通过Release版本运行PiFlow`:
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- 根据需求下载不同版本PiFlow（建议下载最新版本）:
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https://github.com/cas-bigdatalab/piflow/releases/download/v0.5/piflow.tar.gz
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https://github.com/cas-bigdatalab/piflow/releases/download/v0.6/piflow-server-v0.6.tar.gz
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https://github.com/cas-bigdatalab/piflow/releases/download/v0.7/piflow-server-v0.7.tar.gz
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- 解压piflow-server-v0.7.tar.gz:
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tar -zxvf piflow-server-v0.7.tar.gz
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- 编辑配置文件config.properties
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- 运行、停止、重启PiFlow Server
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start.sh、stop.sh、 restart.sh、 status.sh
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- 测试 PiFlow Server
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- 设置环境变量 PIFLOW_HOME
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- vim /etc/profile
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export PIFLOW_HOME=/yourPiflowPath/bin
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export PATH=$PATH:$PIFLOW_HOME/bin
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- 运行如下命令
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piflow flow start example/mockDataFlow.json
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piflow flow stop appID
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piflow flow info appID
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piflow flow log appID
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piflow flowGroup start example/mockDataGroup.json
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piflow flowGroup stop groupId
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piflow flowGroup info groupId
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- `如何配置config.properties`
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#spark and yarn config
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spark.master=yarn
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spark.deploy.mode=cluster
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#hdfs default file system
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fs.defaultFS=hdfs://10.0.86.191:9000
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#yarn resourcemanager.hostname
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yarn.resourcemanager.hostname=10.0.86.191
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#if you want to use hive, set hive metastore uris
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#hive.metastore.uris=thrift://10.0.88.71:9083
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#show data in log, set 0 if you do not want to show data in logs
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data.show=10
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#server port
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server.port=8002
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#h2db port
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h2.port=50002
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### 运行PiFlow Web请到如下链接，PiFlow Server 与 PiFlow Web版本要对应：
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- https://github.com/cas-bigdatalab/piflow-web
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### 接口Restful API：
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- flow json（可查看piflow-bin/example文件夹下的流水线样例）
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<details>
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<summary>flow example</summary>
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<pre>
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<code>
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{
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"flow": {
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"name": "MockData",
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"executorMemory": "1g",
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"executorNumber": "1",
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"uuid": "8a80d63f720cdd2301723b7461d92600",
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"paths": [
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{
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"inport": "",
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"from": "MockData",
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"to": "ShowData",
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"outport": ""
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}
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],
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"executorCores": "1",
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"driverMemory": "1g",
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"stops": [
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{
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"name": "MockData",
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"bundle": "cn.piflow.bundle.common.MockData",
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"uuid": "8a80d63f720cdd2301723b7461d92604",
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"properties": {
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"schema": "title:String, author:String, age:Int",
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"count": "10"
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},
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"customizedProperties": {
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}
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},
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{
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"name": "ShowData",
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"bundle": "cn.piflow.bundle.external.ShowData",
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"uuid": "8a80d63f720cdd2301723b7461d92602",
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"properties": {
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"showNumber": "5"
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},
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"customizedProperties": {
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}
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}
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]
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}
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}</code>
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</pre>
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</details>
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- CURL方式：
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- curl -0 -X POST http://10.0.86.191:8002/flow/start -H "Content-type: application/json" -d 'this is your flow json'
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- 命令行方式：
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- set PIFLOW_HOME
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vim /etc/profile
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export PIFLOW_HOME=/yourPiflowPath/piflow-bin
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export PATH=\$PATH:\$PIFLOW_HOME/bin
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- command example
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piflow flow start yourFlow.json
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piflow flow stop appID
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piflow flow info appID
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piflow flow log appID
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piflow flowGroup start yourFlowGroup.json
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piflow flowGroup stop groupId
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piflow flowGroup info groupId
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## Docker镜像
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- 根据需求拉取不同版本PiFlow docker镜像
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docker pull registry.cn-hangzhou.aliyuncs.com/cnic_piflow/piflow:v0.7.1
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docker pull registry.cn-hangzhou.aliyuncs.com/cnic_piflow/piflow:v0.6.1
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- 查看Docker镜像的信息
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docker images
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- 通过镜像Id运行一个Container，所有PiFlow服务会自动运行
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docker run --name piflow-v0.6 -it [imageID]
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- 访问 "containerip:6001/piflow-web", 启动时间可能有些慢，需要等待几分钟
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- 如果发生错误，所有应用都放在了/opt文件夹下，可自行单独启动服务
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## 页面展示
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- `登录`:
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- `流水线列表`:
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- `创建流水线`:
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- `配置流水线`:
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- `运行流水线`:
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- `监控流水线`:
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- `流水线日志`:
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- `流水线组列表`:
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- `配置流水线组`:
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- `监控流水线组`:
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- `运行态流水线列表`:
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- `流水线模板列表`:
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## 联系我们
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- Name:吴老师
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- Mobile Phone：18910263390
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- WeChat：18910263390
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- Email: wzs@cnic.cn
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- QQ Group：1003489545
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- WeChat group is valid for 7 days
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