πFlow is an easy to use, powerful big data pipeline system.

• Features
• Architecture
• Requirements
• Getting Started
• PiFlow Docker
• Use Interface
• Principled Stand
• Contact Us

• Easy to use
  • provide a WYSIWYG web interface to configure data flow
  • monitor data flow status
  • check the logs of data flow
  • provide checkpoints
• Strong scalability:
  • Support customized development of data processing components
• Superior performance
  • based on distributed computing engine Spark
• Powerful
  • 100+ data processing components available
  • include Spark、MLlib、Hadoop、Hive、HBase、TDengine、OceanBase、openLooKeng、TiDB、Solr、Redis、Memcache、Elasticsearch、JDBC、MongoDB、HTTP、FTP、XML、CSV、JSON，etc.

• JDK 1.8
• Scala-2.12.18
• Apache Maven 3.1.0 or newer
• Spark-3.4.0
• Hadoop-3.3.0

• install external package

      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
      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
      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
      mvn install:install-file -Dfile=/../piflow/piflow-bundle/lib/edtftpj.jar -DgroupId=ftpClient -DartifactId=edtftp -Dversion=1.0.0 -Dpackaging=jar
  

• mvn clean package -Dmaven.test.skip=true

      [INFO] Replacing original artifact with shaded artifact.
      [INFO] Reactor Summary:
      [INFO]
      [INFO] piflow-project ..................................... SUCCESS [  4.369 s]
      [INFO] piflow-core ........................................ SUCCESS [01:23 min]
      [INFO] piflow-configure ................................... SUCCESS [ 12.418 s]
      [INFO] piflow-bundle ...................................... SUCCESS [02:15 min]
      [INFO] piflow-server ...................................... SUCCESS [02:05 min]
      [INFO] ------------------------------------------------------------------------
      [INFO] BUILD SUCCESS
      [INFO] ------------------------------------------------------------------------
      [INFO] Total time: 06:01 min
      [INFO] Finished at: 2020-05-21T15:22:58+08:00
      [INFO] Final Memory: 118M/691M
      [INFO] ------------------------------------------------------------------------
  

• run piflow server on Intellij:

  • download piflow: git clone https://github.com/cas-bigdatalab/piflow.git

  • import piflow into Intellij

  • edit config.properties file

  • build piflow to generate piflow jar:

    • Edit Configurations --> Add New Configuration --> Maven
    • Name: package
    • Command line: clean package -Dmaven.test.skip=true -X
    • run 'package' (piflow jar file will be built in ../piflow/piflow-server/target/piflow-server-0.9.jar)

  • run HttpService:

    • Edit Configurations --> Add New Configuration --> Application
    • Name: HttpService
    • Main class : cn.piflow.api.Main
    • Environment Variable: SPARK_HOME=/opt/spark-2.2.0-bin-hadoop2.6(change the path to your spark home)
    • run 'HttpService'

  • test HttpService:

    • run /../piflow/piflow-server/src/main/scala/cn/piflow/api/HTTPClientStartMockDataFlow.scala
    • change the piflow server ip and port to your configure

• run piflow server by release version:

  • download piflow.tar.gz:
    https://github.com/cas-bigdatalab/piflow/releases/download/v1.2/piflow-server-v1.5.tar.gz

  • unzip piflow.tar.gz:
    tar -zxvf piflow.tar.gz

  • edit config.properties

  • run start.sh、stop.sh、 restart.sh、 status.sh

  • test piflow server

    • set PIFLOW_HOME

      • vim /etc/profile
        export PIFLOW_HOME=/yourPiflowPath/bin
        export PATH=$PATH:$PIFLOW_HOME/bin

      • command
        piflow flow start example/mockDataFlow.json
        piflow flow stop appID
        piflow flow info appID
        piflow flow log appID

        piflow flowGroup start example/mockDataGroup.json
        piflow flowGroup stop groupId
        piflow flowGroup info groupId

• how to configure config.properties

  #spark and yarn config
  spark.master=yarn
  spark.deploy.mode=cluster
  
  #hdfs default file system
  fs.defaultFS=hdfs://10.0.86.191:9000
  
  #yarn resourcemanager.hostname
  yarn.resourcemanager.hostname=10.0.86.191
  
  #if you want to use hive, set hive metastore uris
  #hive.metastore.uris=thrift://10.0.88.71:9083
  
  #show data in log, set 0 if you do not want to show data in logs
  data.show=10
  
  #server port
  server.port=8002
  
  #h2db port
  h2.port=50002
  
  #If you want to upload python stop,please set hdfs configs
  #example hdfs.cluster=hostname:hostIP
  #hdfs.cluster=master:127.0.0.1
  #hdfs.web.url=master:50070
  

• Visit address, download the corresponding *.tar.gz file, and modify the corresponding configuration file（The version must be consistent with piflow-server）
  • https://github.com/cas-bigdatalab/piflow-web/releases/tag/v1.5
• If you want to upload python stops, please modify docker.service

  vim /usr/lib/systemd/system/docker.service
  ExecStart=/usr/bin/dockerd -H tcp://0.0.0.0:2375 -H unix://var/run/docker.sock
  systemctl daemon-reload
  systemctl restart docker

• flow json

  flow example

      
        {
  "flow": {
    "name": "MockData",
    "executorMemory": "1g",
    "executorNumber": "1",
    "uuid": "8a80d63f720cdd2301723b7461d92600",
    "paths": [
      {
        "inport": "",
        "from": "MockData",
        "to": "ShowData",
        "outport": ""
      }
    ],
    "executorCores": "1",
    "driverMemory": "1g",
    "stops": [
      {
        "name": "MockData",
        "bundle": "cn.piflow.bundle.common.MockData",
        "uuid": "8a80d63f720cdd2301723b7461d92604",
        "properties": {
          "schema": "title:String, author:String, age:Int",
          "count": "10"
        },
        "customizedProperties": {
    }
  },
  {
    "name": "ShowData",
    "bundle": "cn.piflow.bundle.external.ShowData",
    "uuid": "8a80d63f720cdd2301723b7461d92602",
    "properties": {
      "showNumber": "5"
    },
    "customizedProperties": {
  
    }
  }
  
  ]
  }
  }
  

• CURL POST：

  • curl -0 -X POST http://10.0.86.191:8002/flow/start -H "Content-type: application/json" -d 'this is your flow json'

• Command line：

  • set PIFLOW_HOME
    vim /etc/profile
    export PIFLOW_HOME=/yourPiflowPath/piflow-bin
    export PATH=$PATH:$PIFLOW_HOME/bin

  • command example
    piflow flow start yourFlow.json
    piflow flow stop appID
    piflow flow info appID
    piflow flow log appID

    piflow flowGroup start yourFlowGroup.json
    piflow flowGroup stop groupId
    piflow flowGroup info groupId

• pull piflow images
  docker pull registry.cn-hangzhou.aliyuncs.com/cnic_piflow/piflow:v1.5

• show docker images
  docker images

• run a container with piflow imageID ， all services run automatically. Please Set HOST_IP and some docker configs.
  docker run -h master -itd --env HOST_IP=*.*.*.* --name piflow-v1.5 -p 6001:6001 -v /usr/bin/docker:/usr/bin/docker -v /var/run/docker.sock:/var/run/docker.sock --add-host docker.host:*.*.*.* [imageID]

• please visit "HOST_IP:6001", it may take a while

• if somethings goes wrong, all the application are in /opt folder

• Login:

  

• Dashboard:

  

• Flow list:

  

• Create flow:

  

• Configure flow:

  

• Load flow:

  

• Monitor flow:

  

• Flow logs:

  

• Group list:

  

• Configure group:

  

• Monitor group:

  

• Process List:

  

• Template List:

  

• DataSource List:

  

• Schedule List:

  

• StopHub List:

  

• Name:吴老师
• Mobile Phone：18910263390
• WeChat：18910263390
• Email: [email protected]
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