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Scala Sample Code

Following is the main logic code for demonstration.

For details about the complete code, see the following:

  • com.huawei.bigdata.flink.examples.UserSource.
  • com.huawei.bigdata.flink.examples.TestPipeline_NettySink.
  • com.huawei.bigdata.flink.examples.TestPipeline_NettySource1.
  • com.huawei.bigdata.flink.examples.TestPipeline_NettySource2.
  1. Code for sending messages:
package com.huawei.bigdata.flink.examples
 
case class Inforamtion(index: Int, content: String) {
 
  def this() = this(0, "")
}
  1. The publisher customizes source operators to generate data.
package com.huawei.bigdata.flink.examples
 
import org.apache.flink.configuration.Configuration
import org.apache.flink.streaming.api.functions.source.RichParallelSourceFunction
import org.apache.flink.streaming.api.functions.source.SourceFunction.SourceContext
 
class UserSource extends RichParallelSourceFunction[Inforamtion] with Serializable{
 
  var isRunning = true
 
  override def open(parameters: Configuration): Unit = {
    super.open(parameters)
   
  }
 
// Generate 10000 pieces of data each second.
  override def run(sourceContext: SourceContext[Inforamtion]) = {
 
    while (isRunning) {
      for (i <- 0 until 10000) {
        sourceContext.collect(Inforamtion(i, "hello-" + i));
 
      }
      Thread.sleep(1000)
    }
  }
 
  override def close(): Unit = super.close()
 
  override def cancel() = {
    isRunning = false
  }
}
  1. Code for the publisher:
package com.huawei.bigdata.flink.examples
 
import org.apache.flink.streaming.api.scala.StreamExecutionEnvironment
import org.apache.flink.streaming.connectors.netty.sink.NettySink
import org.apache.flink.streaming.connectors.netty.utils.ZookeeperRegisterServerHandler
import org.apache.flink.streaming.api.scala._
 
object TestPipeline_NettySink {
 
  def main(args: Array[String]): Unit = {
 
    val env = StreamExecutionEnvironment.getExecutionEnvironment
// Set the concurrency of job to 2.
  env.setParallelism(2)
//Set Zookeeper as the registration server
    val zkRegisterServerHandler = new ZookeeperRegisterServerHandler
//Add a user-defined operator to generate data.    
env.addSource(new UserSource)     .keyBy(0).map(x=>x.content.getBytes)//Transform the to-be-sent data into a byte array. 
      .addSink(new NettySink("NettySink-1", "TOPIC-2", zkRegisterServerHandler, 2))//Add NettySink operator to send data. 
    env.execute()
  }
}
  1. Code for the first subscriber
package com.huawei.bigdata.flink.examples
 
import org.apache.flink.streaming.api.scala.StreamExecutionEnvironment
import org.apache.flink.streaming.connectors.netty.source.NettySource
import org.apache.flink.streaming.connectors.netty.utils.ZookeeperRegisterServerHandler
import org.apache.flink.streaming.api.scala._
 
import scala.util.Random
 
 
object TestPipeline_NettySource1 {
 
  def main(args: Array[String]): Unit = {
 
    val env = StreamExecutionEnvironment.getExecutionEnvironment
// Set the concurrency of job to 2.  
  env.setParallelism(2)
//Set ZooKeeper as the registration server
val zkRegisterServerHandler = new ZookeeperRegisterServerHandler
//Add a NettySource operator to receive messages from the publisher.
    env.addSource(new NettySource("NettySource-1", "TOPIC-2", zkRegisterServerHandler))
      .map(x => (1, new String(x)))//Add a NettySource operator to receive messages from the publisher.
      .filter(x => {
        Random.nextInt(50000) == 10
      })
      .print
 
    env.execute()
  }
}
  1. Code for the second subscriber.
package com.huawei.bigdata.flink.examples
 
import org.apache.flink.streaming.api.scala.StreamExecutionEnvironment
import org.apache.flink.streaming.connectors.netty.source.NettySource
import org.apache.flink.streaming.connectors.netty.utils.ZookeeperRegisterServerHandler
import org.apache.flink.streaming.api.scala._
 
import scala.util.Random
 
 
object TestPipeline_NettySource2 {
 
  def main(args: Array[String]): Unit = {
 
    val env = StreamExecutionEnvironment.getExecutionEnvironment
//Set the concurrency of job to 2.   
 env.setParallelism(2)
//Set the concurrency of job to 2.
    val zkRegisterServerHandler = new ZookeeperRegisterServerHandler
//Add NettySource operator and receive data.
    
env.addSource(new NettySource("NettySource-2", "TOPIC-2", zkRegisterServerHandler))
      .map(x=>(2, new String(x)))//Transform the received byte array into character strings.

      .filter(x=>{
        Random.nextInt(50000) == 10
      })
      .print()
 
    env.execute()
  }
}
Parent topic: Job Pipeline Program