Flink输出到Kafka(两种方式)

文报 2020-01-09

方式一:读取文件输出到Kafka   

   1.代码

import org.apache.flink.api.common.serialization.SimpleStringSchemaimport org.apache.flink.streaming.api.scala.StreamExecutionEnvironmentimport org.apache.flink.streaming.connectors.kafka.FlinkKafkaProducer011//温度传感器读取样例类case class SensorReading(id: String, timestamp: Long, temperature: Double)object KafkaSinkTest {  def main(args: Array[String]): Unit = {    val env = StreamExecutionEnvironment.getExecutionEnvironment    env.setParallelism(1)    import org.apache.flink.api.scala._    val inputStream = env.readTextFile("sensor.txt")    val dataStream = inputStream.map(x => {      val arr = x.split(",")      SensorReading(arr(0).trim, arr(1).trim.toLong, arr(2).trim.toDouble).toString   //转成String方便序列化输出    })    //sink    dataStream.addSink(new FlinkKafkaProducer011[String]("localhost:9092", "sinkTest", new SimpleStringSchema()))    dataStream.print()    env.execute(" kafka sink test")  }}2.启动zookeeper:参考https://www.cnblogs.com/wddqy/p/12156527.html3.启动kafka:参考https://www.cnblogs.com/wddqy/p/12156527.html4.创建kafka消费者观察结果

Flink输出到Kafka(两种方式)

方式二:Kafka到Kafka   

   1.代码

import java.util.Propertiesimport org.apache.flink.api.common.serialization.SimpleStringSchemaimport org.apache.flink.streaming.api.scala.StreamExecutionEnvironmentimport org.apache.flink.streaming.connectors.kafka.{FlinkKafkaConsumer011, FlinkKafkaProducer011}//温度传感器读取样例类case class SensorReading(id: String, timestamp: Long, temperature: Double)object KafkaSinkTest1 {  def main(args: Array[String]): Unit = {    val env = StreamExecutionEnvironment.getExecutionEnvironment    env.setParallelism(1)    import org.apache.flink.api.scala._    //从Kafka到Kafka    val properties = new Properties()    properties.setProperty("bootstrap.servers", "localhost:9092")    properties.setProperty("group.id", "consumer-group")    properties.setProperty("key.deserializer", "org.apache.kafka.common.serialization.StringDeserializer")    properties.setProperty("value.deserializer", "org.apache.kafka.common.serialization.StringDeserializer")    properties.setProperty("auto.offset.reset", "latest")    val inputStream = env.addSource(new FlinkKafkaConsumer011[String]("sensor", new SimpleStringSchema(), properties))    val dataStream = inputStream.map(x => {      val arr = x.split(",")      SensorReading(arr(0).trim, arr(1).trim.toLong, arr(2).trim.toDouble).toString   //转成String方便序列化输出    })    //sink    dataStream.addSink(new FlinkKafkaProducer011[String]("localhost:9092", "sinkTest", new SimpleStringSchema()))    dataStream.print()    env.execute(" kafka sink test")  }}
2.启动zookeeper:参考https://www.cnblogs.com/wddqy/p/12156527.html3.启动kafka:参考https://www.cnblogs.com/wddqy/p/12156527.html4.创建Kafka生产者和消费者,运行代码,观察结果

Flink输出到Kafka(两种方式)

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