python flink kafka_Windows下Flink读取Kafka

代码:

import java.util.Properties

import org.apache.flink.api.common.serialization.SimpleStringSchema

import org.apache.flink.streaming.api.scala.StreamExecutionEnvironment

import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer011

//温度传感器读取样例类

case class SensorReading(id: String, timestamp: Long, temperature: Double)

object SourceTest {

def main(args: Array[String]): Unit = {

val env = StreamExecutionEnvironment.getExecutionEnvironment

//1.从自定义的集合中读取数据

import org.apache.flink.api.scala._

// val stream1 = env.fromCollection(List(SensorReading("sensor_1", 1547718199, 35.80018327300259),

// SensorReading("sensor_6", 1547718201, 15.402984393403084),

// SensorReading("sensor_7", 1547718202, 6.720945201171228),

// SensorReading("sensor_10", 1547718205, 38.101067604893444)

// ))

// stream1.print("stream1").setParallelism(1)

// env.execute("source test")

//

// //2.从文件读取数据

// val stream2 = env.readTextFile("sensor.txt")

// stream2.print("stream2").setParallelism(1)

// env.execute("source test")

//3.以 kafka 消息队列的数据作为来源

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 stream3 = env.addSource(new FlinkKafkaConsumer011[String]("sensor", new SimpleStringSchema(), properties))

stream3.print("stream3").setParallelism(1)

env.execute("source test")

}

}

1.启动zookerper

2.启动Kafka

3.启动Producer并发送数据

4.结果

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