flink_kafka consumer

原创已于 2022-03-16 16:48:48 修改 · 2.1k 阅读

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#kafka #分布式

于 2022-03-16 16:47:00 首次发布

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该博客展示了如何使用Apache Flink从Kafka消费者读取数据并进行处理。代码中定义了一个FlinkKafkaConsumer，配置了Kafka的bootstrap服务器地址，并创建了一个DataStream，然后打印出数据。整个流程简单明了，是Flink与Kafka集成的一个基础示例。

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import org.apache.flink.streaming.api.scala.DataStream
import org.apache.flink.streaming.api.scala.StreamExecutionEnvironment
import org.apache.flink.api.scala._
import nn.MyKafkaUtil

object StartupApp {
def main(args: Array[String]): Unit = {
val environment: StreamExecutionEnvironment = StreamExecutionEnvironment.getExecutionEnvironment

val kafkaConsumer =MyKafkaUtil.getConsumer("gl")

val dstream: DataStream[String] = environment.addSource(kafkaConsumer)
dstream.print()
environment.execute()
}
}
############################
package nn

import java.util.Properties

import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer
import org.apache.flink.api.common.serialization.SimpleStringSchema
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer

object MyKafkaUtil {

// val prop = new Properties()
private val prop = new Properties()
prop.setProperty("bootstrap.servers","localhost:9092")
// prop.setProperty("group.id","gmall")

def getConsumer(topic:String ):FlinkKafkaConsumer[String]= {
val myKafkaConsumer:FlinkKafkaConsumer[String] = new FlinkKafkaConsumer[String](topic, new SimpleStringSchema(), prop)
myKafkaConsumer
}
}