Flink 实时消费多个 topic 数据

package com.demo

import java.util
import java.util.Properties
import org.apache.flink.api.common.serialization.SimpleStringSchema
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer

object KafkaSource {

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

//    创建流处理环境
    val env = StreamExecutionEnvironment.getExecutionEnvironment

    val properties = new Properties()
    properties.setProperty("bootstrap.servers", "10.7.2.20:9092")
    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 topics = new util.LinkedList[String]
    topics.add("test1")
    topics.add("test2")

//    val stream = env.addSource(new FlinkKafkaConsumer[String]("test", new SimpleStringSchema(), properties))
    val stream = env.addSource(new FlinkKafkaConsumer[String](topics, new SimpleStringSchema(), properties))

    stream.print()

    // 启动executor，执行任务
    env.execute("Socket stream word count")
  }

}