前期准备好kafka环境，我这里是1.12.0版本的Flink，Kafka对应版本官方推荐2.4.1，Scala版本2.12

  1. 在kafka目录下启动zookeeper（我这里用的是kafka自带的）
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./bin/zookeeper-server-start.sh -daemon config/zookeeper.properties
  1. 启动kafka
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./bin/kafka-server-start.sh -daemon config/server.properties
  1. 别忘了添加Kafka连接器依赖
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<!-- https://mvnrepository.com/artifact/org.apache.flink/flink-connector-kafka -->
<dependency>
    <groupId>org.apache.flink</groupId>
    <artifactId>flink-connector-kafka_2.12</artifactId>
    <version>1.12.0</version>
</dependency>
  1. 上代码
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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", "IP: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 stream = env.addSource(new FlinkKafkaConsumer[String]("topic名称", new SimpleStringSchema(), properties))

    stream.print()

    // 启动executor，执行任务
    env.execute("Kafka Source")
  }

}
  1. 开启生产者控制台打印数据测试
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./bin/kafka-console-producer.sh --broker-list IP:9092 -topic test