Flink 输出至 Elasticsearch-Toy模板网

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【1】引入pom.xml依赖

<dependency>
    <groupId>org.apache.flink</groupId>
    <artifactId>flink-connector-elasticsearch6_2.12</artifactId>
    <version>1.10.0</version>
</dependency>

【2】ES6 Scala代码，自动导入的scala包需要修改为scala._ 否则会出现错误。

package com.zzx.flink

import java.util

import org.apache.flink.api.common.functions.RuntimeContext
import org.apache.flink.streaming.api.scala._
import org.apache.flink.streaming.connectors.elasticsearch.{ElasticsearchSinkFunction, RequestIndexer}
import org.apache.flink.streaming.connectors.elasticsearch6.ElasticsearchSink
import org.apache.http.HttpHost
import org.elasticsearch.client.Requests


object EsSinkTest {
  def main(args: Array[String]): Unit = {
    // 创建一个流处理执行环境
    val env = StreamExecutionEnvironment.getExecutionEnvironment
    //从文件中读取数据并转换为 类
    val inputStreamFromFile: DataStream[String] = env.readTextFile("E:\\Project\\flink\\src\\main\\resources\\wordcount.txt")
    //转换
    val dataStream: DataStream[SensorReading] = inputStreamFromFile
      .map( data => {
        var dataArray = data.split(",")
        SensorReading(dataArray(0),dataArray(1).toLong,dataArray(2).toDouble)
      })

    //定义一个 HttpHosts
    val httpHost = new util.ArrayList[HttpHost]()
    //默认 9200 我的修改为了 9201
    httpHost.add(new HttpHost("192.168.1.12",9200,"http"))
    httpHost.add(new HttpHost("127.0.0.1",9200,"http"))
    //定义一个 ElasticSearchFuntion 操作 es的function
    val esSinkFunc = new ElasticsearchSinkFunction[SensorReading] {
      //element 每一条数据 通过 index 发送
      override def process(element: SensorReading, runtimeContext: RuntimeContext, index: RequestIndexer): Unit = {
        //包装写入 es 的数据
        val dataSource = new util.HashMap[String,String]()
        dataSource.put("sensor_id",element.id)
        dataSource.put("temp",element.temperature.toString)
        dataSource.put("ts",element.timestamp.toString)

        //index
        val indexRequest = Requests.indexRequest()
            .index("sensor_temp")
            .`type`("readingdata")
            .source(dataSource)
        index.add(indexRequest)
        println("saved successfully " + element.toString)
      }
    }
    //输出值 es
    dataStream.addSink(new ElasticsearchSink.Builder[SensorReading](httpHost,esSinkFunc).build())
    env.execute("es")
  }
}