Flink从入门到真香(10、Sink数据输出-Elasticsearch）

目标： 从txt文件中读取数据，写入es,我这里用的es7.9，如果用的es7之前的版本下面代码中有个.type("_doc") 类别需要设置

如果没有es和kibana(可选)环境可以先安装

安装es7

wget https://artifacts.elastic.co/downloads/elasticsearch/elasticsearch-7.9.3-x86_64.rpm
wget https://artifacts.elastic.co/downloads/elasticsearch/elasticsearch-7.9.3-x86_64.rpm.sha512
shasum -a 512 -c elasticsearch-7.9.3-x86_64.rpm.sha512 
sudo rpm --install elasticsearch-7.9.3-x86_64.rpm
systemctl restart elasticsearch

安装kibana (可选，如果不想界面操作就可以不用装)

wget https://artifacts.elastic.co/downloads/kibana/kibana-7.9.3-x86_64.rpm
sudo rpm --install kibana-7.9.3-x86_64.rpm
 
systemctl start kibana

先引入Elasticsearch的pom依赖

<dependency>
    <groupId>org.apache.flink</groupId>
    <artifactId>flink-connector-elasticsearch7_2.12</artifactId>
    <version>1.10.1</version>
</dependency>

新建一个ElasticsearchSinkTest.scala

package com.mafei.sinktest
 
import java.util
 
import org.apache.flink.api.common.functions.RuntimeContext
import org.apache.flink.streaming.api.scala.{StreamExecutionEnvironment, createTypeInformation}
import org.apache.flink.streaming.connectors.elasticsearch.{ElasticsearchSinkFunction, RequestIndexer}
import org.apache.flink.streaming.connectors.elasticsearch7.ElasticsearchSink
import org.apache.http.HttpHost
import org.elasticsearch.client.Requests
 
object ElasticsearchSinkTest {
  def main(args: Array[String]): Unit = {
    //创建执行环境
    val env = StreamExecutionEnvironment.getExecutionEnvironment
 
    val inputStream = env.readTextFile("/opt/java2020_study/maven/flink1/src/main/resources/sensor.txt")
    env.setParallelism(1)
    inputStream.print()
 
    //先转换成样例类类型
    val dataStream = inputStream
      .map(data => {
        val arr = data.split(",") //按照,分割数据，获取结果
        SensorReadingTest5(arr(0), arr(1).toLong, arr(2).toDouble) //生成一个传感器类的数据，参数中传toLong和toDouble是因为默认分割后是字符串类别
      })
 
    //定义es的连接信息
    val httpHosts = new util.ArrayList[HttpHost]()
    httpHosts.add(new HttpHost("127.0.0.1", 9200))
 
    //自定义写入es的ElasticsearchSinkFunction
    val myEsSinkFunc = new ElasticsearchSinkFunction[SensorReadingTest5] {
      override def process(t: SensorReadingTest5, runtimeContext: RuntimeContext, requestIndexer: RequestIndexer): Unit = {
        //定义一个map作为 数据源
        val dataSource = new util.HashMap[String, String]()
        dataSource.put("id", t.id)
        dataSource.put("temperature", t.temperature.toString)
        dataSource.put("ts", t.timestamp.toString)
 
        //创建index request ，指定index
        val indexRequest = Requests.indexRequest()
        indexRequest.index("sensors") //指定写入哪一个索引
          .source(dataSource) //指定写入的数据
        //            .type("_doc")  //我这里用的es7已经不需要这个参数了
 
        //执行新增操作
        requestIndexer.add(indexRequest)
      }
    }
 
    dataStream.addSink(new ElasticsearchSink.Builder[SensorReadingTest5](httpHosts, myEsSinkFunc)
      .build()
    )
    env.execute()
  }
}

代码结构：

到服务器上查看数据，sensor就是我们刚塞进去的数据
查看所有索引数据
[root@localhost ~]# curl http://127.0.0.1:9200/_cat/indices
green open .kibana-event-log-7.9.3-000001 NvnP2SI9Q_i-z5bNvsgWhA 1 0 1 0 5.5kb 5.5kb
yellow open sensors PGTeT0MZRJ-4hmYkDQnqIw 1 1 6 0 5.4kb 5.4kb
green open .apm-custom-link IdxoOaP9Sh6ssBd0Q9kPsw 1 0 0 0 208b 208b
green open .kibana_task_manager_1 -qAi_8LmTc2eJsWUQwugtw 1 0 6 3195 434.2kb 434.2kb
green open .apm-agent-configuration FG9PE8CARdyKWrdsAg4gbA 1 0 0 0 208b 208b
green open .kibana_1 uVmly8KaQ5uIXZ-IkArnVg 1 0 18 4 10.4mb 10.4m

查看塞进去的数据

[root@localhost ~]# curl http://127.0.0.1:9200/sensors/_search
{"took":0,"timed_out":false,"_shards":{"total":1,"successful":1,"skipped":0,"failed":0},"hits":{"total":{"value":6,"relation":"eq"},"max_score":1.0,"hits":[{"_index":"sensors","_type":"_doc","_id":"h67gkHUBr1E85RDXoNXP","_score":1.0,"_source":{"temperature":"41.0","id":"sensor1","ts":"1603766281"}},{"_index":"sensors","_type":"_doc","_id":"iK7gkHUBr1E85RDXoNXP","_score":1.0,"_source":{"temperature":"42.0","id":"sensor2","ts":"1603766282"}},{"_index":"sensors","_type":"_doc","_id":"ia7gkHUBr1E85RDXoNXP","_score":1.0,"_source":{"temperature":"43.0","id":"sensor3","ts":"1603766283"}},{"_index":"sensors","_type":"_doc","_id":"iq7gkHUBr1E85RDXoNXP","_score":1.0,"_source":{"temperature":"40.1","id":"sensor4","ts":"1603766240"}},{"_index":"sensors","_type":"_doc","_id":"i67gkHUBr1E85RDXoNXP","_score":1.0,"_source":{"temperature":"20.0","id":"sensor4","ts":"1603766284"}},{"_index":"sensors","_type":"_doc","_id":"jK7gkHUBr1E85RDXoNXP","_score":1.0,"_source":{"temperature":"40.2","id":"sensor4","ts":"1603766249"}}]}}