flink jdbc方式下沉到hive

import java.sql.{Connection, DriverManager, PreparedStatement}

import it.bigdata.flink.study.SensorReding
import org.apache.flink.configuration.Configuration
import org.apache.flink.streaming.api.functions.sink.RichSinkFunction
import org.apache.flink.streaming.api.scala._

object HiveJdbcSink {
  def main(args: Array[String]): Unit = {
    //创建环境
    val env = StreamExecutionEnvironment.getExecutionEnvironment
    env.setParallelism(1)

    //读取数据
    val inputPath="D:\\ideaDemo\\maven_flink\\src\\main\\resources\\sensor.txt"
    val inputStream = env.readTextFile(inputPath)

    //简单转换
    val dataStream = inputStream.map(data => {
      var arr = data.split(",")
      SensorReding(arr(0), arr(1).toLong, arr(1).toDouble)
    })

    dataStream.addSink(new MyJdbcHiveSinkFunc())

    env.execute("JdbcHive sink test")
  }

}


class MyJdbcHiveSinkFunc() extends RichSinkFunction[SensorReding]{
  //定义连接、预编译语句

  var conn:Connection =_
  var insetstmt:PreparedStatement =_

  override def open(parameters: Configuration): Unit = {
    Class.forName("org.apache.hive.jdbc.HiveDriver")
    conn=DriverManager.getConnection("jdbc:hive2://192.168.10.20:10000/hive","root","")
    insetstmt = conn.prepareStatement("insert into tb_tmp_001(id,x) values(?,?)")
  }

  override def invoke(value: SensorReding): Unit = {
    //插入数据
    insetstmt.setString(1,value.id)
    insetstmt.setString(2,value.temperature.toString)
    insetstmt.execute()
  }
  override def close(): Unit = {
    insetstmt.close()
    conn.close()
  }
}

需引入依赖

 <!--start   hive相关依赖-->
        <dependency>
            <groupId>org.apache.hive</groupId>
            <artifactId>hive-jdbc</artifactId>
            <version>1.1.0</version>
        </dependency>
        <dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-common</artifactId>
            <version>2.6.0</version>
        </dependency>
        <dependency>
            <groupId>org.apache.hive</groupId>
            <artifactId>hive-exec</artifactId>
            <version>3.1.2</version>
        </dependency>
        <!--end   hive相关依赖-->