用spark streaming实时读取hdfs数据并写入elasticsearch中

1.首先用sqoop将MysqL数据定时导入到hdfs中，然后用spark streaming实时读取hdfs的数据，并把数据写入elasticsearch中。代码如下

------bigdata.project.spark----------
package bigdata.project.spark
import org.apache.spark.{SparkConf, SparkContext}
import org.apache.spark.rdd.RDD
import org.apache.spark.streaming.{Seconds, StreamingContext}
import org.elasticsearch.spark.sql._
object sparkstreamingcopynew {
  def main(args: Array[String]): Unit = {
    val sparkconf = new SparkConf().setMaster("local[2]").setAppName("sparkstreamingcopynew")
    sparkconf.set("es.nodes", "localhost")
    sparkconf.set("es.port", "9200")
    sparkconf.set("es.index.auto.create", "true")
    sparkconf.set("spark.driver.allowMultipleContexts","true")
    sparkconf.set("empty", "true")
    val sc= new SparkContext(sparkconf)
    val ssc = new StreamingContext(sc,Seconds(10))
    import org.apache.spark.streaming.Time
    val lines = ssc.textFileStream("hdfs://hadoop:9000/ershoufang")
      lines.foreachRDD((rdd: RDD[String],time: Time)=> {
        val sqlContext = sqlContextSingleton.getInstance(rdd.sparkContext)
        import sqlContext.implicits._
        val wordsDataFrame = rdd.map(x => (x.split(",")(0), x.split(",")(1), x.split(",")(2),
          x.split(",")(3), x.split(",")(4), x.split(",")(5), x.split(",")(6),
          x.split(",")(8), x.split(",")(9), x.split(",")(10), x.split(",")(11),x.split(",")(12)))
          .map(w => RecordEs(w._1.toInt, w._2, w._3,w._4,w._5,w._6,w._7,w._8,w._9,w._10,w._11,w._12)).toDF()
        val dataDS=wordsDataFrame.as[RecordEs]
        //val datardd= wordsDataFrame.rdd
        Essparksql.savetoEs(dataDS,"zufang/docs")
        wordsDataFrame.registerTempTable("RecordEs")
        val wordCountsDataFrame =
          sqlContext.sql("select id,title,city,huose_type,area,location,direction,price, url,origin,publish_date,true_date from RecordEs")
        println(s"========= $time =========")
        wordCountsDataFrame.show()
        })
    ssc.start()
    ssc.awaitTermination()
  }
}

package bigdata.project.spark

import org.apache.spark.SparkContext
import org.apache.spark.sql.sqlContext

object sqlContextSingleton {
  @transient  private var instance: sqlContext = _
  def getInstance(sparkContext: SparkContext): sqlContext = {
    if (instance == null) {
      instance = new sqlContext(sparkContext)
    }
    instance
  }
}

package bigdata.project.spark

package bigdata.project.spark

case class RecordEs(id: Int,title: String,city: String,huose_type: String,area:String,location:String,direction:String
                    ,price:String, url:String,origin:String,publish_date:String,true_date:String)