SparkMultiThreading.scala

import org.apache.spark.SparkConf
import org.apache.spark.sql.SparkSession

/**
  * Created by vgiridatabricks on 2/1/17.
  */
object SparkMultiThreading {
  def main(args: Array[String]): Unit = {

    val spark = SparkSession
      .builder()
      .appName("Spark Multi Threading Example")
      .master("local")
      .getOrCreate()


    //Using Threads
    import org.apache.spark.sql.functions._

    import spark.implicits._

    case class SimpsonCharacter(name: String, actor: String, episodeDebut: String)

    val employee = spark.range(0, 100).select($"id".as("employee_id"), (rand() * 3).cast("int").as("dep_id"), (rand() * 40 + 20).cast("int").as("age")).toDF()

    val simpsonsDF = spark.sparkContext.parallelize(
      SimpsonCharacter("Homer", "Dan Castellaneta", "Good Night") ::
        SimpsonCharacter("Marge", "Julie Kavner", "Good Night") ::
        SimpsonCharacter("Bart", "Nancy Cartwright", "Good Night") ::
        SimpsonCharacter("Lisa", "Yeardley Smith", "Good Night") ::
        SimpsonCharacter("Maggie", "Liz Georges and more", "Good Night") ::
        SimpsonCharacter("Sideshow Bob", "Kelsey Grammer", "The Telltale Head") ::
        Nil)

    for (a <- 0 until 20) {
      val thread = new Thread {
        override def run {
          spark.sparkContext.parallelize(Array("aaa", "bbb", "ccc")).toDF().write.format("parquet").mode("overWrite").save("/tmp/vgiri/file1")
          spark.sparkContext.parallelize(Array("ddd", "eee", "fff")).toDF().write.format("parquet").mode("overWrite").save("/tmp/vgiri/file2")
          spark.sparkContext.parallelize(Array("ggg", "hhh", "iii")).toDF().write.format("parquet").mode("overWrite").save("/tmp/vgiri/file3")
          spark.sparkContext.parallelize(Array("jjj", "kkk", "lll")).toDF().write.format("parquet").mode("overWrite").save("/tmp/vgiri/file4")
          spark.sparkContext.parallelize(Array("mmm", "nnn", "ooo")).toDF().write.format("parquet").mode("overWrite").save("/tmp/vgiri/file5")
          spark.sparkContext.parallelize(Array("ppp", "qqq", "rrr")).toDF().write.format("parquet").mode("overWrite").save("/tmp/vgiri/file6")
          spark.sparkContext.parallelize(Array("sss", "ttt", "uuu")).toDF().write.format("parquet").mode("overWrite").save("/tmp/vgiri/file7")
          spark.sparkContext.parallelize(Array("aaa", "bbb", "ccc")).toDF().write.format("parquet").mode("overWrite").save("/tmp/vgiri/file8")
          spark.sparkContext.parallelize(Array("ddd", "eee", "fff")).toDF().write.format("parquet").mode("overWrite").save("/tmp/vgiri/file9")
          spark.sparkContext.parallelize(Array("ggg", "hhh", "iii")).toDF().write.format("parquet").mode("overWrite").save("/tmp/vgiri/file10")
          spark.sparkContext.parallelize(Array("jjj", "kkk", "lll")).toDF().write.format("parquet").mode("overWrite").save("/tmp/vgiri/file11")
          spark.sparkContext.parallelize(Array("mmm", "nnn", "ooo")).toDF().write.format("parquet").mode("overWrite").save("/tmp/vgiri/file12")
          spark.sparkContext.parallelize(Array("ppp", "qqq", "rrr")).toDF().write.format("parquet").mode("overWrite").save("/tmp/vgiri/file13")
          spark.sparkContext.parallelize(Array("sss", "ttt", "uuu")).toDF().write.format("parquet").mode("overWrite").save("/tmp/vgiri/file14")
          simpsonsDF.write.format("parquet").mode("overwrite").save("/tmp/vgiri/simpsonsDF_files")
          employee.createOrReplaceTempView("employee")
          spark.table("employee").write.mode("overWrite").format("parquet").saveAsTable("emp")
        }

      }
      thread.start
    }

  }

}

It was very nice to see SparkMultiThreading. I tried in cluster mode and data is not written into the table.
When I tried from the prompt(not in cluster mode), it worked. Any idea ?

It was very nice to see SparkMultiThreading. I tried in cluster mode and data is not written into the table.
When I tried from the prompt(not in cluster mode), it worked. Any idea ?

SPARK-29046

It was very nice to see SparkMultiThreading. I tried in cluster mode and data is not written into the table.
When I tried from the prompt(not in cluster mode), it worked. Any idea ?

SPARK-29046

or try to use : java.util.concurrent.Semaphore to wait all the sub thread to be finished before the main thread stop the sparkcontext.