Spark Structured Streaming, multiples queries are not running concurrently

Question

I slightly modified example taken from here - https://github.com/apache/spark/blob/v2.2.0/examples/src/main/scala/org/apache/spark/examples/sql/streaming/StructuredNetworkWordCount.scala

I added seconds writeStream (sink):

scala
case class MyWriter1() extends ForeachWriter[Row]{
  override def open(partitionId: Long, version: Long): Boolean = true

  override def process(value: Row): Unit = {
    println(s"custom1 - ${value.get(0)}")
  }

  override def close(errorOrNull: Throwable): Unit = true
}

case class MyWriter2() extends ForeachWriter[(String, Int)]{
  override def open(partitionId: Long, version: Long): Boolean = true

  override def process(value: (String, Int)): Unit = {
    println(s"custom2 - $value")
  }

  override def close(errorOrNull: Throwable): Unit = true
}


object Main extends Serializable{

  def main(args: Array[String]): Unit = {
    println("starting")

    Logger.getLogger("org").setLevel(Level.OFF)
    Logger.getLogger("akka").setLevel(Level.OFF)

    val host = "localhost"
    val port = "9999"

    val spark = SparkSession
      .builder
      .master("local[*]")
      .appName("app-test")
      .getOrCreate()

    import spark.implicits._

    // Create DataFrame representing the stream of input lines from connection to host:port
    val lines = spark.readStream
      .format("socket")
      .option("host", host)
      .option("port", port)
      .load()

    // Split the lines into words
    val words = lines.as[String].flatMap(_.split(" "))

    // Generate running word count
    val wordCounts = words.groupBy("value").count()

    // Start running the query that prints the running counts to the console
    val query1 = wordCounts.writeStream
      .outputMode("update")
      .foreach(MyWriter1())
      .start()

    val ds = wordCounts.map(x => (x.getAs[String]("value"), x.getAs[Int]("count")))

    val query2 = ds.writeStream
      .outputMode("update")
      .foreach(MyWriter2())
      .start()

    spark.streams.awaitAnyTermination()

  }
}

Unfortunately, only first query runs, second never runs (MyWriter2 never been called)

Please advice what I'm doing wrong. According to doc: You can start any number of queries in a single SparkSession. They will all be running concurrently sharing the cluster resources.

Answer 1

I had the same situation (but on the newer structured-streaming api) and in my case it helped to call awaitTermination() on the last streamingQuery.

s.th. like:

query1.start()
query2.start().awaitTermination()

Update: Instead above, this build-in solution/method is better:

sparkSession.streams.awaitAnyTermination()

Answer 2

Are you using nc -lk 9999 for sending data to spark ? every query create a connection to nc but nc can only send data to the first connection (query) , you can write a tcp server instead of nc