[SPARK-30986] Structured Streaming: mapGroupsWithState UDT serialization does not work

• Type: Bug
• Status: Resolved
• Priority: Major
• Resolution: Duplicate
• Affects Version/s: 2.3.0, 2.4.0
• Component/s: Structured Streaming
• Labels: correctness

Environment

We're using Spark 2.3.0 on Ubuntu Linux and Windows w/ Scala 2.11.8

• Assignee: Unassigned
• Reporter: Bryan Jeffrey
• Created: 28/Feb/20 14:38
• Updated: 02/Mar/20 19:27
• Resolved: 02/Mar/20 19:27

Description

Hello.  
 
I'm running Scala 2.11 w/ Spark 2.3.0.  I've encountered a problem with mapGroupsWithState, and was wondering if anyone had insight.  We use Joda time in a number of data structures, and so we've generated a custom serializer for Joda.  This works well in most dataset/dataframe structured streaming operations. However, when running mapGroupsWithState we observed that incorrect dates were being returned from a state.
 
Simple example:
1. Input A has a date D
2. Input A updates state in mapGroupsWithState. Date present in state is D
3. Input A is added again.  Input A has correct date D, but existing state now has invalid date
 
Here is a simple repro:
 
Joda Time UDT:
 

private[sql] class JodaTimeUDT extends UserDefinedType[DateTime] {
 override def sqlType: DataType = LongType
 override def serialize(obj: DateTime): Long = obj.getMillis
 def deserialize(datum: Any): DateTime = datum match \{ case value: Long => new DateTime(value, DateTimeZone.UTC) }
 override def userClass: Class[DateTime] = classOf[DateTime]
 private[spark] override def asNullable: JodaTimeUDT = this
}

object JodaTimeUDTRegister {
 def register : Unit = \{ UDTRegistration.register(classOf[DateTime].getName, classOf[JodaTimeUDT].getName) }
}

 
Test Leveraging Joda UDT:
 

case class FooWithDate(date: DateTime, s: String, i: Int)

@RunWith(classOf[JUnitRunner])
class TestJodaTimeUdt extends FlatSpec with Matchers with MockFactory with BeforeAndAfterAll {
  val application = this.getClass.getName
  var session: SparkSession = _

  override def beforeAll(): Unit = {
    System.setProperty("hadoop.home.dir", getClass.getResource("/").getPath)
    val sparkConf = new SparkConf()
      .set("spark.driver.allowMultipleContexts", "true")
      .set("spark.testing", "true")
      .set("spark.memory.fraction", "1")
      .set("spark.ui.enabled", "false")
      .set("spark.streaming.gracefulStopTimeout", "1000")
      .setAppName(application).setMaster("local[*]")


    session = SparkSession.builder().config(sparkConf).getOrCreate()
    session.sparkContext.setCheckpointDir("/")
    JodaTimeUDTRegister.register
  }

  override def afterAll(): Unit = {
    session.stop()
  }

  it should "work correctly for a streaming input with stateful transformation" in {
    val date = new DateTime(2020, 1, 2, 3, 4, 5, 6, DateTimeZone.UTC)
    val sqlContext = session.sqlContext
    import sqlContext.implicits._

    val input = List(FooWithDate(date, "Foo", 1), FooWithDate(date, "Foo", 3), FooWithDate(date, "Foo", 3))
    val streamInput: MemoryStream[FooWithDate] = new MemoryStream[FooWithDate](42, session.sqlContext)
    streamInput.addData(input)
    val ds: Dataset[FooWithDate] = streamInput.toDS()

    val mapGroupsWithStateFunction: (Int, Iterator[FooWithDate], GroupState[FooWithDate]) => FooWithDate = TestJodaTimeUdt.updateFooState
    val result: Dataset[FooWithDate] = ds
      .groupByKey(x => x.i)
      .mapGroupsWithState(GroupStateTimeout.ProcessingTimeTimeout())(mapGroupsWithStateFunction)
    val writeTo = s"random_table_name"

    result.writeStream.outputMode(OutputMode.Update).format("memory").queryName(writeTo).trigger(Trigger.Once()).start().awaitTermination()
    val combinedResults: Array[FooWithDate] = session.sql(sqlText = s"select * from $writeTo").as[FooWithDate].collect()
    val expected = Array(FooWithDate(date, "Foo", 1), FooWithDate(date, "FooFoo", 6))
    combinedResults should contain theSameElementsAs(expected)
  }
}

object TestJodaTimeUdt {
  def updateFooState(id: Int, inputs: Iterator[FooWithDate], state: GroupState[FooWithDate]): FooWithDate = {
    if (state.hasTimedOut) {
      state.remove()
      state.getOption.get
    } else {
      val inputsSeq: Seq[FooWithDate] = inputs.toSeq
      val startingState = state.getOption.getOrElse(inputsSeq.head)
      val toProcess = if (state.getOption.isDefined) inputsSeq else inputsSeq.tail
      val updatedFoo = toProcess.foldLeft(startingState)(concatFoo)

      state.update(updatedFoo)
      state.setTimeoutDuration("1 minute")
      updatedFoo
    }
  }

  def concatFoo(a: FooWithDate, b: FooWithDate): FooWithDate = FooWithDate(b.date, a.s + b.s, a.i + b.i)
}

The test output shows the invalid date:

   
org.scalatest.exceptions.TestFailedException:
Array(FooWithDate(2021-02-02T19:26:23.374Z,Foo,1), FooWithDate(2021-02-02T19:26:23.374Z,FooFoo,6)) did not contain the same elements as
Array(FooWithDate(2020-01-02T03:04:05.006Z,Foo,1), FooWithDate(2020-01-02T03:04:05.006Z,FooFoo,6))

Issue Links

• duplicates: SPARK-30993 GenerateUnsafeRowJoiner corrupts the value if the datatype is UDF and its sql type has fixed length