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Dongjoon Hyun resolved SPARK-30986. ----------------------------------- Resolution: Duplicate > Structured Streaming: mapGroupsWithState UDT serialization does not work > ------------------------------------------------------------------------ > > Key: SPARK-30986 > URL: https://issues.apache.org/jira/browse/SPARK-30986 > Project: Spark > Issue Type: Bug > Components: Structured Streaming > Affects Versions: 2.3.0, 2.4.0 > Environment: We're using Spark 2.3.0 on Ubuntu Linux and Windows w/ > Scala 2.11.8 > Reporter: Bryan Jeffrey > Priority: Major > Labels: correctness > > 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: > > {code:scala} > 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) } > } > {code} > > Test Leveraging Joda UDT: > > {code:scala} > 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) > } > {code} > The test output shows the invalid date: > {quote} > 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)) > {quote} -- This message was sent by Atlassian Jira (v8.3.4#803005) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org