org.scalatest.exceptions.TestFailedException: Timed out waiting for stream: The code passed to failAfter did not complete within 30 seconds. java.lang.Thread.getStackTrace(Thread.java:1559) org.scalatest.concurrent.TimeLimits$class.failAfterImpl(TimeLimits.scala:234) org.apache.spark.sql.kafka010.KafkaSourceTest.failAfterImpl(KafkaMicroBatchSourceSuite.scala:49) org.scalatest.concurrent.TimeLimits$class.failAfter(TimeLimits.scala:230) org.apache.spark.sql.kafka010.KafkaSourceTest.failAfter(KafkaMicroBatchSourceSuite.scala:49) org.apache.spark.sql.streaming.StreamTest$$anonfun$fetchStreamAnswer$1$5.apply(StreamTest.scala:469) org.apache.spark.sql.streaming.StreamTest$$anonfun$fetchStreamAnswer$1$5.apply(StreamTest.scala:468) scala.collection.mutable.HashMap$$anonfun$foreach$1.apply(HashMap.scala:130) scala.collection.mutable.HashMap$$anonfun$foreach$1.apply(HashMap.scala:130) scala.collection.mutable.HashTable$class.foreachEntry(HashTable.scala:236) Caused by: null java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.reportInterruptAfterWait(AbstractQueuedSynchronizer.java:2014) java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2173) org.apache.spark.sql.execution.streaming.StreamExecution.processAllAvailable(StreamExecution.scala:451) org.apache.spark.sql.streaming.StreamTest$$anonfun$fetchStreamAnswer$1$5$$anonfun$apply$3.apply$mcV$sp(StreamTest.scala:473) org.apache.spark.sql.streaming.StreamTest$$anonfun$fetchStreamAnswer$1$5$$anonfun$apply$3.apply(StreamTest.scala:469) org.apache.spark.sql.streaming.StreamTest$$anonfun$fetchStreamAnswer$1$5$$anonfun$apply$3.apply(StreamTest.scala:469) org.scalatest.enablers.Timed$$anon$1.timeoutAfter(Timed.scala:127) org.scalatest.concurrent.TimeLimits$class.failAfterImpl(TimeLimits.scala:235) org.apache.spark.sql.kafka010.KafkaSourceTest.failAfterImpl(KafkaMicroBatchSourceSuite.scala:49) org.scalatest.concurrent.TimeLimits$class.failAfter(TimeLimits.scala:230) == Progress == AssertOnQuery(<condition>, ) AddKafkaData(topics = Set(topic-10), data = WrappedArray(1, 2, 3), message = ) CheckAnswer: [2],[3],[4] StopStream StartStream(ContinuousTrigger(1000),org.apache.spark.util.SystemClock@1b3d3cb8,Map(),null) CheckAnswer: [2],[3],[4] StopStream AddKafkaData(topics = Set(topic-10), data = WrappedArray(4, 5, 6), message = ) StartStream(ContinuousTrigger(1000),org.apache.spark.util.SystemClock@a18dba0,Map(),null) => CheckAnswer: [2],[3],[4],[5],[6],[7] AddKafkaData(topics = Set(topic-10), data = WrappedArray(7, 8), message = ) CheckAnswer: [2],[3],[4],[5],[6],[7],[8],[9] AssertOnQuery(<condition>, Add partitions) AddKafkaData(topics = Set(topic-10), data = WrappedArray(9, 10, 11, 12, 13, 14, 15, 16), message = ) CheckAnswer: [2],[3],[4],[5],[6],[7],[8],[9],[10],[11],[12],[13],[14],[15],[16],[17] == Stream == Output Mode: Append Stream state: {KafkaSource[Assign[topic-10-4, topic-10-3, topic-10-2, topic-10-1, topic-10-0]]: {"topic-10":{"2":1,"4":1,"1":2,"3":1,"0":2}}} Thread state: alive Thread stack trace: sun.misc.Unsafe.park(Native Method) java.util.concurrent.locks.LockSupport.park(LockSupport.java:175) java.util.concurrent.locks.AbstractQueuedSynchronizer.parkAndCheckInterrupt(AbstractQueuedSynchronizer.java:836) java.util.concurrent.locks.AbstractQueuedSynchronizer.doAcquireSharedInterruptibly(AbstractQueuedSynchronizer.java:997) java.util.concurrent.locks.AbstractQueuedSynchronizer.acquireSharedInterruptibly(AbstractQueuedSynchronizer.java:1304) scala.concurrent.impl.Promise$DefaultPromise.tryAwait(Promise.scala:206) scala.concurrent.impl.Promise$DefaultPromise.ready(Promise.scala:222) scala.concurrent.impl.Promise$DefaultPromise.ready(Promise.scala:157) org.apache.spark.util.ThreadUtils$.awaitReady(ThreadUtils.scala:243) org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:728) org.apache.spark.SparkContext.runJob(SparkContext.scala:2061) org.apache.spark.SparkContext.runJob(SparkContext.scala:2082) org.apache.spark.SparkContext.runJob(SparkContext.scala:2101) org.apache.spark.SparkContext.runJob(SparkContext.scala:2126) org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:939) org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112) org.apache.spark.rdd.RDD.withScope(RDD.scala:363) org.apache.spark.rdd.RDD.collect(RDD.scala:938) org.apache.spark.sql.execution.streaming.continuous.WriteToContinuousDataSourceExec.doExecute(WriteToContinuousDataSourceExec.scala:53) org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131) org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127) org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155) org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152) org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127) org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:80) org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:80) org.apache.spark.sql.execution.streaming.continuous.ContinuousExecution$$anonfun$runContinuous$3$$anonfun$apply$1.apply(ContinuousExecution.scala:263) org.apache.spark.sql.execution.streaming.continuous.ContinuousExecution$$anonfun$runContinuous$3$$anonfun$apply$1.apply(ContinuousExecution.scala:263) org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:78) org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:125) org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:73) org.apache.spark.sql.execution.streaming.continuous.ContinuousExecution$$anonfun$runContinuous$3.apply(ContinuousExecution.scala:263) org.apache.spark.sql.execution.streaming.continuous.ContinuousExecution$$anonfun$runContinuous$3.apply(ContinuousExecution.scala:263) org.apache.spark.sql.execution.streaming.ProgressReporter$class.reportTimeTaken(ProgressReporter.scala:401) org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:58) org.apache.spark.sql.execution.streaming.continuous.ContinuousExecution.runContinuous(ContinuousExecution.scala:261) org.apache.spark.sql.execution.streaming.continuous.ContinuousExecution.runActivatedStream(ContinuousExecution.scala:90) org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runStream(StreamExecution.scala:279) org.apache.spark.sql.execution.streaming.StreamExecution$$anon$1.run(StreamExecution.scala:189) == Sink == 0: 1: [2] [3] [4] 2: 3: 4: 5: [7] [6] [5] == Plan == == Parsed Logical Plan == WriteToContinuousDataSource org.apache.spark.sql.execution.streaming.sources.MemoryStreamingWriteSupport@e5b0238 +- SerializeFromObject [input[0, int, false] AS value#12698] +- MapElements <function1>, class scala.Tuple2, [StructField(_1,StringType,true), StructField(_2,StringType,true)], obj#12697: int +- DeserializeToObject newInstance(class scala.Tuple2), obj#12696: scala.Tuple2 +- Project [cast(key#12825 as string) AS key#12688, cast(value#12826 as string) AS value#12689] +- Streaming RelationV2 kafka[key#12825, value#12826, topic#12827, partition#12828, offset#12829L, timestamp#12830, timestampType#12831] (Options: [kafka.metadata.max.age.ms=1,assign={"topic-10":[4,3,2,1,0]},failOnDataLoss=false,kafka.bootstrap...) == Analyzed Logical Plan == WriteToContinuousDataSource org.apache.spark.sql.execution.streaming.sources.MemoryStreamingWriteSupport@e5b0238 +- SerializeFromObject [input[0, int, false] AS value#12698] +- MapElements <function1>, class scala.Tuple2, [StructField(_1,StringType,true), StructField(_2,StringType,true)], obj#12697: int +- DeserializeToObject newInstance(class scala.Tuple2), obj#12696: scala.Tuple2 +- Project [cast(key#12825 as string) AS key#12688, cast(value#12826 as string) AS value#12689] +- Streaming RelationV2 kafka[key#12825, value#12826, topic#12827, partition#12828, offset#12829L, timestamp#12830, timestampType#12831] (Options: [kafka.metadata.max.age.ms=1,assign={"topic-10":[4,3,2,1,0]},failOnDataLoss=false,kafka.bootstrap...) == Optimized Logical Plan == WriteToContinuousDataSource org.apache.spark.sql.execution.streaming.sources.MemoryStreamingWriteSupport@e5b0238 +- SerializeFromObject [input[0, int, false] AS value#12698] +- MapElements <function1>, class scala.Tuple2, [StructField(_1,StringType,true), StructField(_2,StringType,true)], obj#12697: int +- DeserializeToObject newInstance(class scala.Tuple2), obj#12696: scala.Tuple2 +- Project [cast(key#12825 as string) AS key#12688, cast(value#12826 as string) AS value#12689] +- Streaming RelationV2 kafka[key#12825, value#12826, topic#12827, partition#12828, offset#12829L, timestamp#12830, timestampType#12831] (Options: [kafka.metadata.max.age.ms=1,assign={"topic-10":[4,3,2,1,0]},failOnDataLoss=false,kafka.bootstrap...) == Physical Plan == WriteToContinuousDataSource org.apache.spark.sql.execution.streaming.sources.MemoryStreamingWriteSupport@e5b0238 +- *(1) SerializeFromObject [input[0, int, false] AS value#12698] +- *(1) MapElements <function1>, obj#12697: int +- *(1) DeserializeToObject newInstance(class scala.Tuple2), obj#12696: scala.Tuple2 +- *(1) Project [cast(key#12825 as string) AS key#12688, cast(value#12826 as string) AS value#12689] +- *(1) Project [key#12825, value#12826, topic#12827, partition#12828, offset#12829L, timestamp#12830, timestampType#12831] +- *(1) ScanV2 kafka[key#12825, value#12826, topic#12827, partition#12828, offset#12829L, timestamp#12830, timestampType#12831] (Options: [kafka.metadata.max.age.ms=1,assign={"topic-10":[4,3,2,1,0]},failOnDataLoss=false,kafka.bootstrap...)
sbt.ForkMain$ForkError: org.scalatest.exceptions.TestFailedException:
Timed out waiting for stream: The code passed to failAfter did not complete within 30 seconds.
java.lang.Thread.getStackTrace(Thread.java:1559)
org.scalatest.concurrent.TimeLimits$class.failAfterImpl(TimeLimits.scala:234)
org.apache.spark.sql.kafka010.KafkaSourceTest.failAfterImpl(KafkaMicroBatchSourceSuite.scala:49)
org.scalatest.concurrent.TimeLimits$class.failAfter(TimeLimits.scala:230)
org.apache.spark.sql.kafka010.KafkaSourceTest.failAfter(KafkaMicroBatchSourceSuite.scala:49)
org.apache.spark.sql.streaming.StreamTest$$anonfun$fetchStreamAnswer$1$5.apply(StreamTest.scala:469)
org.apache.spark.sql.streaming.StreamTest$$anonfun$fetchStreamAnswer$1$5.apply(StreamTest.scala:468)
scala.collection.mutable.HashMap$$anonfun$foreach$1.apply(HashMap.scala:130)
scala.collection.mutable.HashMap$$anonfun$foreach$1.apply(HashMap.scala:130)
scala.collection.mutable.HashTable$class.foreachEntry(HashTable.scala:236)
Caused by: null
java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.reportInterruptAfterWait(AbstractQueuedSynchronizer.java:2014)
java.util.concurrent.locks.AbstractQueuedSynchronizer$ConditionObject.await(AbstractQueuedSynchronizer.java:2173)
org.apache.spark.sql.execution.streaming.StreamExecution.processAllAvailable(StreamExecution.scala:451)
org.apache.spark.sql.streaming.StreamTest$$anonfun$fetchStreamAnswer$1$5$$anonfun$apply$3.apply$mcV$sp(StreamTest.scala:473)
org.apache.spark.sql.streaming.StreamTest$$anonfun$fetchStreamAnswer$1$5$$anonfun$apply$3.apply(StreamTest.scala:469)
org.apache.spark.sql.streaming.StreamTest$$anonfun$fetchStreamAnswer$1$5$$anonfun$apply$3.apply(StreamTest.scala:469)
org.scalatest.enablers.Timed$$anon$1.timeoutAfter(Timed.scala:127)
org.scalatest.concurrent.TimeLimits$class.failAfterImpl(TimeLimits.scala:235)
org.apache.spark.sql.kafka010.KafkaSourceTest.failAfterImpl(KafkaMicroBatchSourceSuite.scala:49)
org.scalatest.concurrent.TimeLimits$class.failAfter(TimeLimits.scala:230)
== Progress ==
AssertOnQuery(<condition>, )
AddKafkaData(topics = Set(topic-10), data = WrappedArray(1, 2, 3), message = )
CheckAnswer: [2],[3],[4]
StopStream
StartStream(ContinuousTrigger(1000),org.apache.spark.util.SystemClock@1b3d3cb8,Map(),null)
CheckAnswer: [2],[3],[4]
StopStream
AddKafkaData(topics = Set(topic-10), data = WrappedArray(4, 5, 6), message = )
StartStream(ContinuousTrigger(1000),org.apache.spark.util.SystemClock@a18dba0,Map(),null)
=> CheckAnswer: [2],[3],[4],[5],[6],[7]
AddKafkaData(topics = Set(topic-10), data = WrappedArray(7, 8), message = )
CheckAnswer: [2],[3],[4],[5],[6],[7],[8],[9]
AssertOnQuery(<condition>, Add partitions)
AddKafkaData(topics = Set(topic-10), data = WrappedArray(9, 10, 11, 12, 13, 14, 15, 16), message = )
CheckAnswer: [2],[3],[4],[5],[6],[7],[8],[9],[10],[11],[12],[13],[14],[15],[16],[17]
== Stream ==
Output Mode: Append
Stream state: {KafkaSource[Assign[topic-10-4, topic-10-3, topic-10-2, topic-10-1, topic-10-0]]: {"topic-10":{"2":1,"4":1,"1":2,"3":1,"0":2}}}
Thread state: alive
Thread stack trace: sun.misc.Unsafe.park(Native Method)
java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
java.util.concurrent.locks.AbstractQueuedSynchronizer.parkAndCheckInterrupt(AbstractQueuedSynchronizer.java:836)
java.util.concurrent.locks.AbstractQueuedSynchronizer.doAcquireSharedInterruptibly(AbstractQueuedSynchronizer.java:997)
java.util.concurrent.locks.AbstractQueuedSynchronizer.acquireSharedInterruptibly(AbstractQueuedSynchronizer.java:1304)
scala.concurrent.impl.Promise$DefaultPromise.tryAwait(Promise.scala:206)
scala.concurrent.impl.Promise$DefaultPromise.ready(Promise.scala:222)
scala.concurrent.impl.Promise$DefaultPromise.ready(Promise.scala:157)
org.apache.spark.util.ThreadUtils$.awaitReady(ThreadUtils.scala:243)
org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:728)
org.apache.spark.SparkContext.runJob(SparkContext.scala:2061)
org.apache.spark.SparkContext.runJob(SparkContext.scala:2082)
org.apache.spark.SparkContext.runJob(SparkContext.scala:2101)
org.apache.spark.SparkContext.runJob(SparkContext.scala:2126)
org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:939)
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
org.apache.spark.rdd.RDD.withScope(RDD.scala:363)
org.apache.spark.rdd.RDD.collect(RDD.scala:938)
org.apache.spark.sql.execution.streaming.continuous.WriteToContinuousDataSourceExec.doExecute(WriteToContinuousDataSourceExec.scala:53)
org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:80)
org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:80)
org.apache.spark.sql.execution.streaming.continuous.ContinuousExecution$$anonfun$runContinuous$3$$anonfun$apply$1.apply(ContinuousExecution.scala:263)
org.apache.spark.sql.execution.streaming.continuous.ContinuousExecution$$anonfun$runContinuous$3$$anonfun$apply$1.apply(ContinuousExecution.scala:263)
org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:78)
org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:125)
org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:73)
org.apache.spark.sql.execution.streaming.continuous.ContinuousExecution$$anonfun$runContinuous$3.apply(ContinuousExecution.scala:263)
org.apache.spark.sql.execution.streaming.continuous.ContinuousExecution$$anonfun$runContinuous$3.apply(ContinuousExecution.scala:263)
org.apache.spark.sql.execution.streaming.ProgressReporter$class.reportTimeTaken(ProgressReporter.scala:401)
org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:58)
org.apache.spark.sql.execution.streaming.continuous.ContinuousExecution.runContinuous(ContinuousExecution.scala:261)
org.apache.spark.sql.execution.streaming.continuous.ContinuousExecution.runActivatedStream(ContinuousExecution.scala:90)
org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runStream(StreamExecution.scala:279)
org.apache.spark.sql.execution.streaming.StreamExecution$$anon$1.run(StreamExecution.scala:189)
== Sink ==
0:
1: [2] [3] [4]
2:
3:
4:
5: [7] [6] [5]
== Plan ==
== Parsed Logical Plan ==
WriteToContinuousDataSource org.apache.spark.sql.execution.streaming.sources.MemoryStreamingWriteSupport@e5b0238
+- SerializeFromObject [input[0, int, false] AS value#12698]
+- MapElements <function1>, class scala.Tuple2, [StructField(_1,StringType,true), StructField(_2,StringType,true)], obj#12697: int
+- DeserializeToObject newInstance(class scala.Tuple2), obj#12696: scala.Tuple2
+- Project [cast(key#12825 as string) AS key#12688, cast(value#12826 as string) AS value#12689]
+- Streaming RelationV2 kafka[key#12825, value#12826, topic#12827, partition#12828, offset#12829L, timestamp#12830, timestampType#12831] (Options: [kafka.metadata.max.age.ms=1,assign={"topic-10":[4,3,2,1,0]},failOnDataLoss=false,kafka.bootstrap...)
== Analyzed Logical Plan ==
WriteToContinuousDataSource org.apache.spark.sql.execution.streaming.sources.MemoryStreamingWriteSupport@e5b0238
+- SerializeFromObject [input[0, int, false] AS value#12698]
+- MapElements <function1>, class scala.Tuple2, [StructField(_1,StringType,true), StructField(_2,StringType,true)], obj#12697: int
+- DeserializeToObject newInstance(class scala.Tuple2), obj#12696: scala.Tuple2
+- Project [cast(key#12825 as string) AS key#12688, cast(value#12826 as string) AS value#12689]
+- Streaming RelationV2 kafka[key#12825, value#12826, topic#12827, partition#12828, offset#12829L, timestamp#12830, timestampType#12831] (Options: [kafka.metadata.max.age.ms=1,assign={"topic-10":[4,3,2,1,0]},failOnDataLoss=false,kafka.bootstrap...)
== Optimized Logical Plan ==
WriteToContinuousDataSource org.apache.spark.sql.execution.streaming.sources.MemoryStreamingWriteSupport@e5b0238
+- SerializeFromObject [input[0, int, false] AS value#12698]
+- MapElements <function1>, class scala.Tuple2, [StructField(_1,StringType,true), StructField(_2,StringType,true)], obj#12697: int
+- DeserializeToObject newInstance(class scala.Tuple2), obj#12696: scala.Tuple2
+- Project [cast(key#12825 as string) AS key#12688, cast(value#12826 as string) AS value#12689]
+- Streaming RelationV2 kafka[key#12825, value#12826, topic#12827, partition#12828, offset#12829L, timestamp#12830, timestampType#12831] (Options: [kafka.metadata.max.age.ms=1,assign={"topic-10":[4,3,2,1,0]},failOnDataLoss=false,kafka.bootstrap...)
== Physical Plan ==
WriteToContinuousDataSource org.apache.spark.sql.execution.streaming.sources.MemoryStreamingWriteSupport@e5b0238
+- *(1) SerializeFromObject [input[0, int, false] AS value#12698]
+- *(1) MapElements <function1>, obj#12697: int
+- *(1) DeserializeToObject newInstance(class scala.Tuple2), obj#12696: scala.Tuple2
+- *(1) Project [cast(key#12825 as string) AS key#12688, cast(value#12826 as string) AS value#12689]
+- *(1) Project [key#12825, value#12826, topic#12827, partition#12828, offset#12829L, timestamp#12830, timestampType#12831]
+- *(1) ScanV2 kafka[key#12825, value#12826, topic#12827, partition#12828, offset#12829L, timestamp#12830, timestampType#12831] (Options: [kafka.metadata.max.age.ms=1,assign={"topic-10":[4,3,2,1,0]},failOnDataLoss=false,kafka.bootstrap...)
at org.scalatest.Assertions$class.newAssertionFailedException(Assertions.scala:528)
at org.scalatest.FunSuite.newAssertionFailedException(FunSuite.scala:1560)
at org.scalatest.Assertions$class.fail(Assertions.scala:1089)
at org.scalatest.FunSuite.fail(FunSuite.scala:1560)
at org.apache.spark.sql.streaming.StreamTest$class.failTest$1(StreamTest.scala:450)
at org.apache.spark.sql.streaming.StreamTest$class.liftedTree1$1(StreamTest.scala:780)
at org.apache.spark.sql.streaming.StreamTest$class.testStream(StreamTest.scala:756)
at org.apache.spark.sql.kafka010.KafkaSourceTest.testStream(KafkaMicroBatchSourceSuite.scala:49)
at org.apache.spark.sql.kafka010.KafkaSourceSuiteBase.org$apache$spark$sql$kafka010$KafkaSourceSuiteBase$$testFromLatestOffsets(KafkaMicroBatchSourceSuite.scala:1297)
at org.apache.spark.sql.kafka010.KafkaSourceSuiteBase$$anonfun$45$$anonfun$apply$12.apply$mcV$sp(KafkaMicroBatchSourceSuite.scala:1022)
at org.apache.spark.sql.kafka010.KafkaSourceSuiteBase$$anonfun$45$$anonfun$apply$12.apply(KafkaMicroBatchSourceSuite.scala:1020)
at org.apache.spark.sql.kafka010.KafkaSourceSuiteBase$$anonfun$45$$anonfun$apply$12.apply(KafkaMicroBatchSourceSuite.scala:1020)
at org.scalatest.OutcomeOf$class.outcomeOf(OutcomeOf.scala:85)
at org.scalatest.OutcomeOf$.outcomeOf(OutcomeOf.scala:104)
at org.scalatest.Transformer.apply(Transformer.scala:22)
at org.scalatest.Transformer.apply(Transformer.scala:20)
at org.scalatest.FunSuiteLike$$anon$1.apply(FunSuiteLike.scala:186)
at org.apache.spark.SparkFunSuite.withFixture(SparkFunSuite.scala:103)
at org.scalatest.FunSuiteLike$class.invokeWithFixture$1(FunSuiteLike.scala:183)
at org.scalatest.FunSuiteLike$$anonfun$runTest$1.apply(FunSuiteLike.scala:196)
at org.scalatest.FunSuiteLike$$anonfun$runTest$1.apply(FunSuiteLike.scala:196)
at org.scalatest.SuperEngine.runTestImpl(Engine.scala:289)
at org.scalatest.FunSuiteLike$class.runTest(FunSuiteLike.scala:196)
at org.apache.spark.sql.kafka010.KafkaSourceTest.org$scalatest$BeforeAndAfterEach$$super$runTest(KafkaMicroBatchSourceSuite.scala:49)
at org.scalatest.BeforeAndAfterEach$class.runTest(BeforeAndAfterEach.scala:221)
at org.apache.spark.sql.kafka010.KafkaSourceTest.runTest(KafkaMicroBatchSourceSuite.scala:49)
at org.scalatest.FunSuiteLike$$anonfun$runTests$1.apply(FunSuiteLike.scala:229)
at org.scalatest.FunSuiteLike$$anonfun$runTests$1.apply(FunSuiteLike.scala:229)
at org.scalatest.SuperEngine$$anonfun$traverseSubNodes$1$1.apply(Engine.scala:396)
at org.scalatest.SuperEngine$$anonfun$traverseSubNodes$1$1.apply(Engine.scala:384)
at scala.collection.immutable.List.foreach(List.scala:392)
at org.scalatest.SuperEngine.traverseSubNodes$1(Engine.scala:384)
at org.scalatest.SuperEngine.org$scalatest$SuperEngine$$runTestsInBranch(Engine.scala:379)
at org.scalatest.SuperEngine.runTestsImpl(Engine.scala:461)
at org.scalatest.FunSuiteLike$class.runTests(FunSuiteLike.scala:229)
at org.scalatest.FunSuite.runTests(FunSuite.scala:1560)
at org.scalatest.Suite$class.run(Suite.scala:1147)
at org.scalatest.FunSuite.org$scalatest$FunSuiteLike$$super$run(FunSuite.scala:1560)
at org.scalatest.FunSuiteLike$$anonfun$run$1.apply(FunSuiteLike.scala:233)
at org.scalatest.FunSuiteLike$$anonfun$run$1.apply(FunSuiteLike.scala:233)
at org.scalatest.SuperEngine.runImpl(Engine.scala:521)
at org.scalatest.FunSuiteLike$class.run(FunSuiteLike.scala:233)
at org.apache.spark.SparkFunSuite.org$scalatest$BeforeAndAfterAll$$super$run(SparkFunSuite.scala:52)
at org.scalatest.BeforeAndAfterAll$class.liftedTree1$1(BeforeAndAfterAll.scala:213)
at org.scalatest.BeforeAndAfterAll$class.run(BeforeAndAfterAll.scala:210)
at org.apache.spark.SparkFunSuite.run(SparkFunSuite.scala:52)
at org.scalatest.tools.Framework.org$scalatest$tools$Framework$$runSuite(Framework.scala:314)
at org.scalatest.tools.Framework$ScalaTestTask.execute(Framework.scala:480)
at sbt.ForkMain$Run$2.call(ForkMain.java:296)
at sbt.ForkMain$Run$2.call(ForkMain.java:286)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)