linehrr edited a comment on issue #23324: [SPARK-26267][SS]Retry when detecting incorrect offsets from Kafka URL: https://github.com/apache/spark/pull/23324#issuecomment-452172192 @zsxwing not too sure if this is actually a bug related to this fix, but I can share my stacktrace here: ``` 19/01/07 22:56:15 ERROR streaming.MicroBatchExecution: Query [id = c46c67ee-3514-4788-8370-a696837b21b1, runId = bb52783e-33d6-460b-9aa2-cc5da414531e] terminated with error org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 8.0 failed 4 times, most recent failure: Lost task 0.3 in stage 8.0 (TID 164, qa2-hdp-3.acuityads.org, executor 2): java.lang.AssertionError: assertion f ailed: latest offset -9223372036854775808 does not equal -1 at scala.Predef$.assert(Predef.scala:170) at org.apache.spark.sql.kafka010.KafkaMicroBatchInputPartitionReader.resolveRange(KafkaMicroBatchReader.scala:371) at org.apache.spark.sql.kafka010.KafkaMicroBatchInputPartitionReader.<init>(KafkaMicroBatchReader.scala:329) at org.apache.spark.sql.kafka010.KafkaMicroBatchInputPartition.createPartitionReader(KafkaMicroBatchReader.scala:314) at org.apache.spark.sql.execution.datasources.v2.DataSourceRDD.compute(DataSourceRDD.scala:42) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324) at org.apache.spark.rdd.RDD.iterator(RDD.scala:288) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324) at org.apache.spark.rdd.RDD.iterator(RDD.scala:288) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324) at org.apache.spark.rdd.RDD.iterator(RDD.scala:288) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324) at org.apache.spark.rdd.RDD.iterator(RDD.scala:288) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:55) at org.apache.spark.scheduler.Task.run(Task.scala:121) at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:402) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:408) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) at java.lang.Thread.run(Thread.java:745) ``` for some reason, looks like fetchLatestOffset returned a Long.MIN_VALUE for one of the partitions. I checked the structured streaming checkpoint, that was correct, it's the currentAvailableOffset was set to Long.MIN_VALUE. kafka broker version: 1.1.0. lib we used: ```// https://mvnrepository.com/artifact/org.apache.spark/spark-sql-kafka-0-10 libraryDependencies += "org.apache.spark" %% "spark-sql-kafka-0-10" % "2.4.0" ``` how to reproduce: basically we started a structured streamer and subscribed a topic of 4 partitions. then produced some messages into topic, job crashed and logged the stacktrace like above.
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