HeartSaVioR commented on code in PR #50559:
URL: https://github.com/apache/spark/pull/50559#discussion_r2043090343
##########
sql/core/src/test/scala/org/apache/spark/sql/execution/streaming/state/RocksDBCheckpointFailureInjectionSuite.scala:
##########
@@ -414,6 +414,84 @@ class RocksDBCheckpointFailureInjectionSuite extends
StreamTest
}
}
+ case class FailureConf2(logType: String, checkpointFormatVersion: String) {
+ override def toString: String = {
+ s"logType = $logType, checkpointFormatVersion = $checkpointFormatVersion"
+ }
+ }
+
+ // tests to validate the behavior after failures when writing to the commit
and offset logs
+ Seq(
+ FailureConf2("commits", checkpointFormatVersion = "1"),
+ FailureConf2("commits", checkpointFormatVersion = "2"),
+ FailureConf2("offsets", checkpointFormatVersion = "1"),
+ FailureConf2("offsets", checkpointFormatVersion = "2")).foreach {
failureConf =>
+ test(s"Progress log fails to write $failureConf") {
+ val hadoopConf = new Configuration()
+ hadoopConf.set(STREAMING_CHECKPOINT_FILE_MANAGER_CLASS.parent.key,
fileManagerClassName)
+ val rocksdbChangelogCheckpointingConfKey =
+ RocksDBConf.ROCKSDB_SQL_CONF_NAME_PREFIX +
".changelogCheckpointing.enabled"
+
+ withTempDirAllowFailureInjection { (checkpointDir, injectionState) =>
+ withSQLConf(
+ rocksdbChangelogCheckpointingConfKey -> "true",
+ SQLConf.STATE_STORE_MIN_DELTAS_FOR_SNAPSHOT.key -> "2") {
+ val inputData = MemoryStream[Int]
+ val aggregated =
+ inputData.toDF()
+ .groupBy($"value")
+ .agg(count("*"))
+ .as[(Int, Long)]
+
+ // This should cause the second batch to fail
+ injectionState.createAtomicDelayCloseRegex =
Seq(s".*/${failureConf.logType}/1")
+
+ val additionalConfs = Map(
+ rocksdbChangelogCheckpointingConfKey -> "true",
+ SQLConf.STATE_STORE_CHECKPOINT_FORMAT_VERSION.key ->
+ failureConf.checkpointFormatVersion,
+ STREAMING_CHECKPOINT_FILE_MANAGER_CLASS.parent.key ->
fileManagerClassName)
+
+ testStream(aggregated, Update)(
+ StartStream(
+ checkpointLocation = checkpointDir.getAbsolutePath,
+ additionalConfs = additionalConfs),
+ AddData(inputData, 3),
+ CheckLastBatch((3, 1)),
+ AddData(inputData, 3, 2),
+ // We should categorize this error.
+ // TODO after the error is categorized, we should check error class
+ ExpectFailure[IOException] { _ => () }
+ )
+
+ injectionState.createAtomicDelayCloseRegex = Seq.empty
+
+ inputData.addData(3, 1)
+
+ // The query will restart successfully and start at the checkpoint
after Batch 1
+ testStream(aggregated, Update)(
+ StartStream(
+ checkpointLocation = checkpointDir.getAbsolutePath,
+ additionalConfs = additionalConfs),
+ AddData(inputData, 4),
+ if (failureConf.logType == "commits") {
+ // If the failure is in the commit log, data is already
committed. The batch will
Review Comment:
If that's hard to achieve, I'm OK with more direct code comment about "sink"
status - e.g. (3, 2) and (2, 1) were already emitted to sink as batch 1 even
with failure on commit log. The write against sink for batch 1 should have been
ignored (memory sink), but we restart the query and the state in the sink has
reset, hence the write against sink for batch 1 in new query has effect.
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org
For queries about this service, please contact Infrastructure at:
us...@infra.apache.org
---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org
For additional commands, e-mail: reviews-h...@spark.apache.org
