SaintBacchus created SPARK-8367:
-----------------------------------
Summary: ReliableKafka will loss data when
`spark.streaming.blockInterval` was 0
Key: SPARK-8367
URL: https://issues.apache.org/jira/browse/SPARK-8367
Project: Spark
Issue Type: Bug
Components: Streaming
Affects Versions: 1.4.0
Reporter: SaintBacchus
{code:title=BlockGenerator.scala|borderStyle=solid}
/** Change the buffer to which single records are added to. */
private def updateCurrentBuffer(time: Long): Unit = synchronized {
try {
val newBlockBuffer = currentBuffer
currentBuffer = new ArrayBuffer[Any]
if (newBlockBuffer.size > 0) {
val blockId = StreamBlockId(receiverId, time - blockIntervalMs)
val newBlock = new Block(blockId, newBlockBuffer)
listener.onGenerateBlock(blockId)
blocksForPushing.put(newBlock) // put is blocking when queue is full
logDebug("Last element in " + blockId + " is " + newBlockBuffer.last)
}
} catch {
case ie: InterruptedException =>
logInfo("Block updating timer thread was interrupted")
case e: Exception =>
reportError("Error in block updating thread", e)
}
}
{code}
If *spark.streaming.blockInterval* was 0, the *blockId* in the code will always
be the same because of *time* was 0 and *blockIntervalMs* was 0 too.
{code:title=ReliableKafkaReceiver.scala|borderStyle=solid}
private def rememberBlockOffsets(blockId: StreamBlockId): Unit = {
// Get a snapshot of current offset map and store with related block id.
val offsetSnapshot = topicPartitionOffsetMap.toMap
blockOffsetMap.put(blockId, offsetSnapshot)
topicPartitionOffsetMap.clear()
}
{code}
If the *blockId* was the same, Streaming will put current data into previous
*offset*
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