chia7712 commented on code in PR #15618:
URL: https://github.com/apache/kafka/pull/15618#discussion_r1543505409
##########
core/src/main/scala/kafka/log/UnifiedLog.scala:
##########
@@ -1320,10 +1320,8 @@ class UnifiedLog(@volatile var logStartOffset: Long,
// constant time access while being safe to use with concurrent
collections unlike `toArray`.
val segmentsCopy = logSegments.toBuffer
val latestTimestampSegment = segmentsCopy.maxBy(_.maxTimestampSoFar)
- val latestTimestampAndOffset =
latestTimestampSegment.maxTimestampAndOffsetSoFar
-
- Some(new TimestampAndOffset(latestTimestampAndOffset.timestamp,
- latestTimestampAndOffset.offset,
+ val batch =
latestTimestampSegment.log.batches().asScala.maxBy(_.maxTimestamp())
Review Comment:
> latestTimestampSegment.log.batches() scans the whole log segment and could
introduce unnecessary extra I/O. So, there could be performance degradation
because of that.
The `batches` is a `iterable` object, and its implementation load the batch
only if we call `next`.
https://github.com/apache/kafka/blob/3.6/clients/src/main/java/org/apache/kafka/common/record/FileLogInputStream.java#L63
Hence, the benefit of looking up for a batch (find the position and then use
it to call `batchesFrom`) is that we can save some I/O by skipping some
batches. Please correct me if I misunderstand anything.
> I am not sure I understand this. Looking up for a batch with each
baseOffset or lastOffset will locate the same batch using the offset index,
right?
Is the impl of lookup like this?
```scala
val position =
latestTimestampSegment.offsetIndex.lookup(latestTimestampSegment.offsetOfMaxTimestampSoFar)
latestTimestampSegment.log.batchesFrom(position.position).asScala
```
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