MaxNevermind commented on code in PR #44636:
URL: https://github.com/apache/spark/pull/44636#discussion_r1449769428
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sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/FileStreamSource.scala:
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@@ -113,16 +117,32 @@ class FileStreamSource(
// Visible for testing and debugging in production.
val seenFiles = new SeenFilesMap(maxFileAgeMs, fileNameOnly)
- private var allFilesForTriggerAvailableNow: Seq[(SparkPath, Long)] = _
+ private var allFilesForTriggerAvailableNow: Seq[NewFileEntry] = _
metadataLog.restore().foreach { entry =>
seenFiles.add(entry.sparkPath, entry.timestamp)
}
seenFiles.purge()
- logInfo(s"maxFilesPerBatch = $maxFilesPerBatch, maxFileAgeMs =
$maxFileAgeMs")
+ logInfo(s"maxFilesPerBatch = $maxFilesPerBatch, " +
+ s"maxBytesPerBatch = $maxBytesPerBatch, maxFileAgeMs = $maxFileAgeMs")
+
+ private var unreadFiles: Seq[NewFileEntry] = _
- private var unreadFiles: Seq[(SparkPath, Long)] = _
+ /**
+ * Split files into a selected/unselected pair according to a total size
threshold.
+ */
+ private def takeFilesUntilMax(files: Seq[NewFileEntry], maxSize: Long):
+ (Seq[NewFileEntry], Seq[NewFileEntry]) = {
+ var idx = 0
+ var totalSize = 0L
+ val (bFiles, usFiles) = files.span { case NewFileEntry(_, size, _) =>
+ idx += 1
+ totalSize += size
+ idx == 1 || totalSize <= maxSize
Review Comment:
I used Math.addExact to deal with overflow here in another place. Let's me
know if that approach is acceptable. I also found Spark's MathUtils. Not 100%
certain which way is the better.
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