WeichenXu123 commented on a change in pull request #25134: [SPARK-28366][CORE]
Logging in driver when loading single large unsplittable file
URL: https://github.com/apache/spark/pull/25134#discussion_r304997919
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File path: core/src/main/scala/org/apache/spark/rdd/HadoopRDD.scala
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@@ -207,6 +210,15 @@ class HadoopRDD[K, V](
} else {
allInputSplits
}
+ if (inputSplits.length == 1 && inputSplits(0).isInstanceOf[FileSplit]) {
+ val fileSplit = inputSplits(0).asInstanceOf[FileSplit]
+ val path = fileSplit.getPath
+ if (Utils.isFileSplittable(path, codecFactory)
Review comment:
@cloud-fan Yes. But we'd better tell user why it only generate only one
partition. So I prefer:
* If the file is unsplittable, then in log tell user the file is
unsplittable (and include unsplittable reason)
* If the file is splittable, then in log tell user we can increase
parallelism by setting the argument `minPartitions` in method `sc.textFile`.
What do you think ?
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