[GitHub] [spark] WeichenXu123 commented on a change in pull request #25134: [SPARK-28366][CORE] Logging in driver when loading single large unsplittable file

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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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