[GitHub] spark pull request #18441: [SPARK-21137][CORE] Spark reads many small files ...

[cloud-fan <gi...@git.apache.org>]

Github user cloud-fan commented on a diff in the pull request:

    https://github.com/apache/spark/pull/18441#discussion_r125212029
  
    --- Diff: core/src/main/scala/org/apache/spark/rdd/BinaryFileRDD.scala ---
    @@ -35,8 +36,12 @@ private[spark] class BinaryFileRDD[T](
       extends NewHadoopRDD[String, T](sc, inputFormatClass, keyClass, valueClass, conf) {
     
       override def getPartitions: Array[Partition] = {
    -    val inputFormat = inputFormatClass.newInstance
         val conf = getConf
    +    // setMinPartitions below will call FileInputFormat.listStatus(), which can be quite slow when
    +    // traversing a large number of directories and files. Parallelize it.
    +    conf.setIfUnset(FileInputFormat.LIST_STATUS_NUM_THREADS,
    +      Runtime.getRuntime.availableProcessors().toString)
    --- End diff --
    
    shall we use `CPU_CORES_PER_EXECUTOR`?


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