Github user brkyvz commented on a diff in the pull request:
https://github.com/apache/spark/pull/15235#discussion_r80581975
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/ListingFileCatalog.scala
---
@@ -82,73 +85,185 @@ class ListingFileCatalog(
* This is publicly visible for testing.
*/
def listLeafFiles(paths: Seq[Path]): mutable.LinkedHashSet[FileStatus] =
{
- if (paths.length >=
sparkSession.sessionState.conf.parallelPartitionDiscoveryThreshold) {
- HadoopFsRelation.listLeafFilesInParallel(paths, hadoopConf,
sparkSession)
- } else {
- // Right now, the number of paths is less than the value of
- // parallelPartitionDiscoveryThreshold. So, we will list file
statues at the driver.
- // If there is any child that has more files than the threshold, we
will use parallel
- // listing.
-
- // Dummy jobconf to get to the pathFilter defined in configuration
- val jobConf = new JobConf(hadoopConf, this.getClass)
- val pathFilter = FileInputFormat.getInputPathFilter(jobConf)
-
- val statuses: Seq[FileStatus] = paths.flatMap { path =>
- val fs = path.getFileSystem(hadoopConf)
- logTrace(s"Listing $path on driver")
-
- val childStatuses = {
- try {
- val stats = fs.listStatus(path)
- if (pathFilter != null) stats.filter(f =>
pathFilter.accept(f.getPath)) else stats
- } catch {
- case _: FileNotFoundException =>
- logWarning(s"The directory $path was not found. Was it
deleted very recently?")
- Array.empty[FileStatus]
- }
- }
+ val files =
+ if (paths.length >=
sparkSession.sessionState.conf.parallelPartitionDiscoveryThreshold) {
+ ListingFileCatalog.listLeafFilesInParallel(paths, hadoopConf,
sparkSession)
+ } else {
+ ListingFileCatalog.listLeafFilesInSerial(paths, hadoopConf)
+ }
+
+ mutable.LinkedHashSet(files: _*)
+ }
+
+ override def equals(other: Any): Boolean = other match {
+ case hdfs: ListingFileCatalog => paths.toSet == hdfs.paths.toSet
+ case _ => false
+ }
+
+ override def hashCode(): Int = paths.toSet.hashCode()
+}
+
+
+object ListingFileCatalog extends Logging {
+
+ // `FileStatus` is Writable but not serializable. What make it worse,
somehow it doesn't play
+ // well with `SerializableWritable`. So there seems to be no way to
serialize a `FileStatus`.
+ // Here we use `SerializableFileStatus` to extract key components of a
`FileStatus` to serialize
+ // it from executor side and reconstruct it on driver side.
+ private case class SerializableBlockLocation(
+ names: Array[String],
+ hosts: Array[String],
+ offset: Long,
+ length: Long)
+
+ private case class SerializableFileStatus(
+ path: String,
+ length: Long,
+ isDir: Boolean,
+ blockReplication: Short,
+ blockSize: Long,
+ modificationTime: Long,
+ accessTime: Long,
+ blockLocations: Array[SerializableBlockLocation])
+
+ /**
+ * List a collection of path recursively.
+ */
+ private def listLeafFilesInSerial(
+ paths: Seq[Path],
+ hadoopConf: Configuration): Seq[FileStatus] = {
+ // Dummy jobconf to get to the pathFilter defined in configuration
+ val jobConf = new JobConf(hadoopConf, this.getClass)
+ val filter = FileInputFormat.getInputPathFilter(jobConf)
+
+ paths.flatMap { path =>
+ logTrace(s"Listing $path")
+ val fs = path.getFileSystem(hadoopConf)
+
+ // [SPARK-17599] Prevent ListingFileCatalog from failing if path
doesn't exist
+ val status: Option[FileStatus] = try Option(fs.getFileStatus(path))
catch {
+ case _: FileNotFoundException =>
+ logWarning(s"The directory $path was not found. Was it deleted
very recently?")
+ None
+ }
- childStatuses.map {
- case f: LocatedFileStatus => f
-
- // NOTE:
- //
- // - Although S3/S3A/S3N file system can be quite slow for
remote file metadata
- // operations, calling `getFileBlockLocations` does no harm
here since these file system
- // implementations don't actually issue RPC for this method.
- //
- // - Here we are calling `getFileBlockLocations` in a sequential
manner, but it should not
- // be a big deal since we always use to
`listLeafFilesInParallel` when the number of
- // paths exceeds threshold.
- case f =>
- if (f.isDirectory ) {
- // If f is a directory, we do not need to call
getFileBlockLocations (SPARK-14959).
- f
- } else {
- HadoopFsRelation.createLocatedFileStatus(f,
fs.getFileBlockLocations(f, 0, f.getLen))
+ status.map(listLeafFiles0(fs, _, filter)).getOrElse(Seq.empty)
+ }
+ }
+
+ /**
+ * List a collection of path recursively in parallel (using Spark
executors).
+ * Each task launched will use [[listLeafFilesInSerial]] to list.
+ */
+ private def listLeafFilesInParallel(
+ paths: Seq[Path],
+ hadoopConf: Configuration,
+ sparkSession: SparkSession): Seq[FileStatus] = {
+ assert(paths.size >=
sparkSession.sessionState.conf.parallelPartitionDiscoveryThreshold)
+ logInfo(s"Listing leaf files and directories in parallel under:
${paths.mkString(", ")}")
+
+ val sparkContext = sparkSession.sparkContext
+ val serializableConfiguration = new
SerializableConfiguration(hadoopConf)
+ val serializedPaths = paths.map(_.toString)
+
+ // Set the number of parallelism to prevent following file listing
from generating many tasks
+ // in case of large #defaultParallelism.
+ val numParallelism = Math.min(paths.size, 10000)
+
+ val statuses = sparkContext
+ .parallelize(serializedPaths, numParallelism)
+ .mapPartitions { paths =>
+ val hadoopConf = serializableConfiguration.value
+ listLeafFilesInSerial(paths.map(new Path(_)).toSeq,
hadoopConf).iterator
+ }.map { status =>
--- End diff --
why don't you just call map on the iterator but call it on the rdd?
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