[SPARK-3954][Streaming] Optimization to FileInputDStream

about convert files to RDDS there are 3 loops with files sequence in spark source.
loops files sequence:
1.files.map(...)
2.files.zip(fileRDDs)
3.files-size.foreach
It's will very time consuming when lots of files.So I do the following correction:
3 loops with files sequence => only one loop

Author: surq <surq@asiainfo.com>

Closes #2811 from surq/SPARK-3954 and squashes the following commits:

321bbe8 [surq]  updated the code style.The style from [for...yield]to [files.map(file=>{})]
88a2c20 [surq] Merge branch 'master' of https://github.com/apache/spark into SPARK-3954
178066f [surq] modify code's style. [Exceeds 100 columns]
626ef97 [surq] remove redundant import(ArrayBuffer)
739341f [surq] promote the speed of convert files to RDDS

1 files changed, 4 insertions, 3 deletions

diff --git a/streaming/src/main/scala/org/apache/spark/streaming/dstream/FileInputDStream.scala b/streaming/src/main/scala/org/apache/spark/streaming/dstream/FileInputDStream.scala
index 8152b7542a..55d6cf6a78 100644
--- a/streaming/src/main/scala/org/apache/spark/streaming/dstream/FileInputDStream.scala
+++ b/streaming/src/main/scala/org/apache/spark/streaming/dstream/FileInputDStream.scala
@@ -120,14 +120,15 @@ class FileInputDStream[K: ClassTag, V: ClassTag, F <: NewInputFormat[K,V] : Clas
 
   /** Generate one RDD from an array of files */
   private def filesToRDD(files: Seq[String]): RDD[(K, V)] = {
-    val fileRDDs = files.map(file => context.sparkContext.newAPIHadoopFile[K, V, F](file))
-    files.zip(fileRDDs).foreach { case (file, rdd) => {
+    val fileRDDs = files.map(file =>{
+      val rdd = context.sparkContext.newAPIHadoopFile[K, V, F](file)
       if (rdd.partitions.size == 0) {
         logError("File " + file + " has no data in it. Spark Streaming can only ingest " +
           "files that have been \"moved\" to the directory assigned to the file stream. " +
           "Refer to the streaming programming guide for more details.")
       }
-    }}
+      rdd
+    })
     new UnionRDD(context.sparkContext, fileRDDs)
   }