How to map filenames to RDD using sc.textFile(

Question

Please note, I must use the sc.textFile, but I would accept any other answers.

What I want to do is to simply add the filename that is being processed to RDD.... some thing like:

var rdd = sc.textFile("s3n://bucket/*.csv").map(line=>filename+","+line)

Much appreciated!

EDIT2: SOLUTION TO EDIT1 is to use Hadoop 2.4 or above. However, I have not tested it by using the slaves... etc. However, some of the mentioned solutions work only for the small data-sets. If you want to use the big-data, you will have to use the HadoopRDD

EDIT: I have tried the following, and it did not work:

:cp symjar/aws-java-sdk-1.9.29.jar
:cp symjar/aws-java-sdk-flow-build-tools-1.9.29.jar

import com.amazonaws.services.s3.AmazonS3Client
import com.amazonaws.services.s3.model.{S3ObjectSummary, ObjectListing, GetObjectRequest}
import com.amazonaws.auth._


def awsAccessKeyId = "AKEY"
def awsSecretAccessKey = "SKEY"

val hadoopConf = sc.hadoopConfiguration;
hadoopConf.set("fs.s3n.impl", "org.apache.hadoop.fs.s3native.NativeS3FileSystem")
hadoopConf.set("fs.s3n.awsAccessKeyId", awsAccessKeyId)
hadoopConf.set("fs.s3n.awsSecretAccessKey", awsSecretAccessKey)

var rdd = sc.wholeTextFiles("s3n://bucket/dir/*.csv").map { case (filename, content) =>  filename }
rdd.count

NOTE: It is connecting to S3, and that is not an issue (as I have tested it many many times).

The error I get is:

INFO input.FileInputFormat: Total input paths to process : 4
java.io.FileNotFoundException: File does not exist: /RTLM-918/simple/t1-100.csv
    at org.apache.hadoop.hdfs.DistributedFileSystem.getFileStatus(DistributedFileSystem.java:517)
    at org.apache.hadoop.mapreduce.lib.input.CombineFileInputFormat$OneFileInfo.<init>(CombineFileInputFormat.java:489)
    at org.apache.hadoop.mapreduce.lib.input.CombineFileInputFormat.getMoreSplits(CombineFileInputFormat.java:280)
    at org.apache.hadoop.mapreduce.lib.input.CombineFileInputFormat.getSplits(CombineFileInputFormat.java:240)
    at org.apache.spark.rdd.WholeTextFileRDD.getPartitions(NewHadoopRDD.scala:267)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:219)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:217)
    at scala.Option.getOrElse(Option.scala:120)
    at org.apache.spark.rdd.RDD.partitions(RDD.scala:217)
    at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:32)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:219)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:217)
    at scala.Option.getOrElse(Option.scala:120)
    at org.apache.spark.rdd.RDD.partitions(RDD.scala:217)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:1511)
    at org.apache.spark.rdd.RDD.collect(RDD.scala:813)
    at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:29)
    at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:34)
    at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:36)
    at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:38)
    at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:40)
    at $iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:42)
    at $iwC$$iwC$$iwC$$iwC.<init>(<console>:44)
    at $iwC$$iwC$$iwC.<init>(<console>:46)
    at $iwC$$iwC.<init>(<console>:48)
    at $iwC.<init>(<console>:50)
    at <init>(<console>:52)
    at .<init>(<console>:56)
    at .<clinit>(<console>)
    at .<init>(<console>:7)
    at .<clinit>(<console>)
    at $print(<console>)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:606)
    at org.apache.spark.repl.SparkIMain$ReadEvalPrint.call(SparkIMain.scala:1065)
    at org.apache.spark.repl.SparkIMain$Request.loadAndRun(SparkIMain.scala:1338)
    at org.apache.spark.repl.SparkIMain.loadAndRunReq$1(SparkIMain.scala:840)
    at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:871)
    at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:819)
    at org.apache.spark.repl.SparkILoop.reallyInterpret$1(SparkILoop.scala:856)
    at org.apache.spark.repl.SparkILoop.interpretStartingWith(SparkILoop.scala:901)
    at org.apache.spark.repl.SparkILoop.command(SparkILoop.scala:813)
    at org.apache.spark.repl.SparkILoop.processLine$1(SparkILoop.scala:656)
    at org.apache.spark.repl.SparkILoop.innerLoop$1(SparkILoop.scala:664)
    at org.apache.spark.repl.SparkILoop.org$apache$spark$repl$SparkILoop$$loop(SparkILoop.scala:669)
    at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply$mcZ$sp(SparkILoop.scala:996)
    at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:944)
    at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:944)
    at scala.tools.nsc.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:135)
    at org.apache.spark.repl.SparkILoop.org$apache$spark$repl$SparkILoop$$process(SparkILoop.scala:944)
    at org.apache.spark.repl.SparkILoop.process(SparkILoop.scala:1058)
    at org.apache.spark.repl.Main$.main(Main.scala:31)
    at org.apache.spark.repl.Main.main(Main.scala)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:606)
    at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:569)
    at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:166)
    at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:189)
    at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:110)
    at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)

Answer 1

Just pass it in as a variable during the map (or set as an object property).

sc.textFile("s3n://bucket/"+fn+".csv").map(line=>set_filepath(line,fn))

Answer 2

If you are dealing with big-data HadoopRDD is then the answer. Otherwise, with other suggestions, it won't work.

Code:

val text = sc.hadoopFile("s3n://.../", classOf[TextInputFormat], classOf[LongWritable], classOf[Text])
// Cast to a HadoopRDD
val hadoopRdd = text.asInstanceOf[HadoopRDD[LongWritable, Text]]

val fileAndLine = hadoopRdd.mapPartitionsWithInputSplit { (inputSplit, iterator) ⇒
  val file = inputSplit.asInstanceOf[FileSplit]
  iterator.map { tpl ⇒ (file.getPath, tpl._2) }
}

Answer 3

The only text method that includes the file name is wholeTextFiles.

sc.wholeTextFiles(path).map { case (filename, content) => ... }