Spark-Hadoop-> org.apache.hadoop.mapred.InvalidInputException: Input path does not exist

Question

I am encountering error while trying to read a file from hdfs into Spark. The file README.md is present in hdfs

 spark@osboxes hadoop]$ hdfs dfs -ls README.md
16/02/26 00:29:14 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
-rw-r--r--   1 spark supergroup       4811 2016-02-25 23:38 README.md

In Spark shell, I gave

scala> val readme = sc.textFile("hdfs://localhost:9000/README.md")
readme: org.apache.spark.rdd.RDD[String] = MapPartitionsRDD[1] at textFile at <console>:27

scala> readme.count
16/02/26 00:25:26 DEBUG BlockManager: Getting local block broadcast_4
16/02/26 00:25:26 DEBUG BlockManager: Level for block broadcast_4 is StorageLevel(true, true, false, true, 1)
16/02/26 00:25:26 DEBUG BlockManager: Getting block broadcast_4 from memory
16/02/26 00:25:26 DEBUG HadoopRDD: Creating new JobConf and caching it for later re-use
16/02/26 00:25:26 DEBUG Client: The ping interval is 60000 ms.
16/02/26 00:25:26 DEBUG Client: Connecting to localhost/127.0.0.1:9000
16/02/26 00:25:26 DEBUG Client: IPC Client (648679508) connection to localhost/127.0.0.1:9000 from spark: starting, having connections 1
16/02/26 00:25:26 DEBUG Client: IPC Client (648679508) connection to localhost/127.0.0.1:9000 from spark sending #4
16/02/26 00:25:26 DEBUG Client: IPC Client (648679508) connection to localhost/127.0.0.1:9000 from spark got value #4
16/02/26 00:25:26 DEBUG ProtobufRpcEngine: Call: getFileInfo took 6ms
org.apache.hadoop.mapred.InvalidInputException: Input path does not exist: hdfs://localhost:9000/README.md
        at org.apache.hadoop.mapred.FileInputFormat.singleThreadedListStatus(FileInputFormat.java:285)
        at org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInputFormat.java:228)
        at org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.java:313)
        at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:199)
        at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239)
        at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237)
        at scala.Option.getOrElse(Option.scala:120)
        at org.apache.spark.rdd.RDD.partitions(RDD.scala:237)
        at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
        at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:239)
        at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:237)
        at scala.Option.getOrElse(Option.scala:120)
        at org.apache.spark.rdd.RDD.partitions(RDD.scala:237)
        at org.apache.spark.SparkContext.runJob(SparkContext.scala:1929)
        at org.apache.spark.rdd.RDD.count(RDD.scala:1143)
        at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:30)
        at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:35)
        at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:37)
        at $iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:39)
        at $iwC$$iwC$$iwC$$iwC.<init>(<console>:41)
        at $iwC$$iwC$$iwC.<init>(<console>:43)
        at $iwC$$iwC.<init>(<console>:45)
        at $iwC.<init>(<console>:47)
        at <init>(<console>:49)
        at .<init>(<console>:53)
        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:1346)
        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:857)
        at org.apache.spark.repl.SparkILoop.interpretStartingWith(SparkILoop.scala:902)
        at org.apache.spark.repl.SparkILoop.command(SparkILoop.scala:814)
        at org.apache.spark.repl.SparkILoop.processLine$1(SparkILoop.scala:657)
        at org.apache.spark.repl.SparkILoop.innerLoop$1(SparkILoop.scala:665)
        at org.apache.spark.repl.SparkILoop.org$apache$spark$repl$SparkILoop$$loop(SparkILoop.scala:670)
        at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply$mcZ$sp(SparkILoop.scala:997)
        at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:945)
        at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:945)
        at scala.tools.nsc.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:135)
        at org.apache.spark.repl.SparkILoop.org$apache$spark$repl$SparkILoop$$process(SparkILoop.scala:945)
        at org.apache.spark.repl.SparkILoop.process(SparkILoop.scala:1059)
        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:731)
        at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:181)
        at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:206)
        at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:121)
        at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)


scala> 16/02/26 00:25:36 DEBUG Client: IPC Client (648679508) connection to localhost/127.0.0.1:9000 from spark: closed
16/02/26 00:25:36 DEBUG Client: IPC Client (648679508) connection to localhost/127.0.0.1:9000 from spark: stopped, remaining connections 0

In core-site.xml, I have below entry:

<configuration>
<property>
    <name>fs.defaultFS</name>
    <value>hdfs://localhost:9000</value>
</property>

and hdfs-site.xml has below detail:

<configuration>
<property>
    <name>dfs.replication</name>
    <value>1</value>
</property>

Am I missing something here ? My OS is CentOS Linux release 7.2.1511 (Core), Hadoop is 2.7.2, and Spark is 1.6.0-bin-hadoop2.6

Answer 1

This happens due to internal mapping between directories. First go to the directory where your file (README.md) is kept. run command : df -k .. You will get the actual mount point of the directory. For example: /xyz Now, try finding your file(README.md) within this mount point. For example: /xyz/home/omi/myDir/README.md Use this path in your code. val readme = sc.textfile("/xyz/home/omi/myDir/README.md");

Answer 2

By default, hdfs dfs -ls will ls your user home folder on hdfs, not the root of hdfs. You can easily verify this by comparing the output of hdfs dfs -ls and hdfs dfs -ls / . When you use the full hdfs URL, you're using an absolute path, and it's not finding your file (because it's located in your user home folder). When you use a relative path, the problem is gone :)

You may want to know that hdfs dfs -put will also use your hdfs home folder as the default destination for the file, not the root of hdfs.