Failed to use Spark shell

Question

I'm new to Spark and I tried using Spark shell (both Python and Scala versions), but I get an exception when I try a simple example. Here's the input:

text = sc.textFile("README.md")
text.count() #fails

Here's the exception:

java.net.ConnectException: Call From marko/127.0.1.1 to localhost:8020 failed on connection exception: java.net.ConnectException: Connection refused; For more details see:  http://wiki.apache.org/hadoop/ConnectionRefused
    at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
    at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
    at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
    at java.lang.reflect.Constructor.newInstance(Constructor.java:408)
    at org.apache.hadoop.net.NetUtils.wrapWithMessage(NetUtils.java:792)
    at org.apache.hadoop.net.NetUtils.wrapException(NetUtils.java:732)
    at org.apache.hadoop.ipc.Client.call(Client.java:1479)
    at org.apache.hadoop.ipc.Client.call(Client.java:1412)
    at org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:229)
    at com.sun.proxy.$Proxy20.getFileInfo(Unknown Source)
    at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolTranslatorPB.getFileInfo(ClientNamenodeProtocolTranslatorPB.java:771)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:483)
    at org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:191)
    at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:102)
    at com.sun.proxy.$Proxy21.getFileInfo(Unknown Source)
    at org.apache.hadoop.hdfs.DFSClient.getFileInfo(DFSClient.java:2108)
    at org.apache.hadoop.hdfs.DistributedFileSystem$22.doCall(DistributedFileSystem.java:1305)
    at org.apache.hadoop.hdfs.DistributedFileSystem$22.doCall(DistributedFileSystem.java:1301)
    at org.apache.hadoop.fs.FileSystemLinkResolver.resolve(FileSystemLinkResolver.java:81)
    at org.apache.hadoop.hdfs.DistributedFileSystem.getFileStatus(DistributedFileSystem.java:1317)
    at org.apache.hadoop.fs.Globber.getFileStatus(Globber.java:57)
    at org.apache.hadoop.fs.Globber.glob(Globber.java:252)
    at org.apache.hadoop.fs.FileSystem.globStatus(FileSystem.java:1674)
    at org.apache.hadoop.mapred.FileInputFormat.singleThreadedListStatus(FileInputFormat.java:259)
    at org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInputFormat.java:229)
    at org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.java:315)
    at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:200)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:248)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:246)
    at scala.Option.getOrElse(Option.scala:121)
    at org.apache.spark.rdd.RDD.partitions(RDD.scala:246)
    at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:248)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:246)
    at scala.Option.getOrElse(Option.scala:121)
    at org.apache.spark.rdd.RDD.partitions(RDD.scala:246)
    at org.apache.spark.api.python.PythonRDD.getPartitions(PythonRDD.scala:53)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:248)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:246)
    at scala.Option.getOrElse(Option.scala:121)
    at org.apache.spark.rdd.RDD.partitions(RDD.scala:246)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:1911)
    at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:893)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
    at org.apache.spark.rdd.RDD.withScope(RDD.scala:358)
    at org.apache.spark.rdd.RDD.collect(RDD.scala:892)
    at org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:453)
    at org.apache.spark.api.python.PythonRDD.collectAndServe(PythonRDD.scala)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:483)
    at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:237)
    at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
    at py4j.Gateway.invoke(Gateway.java:280)
    at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:128)
    at py4j.commands.CallCommand.execute(CallCommand.java:79)
    at py4j.GatewayConnection.run(GatewayConnection.java:211)
    at java.lang.Thread.run(Thread.java:745)
Caused by: java.net.ConnectException: Connection refused
    at sun.nio.ch.SocketChannelImpl.checkConnect(Native Method)
    at sun.nio.ch.SocketChannelImpl.finishConnect(SocketChannelImpl.java:716)
    at org.apache.hadoop.net.SocketIOWithTimeout.connect(SocketIOWithTimeout.java:206)
    at org.apache.hadoop.net.NetUtils.connect(NetUtils.java:531)
    at org.apache.hadoop.net.NetUtils.connect(NetUtils.java:495)
    at org.apache.hadoop.ipc.Client$Connection.setupConnection(Client.java:614)
    at org.apache.hadoop.ipc.Client$Connection.setupIOstreams(Client.java:712)
    at org.apache.hadoop.ipc.Client$Connection.access$2900(Client.java:375)
    at org.apache.hadoop.ipc.Client.getConnection(Client.java:1528)
    at org.apache.hadoop.ipc.Client.call(Client.java:1451)
    ... 56 more

I'm guessing that there is some problem with configuration and that the client tries to connect to HDFS cluster, but I did not find any information that I should change the configuration or pass parameters before running the shell. What to do?

Answer 1

A similar question has been answered before here. Try file:///path_to_file instead.

According to the answer,

SparkContext.textFile internally calls org.apache.hadoop.mapred.FileInputFormat.getSplits, which in turn uses org.apache.hadoop.fs.getDefaultUri if schema is absent. This method reads "fs.defaultFS" parameter of Hadoop conf. If you set HADOOP_CONF_DIR environment variable, the parameter is usually set as "hdfs://..."; otherwise "file://".