Hello everyone, I'm a newbie in both hadoop and spark so please forgive any obvious mistakes, I'm posting because my google-fu has failed me.
I'm trying to run a test Spark script in order to connect Spark to hadoop. The script is the following from pyspark import SparkContext sc = SparkContext("local", "Simple App") file = sc.textFile("hdfs://hadoop_node.place:9000/errs.txt") errors = file.filter(lambda line: "ERROR" in line) errors.count() When I run it with pyspark I get py4j.protocol.Py4JJavaError: An error occurred while calling o21.collect. : java.io.IOException: Can't get Master Kerberos principal for use as renewer at org.apache.hadoop.mapreduce.security.TokenCache.obtainTokensForNamenodesInternal(TokenCache.java:116) at org.apache.hadoop.mapreduce.security.TokenCache.obtainTokensForNamenodesInternal(TokenCache.java:100) at org.apache.hadoop.mapreduce.security.TokenCache.obtainTokensForNamenodes(TokenCache.java:80) at org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInputFormat.java:187) at org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.java:251) at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:140) at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:207) at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:205) at scala.Option.getOrElse(Option.scala:120) at org.apache.spark.rdd.RDD.partitions(RDD.scala:205) at org.apache.spark.rdd.MappedRDD.getPartitions(MappedRDD.scala:28) at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:207) at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:205) at scala.Option.getOrElse(Option.scala:120) at org.apache.spark.rdd.RDD.partitions(RDD.scala:205) at org.apache.spark.api.python.PythonRDD.getPartitions(PythonRDD.scala:46) at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:207) at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:205) at scala.Option.getOrElse(Option.scala:120) at org.apache.spark.rdd.RDD.partitions(RDD.scala:205) at org.apache.spark.SparkContext.runJob(SparkContext.scala:898) at org.apache.spark.rdd.RDD.collect(RDD.scala:608) at org.apache.spark.api.java.JavaRDDLike$class.collect(JavaRDDLike.scala:243) at org.apache.spark.api.java.JavaRDD.collect(JavaRDD.scala:27) 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 py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231) at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:379) at py4j.Gateway.invoke(Gateway.java:259) at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132) at py4j.commands.CallCommand.execute(CallCommand.java:79) at py4j.GatewayConnection.run(GatewayConnection.java:207) at java.lang.Thread.run(Thread.java:744) This happens despite the facts that - I've done a kinit and a klist shows I have the correct tokens - when I issue a ./bin/hadoop fs -ls hdfs://hadoop_node.place:9000/errs.txt it shows the file - Both the local hadoop client and spark have the same configuration file The core-site.xml in the spark/conf and hadoop/conf folders is the following (got it from one of the hadoop nodes) <configuration> <property> <name>hadoop.security.auth_to_local</name> <value> RULE:[1:$1](.*@place)s/@place// RULE:[2:$1/$2@$0](.**/node1.place@place)s/*^([a-zA-Z]*).*/$1/ RULE:[2:$1/$2@$0](.**/node2.place@place)s/*^([a-zA-Z]*).*/$1/ RULE:[2:$1/$2@$0](.**/node3.place@place)s/*^([a-zA-Z]*).*/$1/ RULE:[2:$1/$2@$0](.**/node4.place@place)s/*^([a-zA-Z]*).*/$1/ RULE:[2:$1/$2@$0](.**/node5.place@place)s/*^([a-zA-Z]*).*/$1/ RULE:[2:$1/$2@$0](.**/node6.place@place)s/*^([a-zA-Z]*).*/$1/ RULE:[2:$1/$2@$0](.**/node7.place@place)s/*^([a-zA-Z]*).*/$1/ RULE:[2:nobody] DEFAULT </value> </property> <property> <name>net.topology.node.switch.mapping.impl</name> <value>org.apache.hadoop.net.TableMapping</value> </property> <property> <name>net.topology.table.file.name</name> <value>/etc/hadoop/conf/topology.table.file</value> </property> <property> <name>fs.defaultFS</name> <value>hdfs://server.place:9000/</value> </property> <property> <name>hadoop.security.authentication</name> <value>kerberos</value> </property> <property> <name>hadoop.security.authorization</name> <value>true</value> </property> <property> <name>hadoop.proxyuser.hive.hosts</name> <value>*</value> </property> <property> <name>hadoop.proxyuser.hive.groups</name> <value>*</value> </property> </configuration> Can someone point out what am I missing?