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Posted to common-user@hadoop.apache.org by Kevin Burton <rk...@charter.net> on 2013/04/30 18:36:11 UTC
Can't initialize cluster
I have a simple MapReduce job that I am trying to get to run on my cluster.
When I run it I get:
13/04/30 11:27:45 INFO mapreduce.Cluster: Failed to use
org.apache.hadoop.mapred.LocalClientProtocolProvider due to error: Invalid
"mapreduce.jobtracker.address" configuration value for LocalJobRunner :
"devubuntu05:9001"
13/04/30 11:27:45 ERROR security.UserGroupInformation:
PriviledgedActionException as:kevin (auth:SIMPLE) cause:java.io.IOException:
Cannot initialize Cluster. Please check your configuration for
mapreduce.framework.name and the correspond server addresses.
Exception in thread "main" java.io.IOException: Cannot initialize Cluster.
Please check your configuration for mapreduce.framework.name and the
correspond server addresses.
My core-site.xml looks like:
<property>
<name>fs.default.name</name>
<value>hdfs://devubuntu05:9000</value>
<description>The name of the default file system. A URI whose scheme and
authority determine the FileSystem implementation. </description>
</property>
So I am unclear as to why it is looking at devubuntu05:9001?
Here is the code:
public static void WordCount( String[] args ) throws Exception {
Configuration conf = new Configuration();
String[] otherArgs = new GenericOptionsParser(conf,
args).getRemainingArgs();
if (otherArgs.length != 2) {
System.err.println("Usage: wordcount <in> <out>");
System.exit(2);
}
Job job = new Job(conf, "word count");
job.setJarByClass(WordCount.class);
job.setMapperClass(WordCount.TokenizerMapper.class);
job.setCombinerClass(WordCount.IntSumReducer.class);
job.setReducerClass(WordCount.IntSumReducer.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
org.apache.hadoop.mapreduce.lib.input.FileInputFormat.addInputPath(job, new
Path(otherArgs[0]));
org.apache.hadoop.mapreduce.lib.output.FileOutputFormat.setOutputPath(job,
new Path(otherArgs[1]));
System.exit(job.waitForCompletion(true) ? 0 : 1);
Ideas?