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When I run a mapreduce program using Hadoop, I get the following error.
10/01/18 10:52:48 INFO mapred.JobClient: Task Id : attempt_201001181020_0002_m_000014_0, Status : FAILED
java.io.IOException: Task process exit with nonzero status of 1.
at org.apache.hadoop.mapred.TaskRunner.run(TaskRunner.java:418)
10/01/18 10:52:48 WARN mapred.JobClient: Error reading task outputhttp://ubuntu.ubuntu-domain:50060/tasklog?plaintext=true&taskid=attempt_201001181020_0002_m_000014_0&filter=stdout
10/01/18 10:52:48 WARN mapred.JobClient: Error reading task outputhttp://ubuntu.ubuntu-domain:50060/tasklog?plaintext=true&taskid=attempt_201001181020_0002_m_000014_0&filter=stderr
What is this error about?
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Running Python MapReduce function To execute Python in Hadoop, we will need to use the Hadoop Streaming library to pipe the Python executable into the Java framework. As a result, we need to process the Python input from STDIN. Run ls and you should find mapper.py and reducer.py in the namenode container.
Hadoop framework is written in Java language; however, Hadoop programs can be coded in Python or C++ language.
MapReduce is written in Java but capable of running g in different languages such as Ruby, Python, and C++. Here we are going to use Python with the MR job package. We will count the number of reviews for each rating(1,2,3,4,5) in the dataset. Step 1: Transform raw data into key/value pairs in parallel.
One reason Hadoop produces this error is when the directory containing the log files becomes too full. This is a limit of the Ext3 Filesystem which only allows a maximum of 32000 links per inode.
Check how full your logs directory is in hadoop/userlogs
A simple test for this problem is to just try and create a directory from the command-line for example: $ mkdir hadoop/userlogs/testdir
If you have too many directories in userlogs the OS should fail to create the directory and report there are too many.
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