hadoop-streaming

I am trying to process XML files from hadoop, i got following error on invoking word-count job on XML files . 13/07/25 12:39:57 INFO mapred.JobClient: Task Id : attempt_201307251234_0001_m_000008_0, Status : FAILED Too many fetch-failures 13/07/25 12:39:58 INFO mapred.JobClient: map 99% reduce 0% 13/07/25 12:39:59 INFO mapred.JobClient: map 100% reduce 0% 13/07/25 12:40:56 INFO mapred.JobClient: Task Id : attempt_201307251234_0001_m_000009_0, Status : FAILED Too many fetch-failures 13/07/25 12:40:58 INFO mapred.JobClient: map 99% reduce 0% 13/07/25 12:40:59 INFO mapred.JobClient: map 100%

I can see all hadoop logs on my /usr/local/hadoop/logs path but where can I see application level logs? for example : mapper.py import logging def main(): logging.info("starting map task now") // -- do some task -- // print statement reducer.py import logging def main(): for line in sys.stdin: logging.info("received input to reducer - " + line) // -- do some task -- // print statement Where I can see logging.info or related log statements of my application? I am using Python and using hadoop-streaming Thank you Praveen Sripati Hadoop streaming uses STDIN/STDOUT for passing the key/value pairs

I'm running a streaming Hadoop job and the byte offsets are not being generated as output (keys) of the mapper, like I would expect it too. The command: $HADOOP_INSTALL/bin/hadoop \ jar $HADOOP_INSTALL/contrib/streaming/hadoop-streaming-$HADOOP_VERSION.jar \ -D stream.map.input.ignoreKey=false \ -inputformat org.apache.hadoop.mapred.TextInputFormat \ -file ./mapper.py \ -file ./reducer.py \ -mapper ./mapper.py \ -reducer ./reducer.py \ -input $INPUT_DIR \ -output $OUTPUT_DIR \ -cmdenv REGEX=$REGEX My understanding is that TextInputFormat is the default, so I also tried the above command

I'm a newcomer to Ubuntu, Hadoop and DFS but I've managed to install a single-node hadoop instance on my local ubuntu machine following the directions posted on Michael-Noll.com here: http://www.michael-noll.com/tutorials/running-hadoop-on-ubuntu-linux-single-node-cluster/#copy-local-example-data-to-hdfs http://www.michael-noll.com/tutorials/writing-an-hadoop-mapreduce-program-in-python/ I'm currently stuck on running the basic word count example on Hadoop. I'm not sure if the fact I've been running Hadoop out of my Downloads directory makes too much of a difference, but I've atempted to tweek

I have a sequential file which is the output of hadoop map-reduce job. In this file data is written in key value pairs ,and value itself is a map. I want to read the value as a MAP object so that i can process it further. Configuration config = new Configuration(); Path path = new Path("D:\\OSP\\sample_data\\data\\part-00000"); SequenceFile.Reader reader = new SequenceFile.Reader(FileSystem.get(config), path, config); WritableComparable key = (WritableComparable) reader.getKeyClass().newInstance(); Writable value = (Writable) reader.getValueClass().newInstance(); long position = reader

I want to read the PDF file using hadoop, how it is possible? I only know that hadoop can process only txt files, so is there anyway to parse the PDF files to txt. Give me some suggestion. An easy way would be to create a SequenceFile to contain the PDF files. SequenceFile is a binary file format. You could make each record in the SequenceFile a PDF. To do this you would create a class derived from Writable which would contain the PDF and any metadata that you needed. Then you could use any java PDF library such as PDFBox to manipulate the PDFs. Processing PDF files in Hadoop can be done by