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The following page has been changed by OwenOMalley: http://wiki.apache.org/lucene-hadoop/HowToDebugMapReducePrograms ------------------------------------------------------------------------------ This can be extremely useful to display debug information about the current record being handled, or setting certain debug flags about the status of the mapper. While running locally on a small data set can find many bugs, large data sets may contain pathological cases that are otherwise unexepcted. This method of debugging can help catch those cases. + == How to debug Hadoop Pipes programs + + In order to debug Pipes programs you need to keep the downloaded commands. + + First, to keep the !TaskTracker from deleting the files when the task is finished, you need to set either keep.failed.task.files (set to true if the task you want to debug fails) or keep.task.files.pattern (set to a regex of the task name you want to debug). + + Second, your job should set hadoop.pipes.command-file.keep to true in the JobConf. This will cause all of the tasks in the job to write their command stream to a file in the working directory named downlink.data. This file will contain the JobConf, the task information, and the task input, so it may be large. But it provides enough information that your executable will run without any interaction with the framework. + + Third, go to the host where the problem task ran, go into the work directory and + {{{ + setenv hadoop.pipes.command.file downlink.data + }}} + and run your executable under the debugger or valgrind. It will run as if the framework was feeding it commands and data and produce a output file downlink.data.out with the binary commands that it would have sent up to the framework. I guess eventually, I should have the output file be written in text rather than binary... +
