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courses:mapreduce-tutorial:step-6 [2012/01/29 20:25] straka |
courses:mapreduce-tutorial:step-6 [2012/01/30 13:46] straka |
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| * for any job, the counters and outputs of all mappers and reducers | * for any job, the counters and outputs of all mappers and reducers | ||
| * for any job, all Hadoop settings | * for any job, all Hadoop settings | ||
| + | |||
| + | ===== If things go wrong ===== | ||
| + | |||
| + | If the Hadoop job crashes, there are several ways you can do: | ||
| + | * run the computation locally in single threaded mode. This is more useful for Hadoop jobs written in Java, because then you can use a debugger. When using Perl API, new subprocess are created for Perl tasks anyway. | ||
| + | * use standard error output for log messages. You can access the stderr logs of all Hadoop tasks using the web interface. | ||
| ===== Example ===== | ===== Example ===== | ||