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courses:mapreduce-tutorial:managing-a-hadoop-cluster [2012/02/05 19:16] straka vytvořeno |
courses:mapreduce-tutorial:managing-a-hadoop-cluster [2013/02/08 15:25] (current) popel |
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- | ====== MapReduce Tutorial : ====== | + | ====== MapReduce Tutorial : Managing a Hadoop cluster |
+ | |||
+ | Hadoop clusters can be created and stopped dynamically, | ||
+ | |||
+ | A Hadoop cluster can be created: | ||
+ | * for a specific Hadoop job. This is done by executing the job with the '' | ||
+ | * manually using ''/ | ||
+ | |||
+ | When a Hadoop cluster is about to start, a job is submitted to SGE cluster. When the cluster starts successfully, | ||
+ | * '' | ||
+ | * '' | ||
+ | * '' | ||
+ | |||
+ | A Hadoop cluster is stopped: | ||
+ | * after the timeout specified by '' | ||
+ | * when the '' | ||
+ | * using '' | ||
+ | |||
+ | ===== Web interface ===== | ||
+ | |||
+ | The web interface provides a lot of useful information: | ||
+ | * running, failed and successfully completed jobs | ||
+ | * for running job, current progress and counters of the whole job and also of each mapper and reducer is available | ||
+ | * for any job, the counters and outputs of all mappers and reducers | ||
+ | * for any job, all Hadoop settings | ||
+ | |||
+ | ===== Killing running jobs ===== | ||
+ | |||
+ | Jobs running in a cluster can be stopped using | ||
+ | < | ||
+ | |||
+ | The jobs running on a cluster are present in the web interface, or can be printed using | ||
+ | < |