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MapReduce Tutorial : Running jobs
The input of a Hadoop job is either a file, or a directory. In latter case all files in the directory are processed.
The output of a Hadoop job must be a directory, which does not exist.
Running jobs
| Command | |
|---|---|
Run Perl script script.pl | perl script.pl options |
Run Java job job.jar | /net/projects/hadoop/bin/hadoop job.jar options |
The options are the same for Perl and java:
| Options | |
|---|---|
| Run locally | input output |
| Run using specified jobtracker | -jt jobtracker:port input output |
| Run job in dedicated cluster | -c number_of_machines input output |
| Run job in dedicated cluster and after it finishes, wait for W seconds before stopping the cluster | -c number_of_machines -w W_seconds input output |
| Run using R reducers (R>1 not working when running locally) | -r R input output |
| Run using M mappers | `/net/projects/hadoop/bin/compute-splitsize input M` input output |