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Whenever a client submits a hadoop job, who receives it?

+1 vote
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Whenever a client submits a hadoop job, who receives it?
posted Jul 14, 2017 by Karthick.c

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+1 vote

A mapreduce job can be run as jar file from terminal or directly from eclipse IDE. When a job run as jar file from terminal it uses multiple jvm and all resources of cluster. Does the same thing happen when we run from IDE. I have run a job on both and it takes less time on IDE than jar file on terminal.

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I want to ask, what's the best way implementing a Job which is importing files into the HDFS?

I have an external System offering data accessible through a Rest API. My goal is to have a job running in Hadoop which is periodical (maybe started by chron?) looking into the Rest API if new data is available.

It would be nice if also this job could run on multiple data nodes. But in difference to all the MapReduce examples I found, is my job looking for new Data or changed data from an external interface and compares the data with existing one.

This is a conceptual example of the job:

  • The job ask the Rest API if there are new files
  • if so, the job imports the first file in the list
  • look if the file already exits

  • if not, the job imports the file

  • if yes, the job compares the data with the data already stored

  • if changed the job updates the file

  • if more file exits the job continues with 2 -

  • otherwise ends.

Can anybody give me a little help how to start (its my first job I write...) ?

+1 vote

To run a job we use the command
$ hadoop jar example.jar inputpath outputpath
If job is so time taken and we want to stop it in middle then which command is used? Or is there any other way to do that?

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