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From Mohit Singh <>
Subject Re: Beginners Hadoop question
Date Mon, 03 Mar 2014 11:23:48 GMT
Not sure whether I understand your question correctly or not?
If you are trying to use hadoop ( as in map reduce programming model), then
basically you would have to use hadoop api's to solve your program.
But if you have data stored in hdfs, and you want to use spark to process
that data, then just specify the input path as spark.textFile("hdfs://...")

Take a look at these examples:

On Mon, Mar 3, 2014 at 3:19 AM, Alonso Isidoro Roman <>wrote:

> Hi, i am a beginner too, but as i have learned, hadoop works better with
> big files, at least with 64MB, 128MB or even more. I think you need to
> aggregate all the files into a new big one. Then you must copy to HDFS
> using this command:
> hadoop just copy MYFILE into hadoop distributed file system.
> Can i recommend you what i have done? go to and take
> the Hadoop Fundamentals I course. It is free and very well documented.
> Regards
> Alonso Isidoro Roman.
> Mis citas preferidas (de hoy) :
> "Si depurar es el proceso de quitar los errores de software, entonces
> programar debe ser el proceso de introducirlos..."
>  -  Edsger Dijkstra
> My favorite quotes (today):
> "If debugging is the process of removing software bugs, then programming
> must be the process of putting ..."
>   - Edsger Dijkstra
> "If you pay peanuts you get monkeys"
> 2014-03-03 12:10 GMT+01:00 goi cto <>:
> Hi,
>> I am sorry for the beginners question but...
>> I have a spark java code which reads a file (c:\my-input.csv) process it
>> and writes an output file (my-output.csv)
>> Now I want to run it on Hadoop in a distributed environment
>> 1) My inlut file should be one big file or separate smaller files?
>> 2) if we are using smaller files, how does my code needs to change to
>> process all of the input files?
>> Will Hadoop just copy the files to different servers or will it also
>> split their content among servers?
>> Any example will be great!
>> --
>> Eran | CTO


"When you want success as badly as you want the air, then you will get it.
There is no other secret of success."

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