If it was me I would prefix the map values outputs with a: and n:.
a: for address and n: for number
then on the reduce you could test the value to see if its the address or the name with if statements no need to worry about which one comes first just make sure they both have been set before output on the reduce.

Billy

"Amandeep Khurana" <ama...@gmail.com> wrote in message news:35a22e220902061646m941a545o554b189ed5bdb...@mail.gmail.com...
Ok. I was able to get this to run but have a slight problem.

*File 1*
1   10
2   20
3   30
3   35
4   40
4   45
4   49
5   50

*File 2*

a   10   123
b   20   21321
c   45   2131
d   40   2131111

I want to join the above two based on the second column of file 1. Here's
what I am getting as the output.

*Output*
1   a   123
b   21321   2
3
3
4   d   2131111
c   2131   4
4
5

The ones in red are in the format I want it. The ones in blue have their
order reversed. How can I get them to be in the correct order too?
Basically, the order in which the iterator iterates over the values is not
consistent. How can I get this to be consistent?

Amandeep

Amandeep Khurana
Computer Science Graduate Student
University of California, Santa Cruz


On Fri, Feb 6, 2009 at 2:58 PM, Amandeep Khurana <ama...@gmail.com> wrote:

Ok. Got it.

Now, how would my reducer know whether the name is coming first or the
address? Is it going to be in the same order in the iterator as the files
are read (alphabetically) in the mapper?


Amandeep Khurana
Computer Science Graduate Student
University of California, Santa Cruz


On Fri, Feb 6, 2009 at 5:22 AM, Jeff Hammerbacher <ham...@cloudera.com>wrote:

You put the files into a common directory, and use that as your input to
the
MapReduce job. You write a single Mapper class that has an "if" statement examining the map.input.file property, outputting "number" as the key for
both files, but "address" for one and "name" for the other. By using a
commone key ("number"), you'll  ensure that the name and address make it
to
the same reducer after the shuffle. In the reducer, you'll then have the
relevant information (in the values) you need to create the name, address
pair.

On Fri, Feb 6, 2009 at 2:17 AM, Amandeep Khurana <ama...@gmail.com>
wrote:

> Thanks Jeff...
> I am not 100% clear about the first solution you have given. How do I
get
> the multiple files to be read and then feed into a single reducer? I
should
> have multiple mappers in the same class and have different job configs
for
> them, run two separate jobs with one outputing the key as > (name,number)
and
> the other outputing the value as (number, address) into the reducer?
> Not clear what I'll be doing with the map.intput.file here...
>
> Amandeep
>
>
> Amandeep Khurana
> Computer Science Graduate Student
> University of California, Santa Cruz
>
>
> On Fri, Feb 6, 2009 at 1:55 AM, Jeff Hammerbacher > <ham...@cloudera.com
> >wrote:
>
> > Hey Amandeep,
> >
> > You can get the file name for a task via the "map.input.file"
property.
> For
> > the join you're doing, you could inspect this property and ouput
(number,
> > name) and (number, address) as your (key, value) pairs, depending on
the
> > file you're working with. Then you can do the combination in your
> reducer.
> >
> > You could also check out the join package in contrib/utils (
> >
> >
>
http://hadoop.apache.org/core/docs/current/api/org/apache/hadoop/contrib/utils/join/package-summary.html
> > ),
> > but I'd say your job is simple enough that you'll get it done faster
with
> > the above method.
> >
> > This task would be a simple join in Hive, so you could consider > > using
> Hive
> > to manage the data and perform the join.
> >
> > Later,
> > Jeff
> >
> > On Fri, Feb 6, 2009 at 1:34 AM, Amandeep Khurana > > <ama...@gmail.com>
> wrote:
> >
> > > Is it possible to write a map reduce job using multiple input > > > files?
> > >
> > > For example:
> > > File 1 has data like - Name, Number
> > > File 2 has data like - Number, Address
> > >
> > > Using these, I want to create a third file which has something > > > like
-
> > Name,
> > > Address
> > >
> > > How can a map reduce job be written to do this?
> > >
> > > Amandeep
> > >
> > >
> > >
> > > Amandeep Khurana
> > > Computer Science Graduate Student
> > > University of California, Santa Cruz
> > >
> >
>






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