If you assign each file to a standalone partition, then you can generate
the Rating RDD using something like the following:
files.mapPartitions { part =>
product = part.next()
part.map((user, rating) => (user, product, rating))
}
Thanks,
-Jason
On Tue, Jan 7, 2014 at 1:17 AM, Nan Zhu <[email protected]> wrote:
> Hi, all
>
> I meet a question related to how to share a variable among tasks, it seems
> that neither broadcast nor accumulator can resolve my problem
>
> I have a set of txt files as my dataset, naming 1.txt - 20000.txt
>
> each txt file represents the rating of users to a certain product, the
> product ID is indicated in the first line of each file, “1:”…”20000:”
>
> the following lines are ratings “userid, rating"
>
> I want to parse the input files with spark and pass it to the ALS
> implementation in mllib
>
> the ALS requires me to have a RDD of Rating objects, where Rating is
> 3-tuple (user, product, rating)
>
> My problem is that some tasks get the partition of a certain text file, so
> it will never see the first line like “1:” so that it cannot get which
> product the rating is corresponded to
>
> How can I resolve this, except getting some script to transform the format
> of the files by appending the product id to each line?
>
> Best,
>
> --
> Nan Zhu
>
>
