Hi Jacek,
Thanks for the suggestion, i am going to try union.
And what is your opinion on 2nd question.
Thanks
Shams
On Tue, Dec 1, 2015 at 3:23 PM, Jacek Laskowski wrote:
> Hi,
>
> Never done it before, but just yesterday I found out about
> SparkContext.union method that
cogroup could be useful to you, since all three are PairRDD's.
https://spark.apache.org/docs/latest/api/scala/index.html#org.apache.spark.rdd.PairRDDFunctions
Best Regards,
Praveen
On 01.12.2015 10:47, Shams ul Haque wrote:
Hi All,
I have made 3 RDDs of 3 different dataset, all RDDs are
I think you should be able to join different rdds with same key. Have you
tried that?
On Dec 1, 2015 3:30 PM, "Praveen Chundi" wrote:
> cogroup could be useful to you, since all three are PairRDD's.
>
>
>
Hi,
I have myself used union in a similar case. And applied reduceByKey on it.
Union + reduceByKey will suffice join... but you will have to first use Map
so that all values are of same datatype
Regards,
Sushrut Ikhar
[image: https://]about.me/sushrutikhar
On Tue, Dec 1, 2015 at 10:57 AM, Shams ul Haque wrote:
> Thanks for the suggestion, i am going to try union.
...and please report your findings back.
> And what is your opinion on 2nd question.
Dunno. If you find a solution, let us know.
Jacek