I think Yes, as the documentation says " Creates tuples of the elements in
this RDD by applying f. "
Thanks
Best Regards
On Tue, Jun 9, 2015 at 1:54 PM, amit tewari <amittewar...@gmail.com> wrote:
> Actually the question was will keyBy() take accept multiple fields (eg
> x(0), x(1)) as Key?
>
>
> On Tue, Jun 9, 2015 at 1:07 PM, amit tewari <amittewar...@gmail.com>
> wrote:
>
>> Thanks Akhil, as you suggested, I have to go keyBy(route) as need the
>> columns intact.
>> But wil keyBy() take accept multiple fields (eg x(0), x(1))?
>>
>> Thanks
>> Amit
>>
>> On Tue, Jun 9, 2015 at 12:26 PM, Akhil Das <ak...@sigmoidanalytics.com>
>> wrote:
>>
>>> Try this way:
>>>
>>> scala>val input1 = sc.textFile("/test7").map(line =>
>>> line.split(",").map(_.trim));
>>> scala>val input2 = sc.textFile("/test8").map(line =>
>>> line.split(",").map(_.trim));
>>> scala>val input11 = input1.map(x=>(*(x(0) + x(1)*),x(2),x(3)))
>>> scala>val input22 = input2.map(x=>(*(x(0) + x(1)*),x(2),x(3)))
>>>
>>> scala> input11.join(input22).take(10)
>>>
>>>
>>> PairFunctions basically requires RDD[K,V] and in your case its ((String,
>>> String), String, String). You can also look in keyBy if you don't want to
>>> concatenate your keys.
>>>
>>> Thanks
>>> Best Regards
>>>
>>> On Tue, Jun 9, 2015 at 10:14 AM, amit tewari <amittewar...@gmail.com>
>>> wrote:
>>>
>>>> Hi Dear Spark Users
>>>>
>>>> I am very new to Spark/Scala.
>>>>
>>>> Am using Datastax (4.7/Spark 1.2.1) and struggling with following
>>>> error/issue.
>>>>
>>>> Already tried options like import org.apache.spark.SparkContext._ or
>>>> explicit import org.apache.spark.SparkContext.rddToPairRDDFunctions.
>>>> But error not resolved.
>>>>
>>>> Help much appreciated.
>>>>
>>>> Thanks
>>>> AT
>>>>
>>>> scala>val input1 = sc.textFile("/test7").map(line =>
>>>> line.split(",").map(_.trim));
>>>> scala>val input2 = sc.textFile("/test8").map(line =>
>>>> line.split(",").map(_.trim));
>>>> scala>val input11 = input1.map(x=>((x(0),x(1)),x(2),x(3)))
>>>> scala>val input22 = input2.map(x=>((x(0),x(1)),x(2),x(3)))
>>>>
>>>> scala> input11.join(input22).take(10)
>>>>
>>>> <console>:66: error: value join is not a member of
>>>> org.apache.spark.rdd.RDD[((String, String), String, String)]
>>>>
>>>> input11.join(input22).take(10)
>>>>
>>>>
>>>>
>>>>
>>>>
>>>>
>>>>
>>>
>>
>
