you could join, it'll give you the intersection and a list of the labels
where the value was found.
> a.join(b).collect
Array[(String, (String, String))] = Array((4,(a,b)), (3,(a,b)))
best,
matt
On 08/31/2014 09:23 PM, Liu, Raymond wrote:
> You could use cogroup to combine RDDs in one RDD for cross reference
> processing.
>
> e.g.
>
> a.cogroup(b). filter{case (_, (l,r)) => l.nonEmpty && r.nonEmpty }. map{case
> (k,(l,r)) => (k, l)}
>
> Best Regards,
> Raymond Liu
>
> -----Original Message-----
> From: marylucy [mailto:[email protected]]
> Sent: Friday, August 29, 2014 9:26 PM
> To: Matthew Farrellee
> Cc: [email protected]
> Subject: Re: how to filter value in spark
>
> i see it works well，thank you!!!
>
> But in follow situation how to do
>
> var a = sc.textFile("/sparktest/1/").map((_,"a"))
> var b = sc.textFile("/sparktest/2/").map((_,"b"))
> How to get (3,"a") and (4,"a")????
>
>
> 在 Aug 28, 2014，19:54，"Matthew Farrellee" <[email protected]> 写道：
>
>> On 08/28/2014 07:20 AM, marylucy wrote:
>>> fileA=1 2 3 4 one number a line,save in /sparktest/1/
>>> fileB=3 4 5 6 one number a line,save in /sparktest/2/ I want to get
>>> 3 and 4
>>>
>>> var a = sc.textFile("/sparktest/1/").map((_,1))
>>> var b = sc.textFile("/sparktest/2/").map((_,1))
>>>
>>> a.filter(param=>{b.lookup(param._1).length>0}).map(_._1).foreach(prin
>>> tln)
>>>
>>> Error throw
>>> Scala.MatchError:Null
>>> PairRDDFunctions.lookup...
>>
>> the issue is nesting of the b rdd inside a transformation of the a rdd
>>
>> consider using intersection, it's more idiomatic
>>
>> a.intersection(b).foreach(println)
>>
>> but not that intersection will remove duplicates
>>
>> best,
>>
>>
>> matt
>>
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