is the following what you are looking for?
scala > sc.parallelize(myMap.map{ case (k,v) => (k,v) }.toSeq)
res2: org.apache.spark.rdd.RDD[(String, Int)] = ParallelCollectionRDD[0] at
parallelize at <console>:21
2014-10-13 14:02 GMT-07:00 jon.g.massey <jon.g.mas...@gmail.com>:
> Hi guys,
> Just starting out with Spark and following through a few tutorials, it
> seems
> the easiest way to get ones source data into an RDD is using the
> sc.parallelize function. Unfortunately, my local data is in multiple
> instances of Map<K,V> types, and the parallelize function only works on
> objects with the Seq trait, and produces an RDD which seemingly doesn't
> then
> have the notion of Keys and Values which I require for joins (amongst other
> functions).
>
> Is there a way of using a SparkContext to create a distributed RDD from a
> local Map, rather than from a Hadoop or text file source?
>
> Thanks,
> Jon
>
>
>
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