Since you can translate between the two representations, either one works. It sounds like Measures within one bucket are always used together, even if they are not necessarily related. Their ordering matters. Therefore it seems like an RDD[(String,Seq[Measure])] or something is most appropriate. You can sort or aggregate with mapValues, and can combine RDDs with join.
On Sat, Aug 30, 2014 at 12:00 AM, cjwang <c...@cjwang.us> wrote: > I need some advices regarding how data are stored in an RDD. I have millions > of records, called "Measures". They are bucketed with keys of String type. > I wonder if I need to store them as RDD[(String, Measure)] or RDD[(String, > Iterable[Measure])], and why? > > Data in each bucket are not related most of the time. The operations that I > often needs to do are: > > - Sort the Measures in each bucket separately > - Aggregate the Measures in each bucket separately > - Combine Measures in two RDDs into one based on their bucket keys > > > > > > > -- > View this message in context: > http://apache-spark-user-list.1001560.n3.nabble.com/What-is-the-better-data-structure-in-an-RDD-tp13159.html > Sent from the Apache Spark User List mailing list archive at Nabble.com. > > --------------------------------------------------------------------- > To unsubscribe, e-mail: user-unsubscr...@spark.apache.org > For additional commands, e-mail: user-h...@spark.apache.org > --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org
