org.hammerlab.magic.rdd

CachedCountRegistry

class CachedCountRegistry extends AnyRef

CachedCountRegistry adds a .size method to RDDs that mimicks RDD.count, but caches its result.

It also exposes .sizes and .total on Seq[RDD]s, which compute the constituent RDDs' sizes (per above) in one Spark job.

Additionally, both sets of APIs optimize computations on UnionRDDs by computing their component RDDs' sizes and caching those as well as the UnionRDD's total.

Cached size info is keyed by a SparkContext for robustness in apps that stop their SparkContext and then resume with a new one; this is especially useful for testing!

Usage:

\ * import org.hammerlab.magic.rdd.CachedCountRegistry._
val rdd1 = sc.parallelize(0 until 4)
val rdd2 = sc.parallelize("a" :: "b" :: Nil)
rdd1.size()
(rdd1 :: rdd2 :: Nil).sizes()
(rdd1 :: rdd2 :: Nil).total()
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  7. def cachedCount(rdd: RDD[_]): Long

    Count RDD and cache result for RDD id

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  15. def multiCachedCount(rdds: Seq[RDD[_]]): Seq[Long]

    Compute multiple RDDs' sizes with a single Spark job; cache and return these sizes separately.

    Compute multiple RDDs' sizes with a single Spark job; cache and return these sizes separately.

    Along the way, this method will construct a UnionRDD from all non-cached, non-Union RDDs.

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