RDD里的模式匹配：
def hasNext: Boolean = (thisIter.hasNext, otherIter.hasNext) match {
case (true, true) => true
case (false, false) => false
case _ => throw new SparkException("Can only zip RDDs with " +
"same number of elements in each partition")
}
jobResult = jobResult match {
case Some(value) => Some(f(value, taskResult.get))
case None => taskResult
}
take(1) match {
case Array(t) => t
case _ => throw new UnsupportedOperationException("empty collection")
}
下面的比较好理解：
val len = rdd.dependencies.length
len match {
case 0 => Seq.empty
case 1 =>
val d = rdd.dependencies.head
debugString(d.rdd, prefix, d.isInstanceOf[ShuffleDependency[_, _, _]], true)
case _ => //所有的都到碗里来
val frontDeps = rdd.dependencies.take(len - 1)
val frontDepStrings = frontDeps.flatMap(
d => debugString(d.rdd, prefix, d.isInstanceOf[ShuffleDependency[_, _, _]]))
val lastDep = rdd.dependencies.last
val lastDepStrings =
debugString(lastDep.rdd, prefix, lastDep.isInstanceOf[ShuffleDependency[_, _, _]], true)
(frontDepStrings ++ lastDepStrings)
}
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