Github user lianhuiwang commented on a diff in the pull request:
https://github.com/apache/spark/pull/3505#discussion_r22773920
--- Diff: core/src/main/scala/org/apache/spark/rdd/PairRDDFunctions.scala
---
@@ -487,6 +487,196 @@ class PairRDDFunctions[K, V](self: RDD[(K, V)])
}
/**
+ * ::Experimental::
+ * Return an RDD containing all pairs of elements with matching keys in
`this` and `other`. Each
+ * pair of elements will be returned as a (k, (v1, v2)) tuple, where (k,
v1) is in `this` and
+ * (k, v2) is in `other`. Performs a hash join across the cluster.
+ *
+ * It supports to join skewed data. If values of some key cannot be fit
into memory, it will spill
+ * them to disk.
+ */
+ @Experimental
+ def skewedJoin[W: ClassTag](other: RDD[(K, W)]): RDD[(K, (V, W))] = {
--- End diff --
how about we just use previous join api. if we want to use skewedJoin, we
can set spark.join.skew=true. Running application based on common join api can
use skewedJoin without any changes.@zsxwing
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