[jira] [Created] (SPARK-1955) VertexRDD can incorrectly assume index sharing

["Ankur Dave (JIRA)" <ji...@apache.org>]

Ankur Dave created SPARK-1955:
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             Summary: VertexRDD can incorrectly assume index sharing
                 Key: SPARK-1955
                 URL: https://issues.apache.org/jira/browse/SPARK-1955
             Project: Spark
          Issue Type: Bug
          Components: GraphX
    Affects Versions: 0.9.0, 1.0.0, 0.9.1
            Reporter: Ankur Dave
            Assignee: Ankur Dave
            Priority: Minor


Many VertexRDD operations (diff, leftJoin, innerJoin) can use a fast zip join if both operands are VertexRDDs sharing the same index (i.e., one operand is derived from the other). However, this check is implemented by matching on the operand type and using the fast join strategy if it is a VertexRDD.

When the two VertexRDDs have the same partitioner but different indexes, this is fine, because each VertexPartition will detect the index mismatch and fall back to the slow but correct local join strategy.

However, when they have different numbers of partitions or different partition functions, an exception or even silently incorrect results can occur.

For example:

{code}
// Construct VertexRDDs with different numbers of partitions
val a = VertexRDD(sc.parallelize(List((0L, 1), (1L, 2)), 1))
val b = VertexRDD(sc.parallelize(List((0L, 5)), 8))
// Try to join them. Appears to work...
val c = a.innerJoin(b) { (vid, x, y) => x + y }
// ... but then fails with java.lang.IllegalArgumentException: Can't zip RDDs with unequal numbers of partitions
c.collect
{code}

{code}
import org.apache.spark._
// Construct VertexRDDs with different partition functions
val a = VertexRDD(sc.parallelize(List((0L, 1), (1L, 2))).partitionBy(new HashPartitioner(2)))
val bVerts = sc.parallelize(List((1L, 5)))
val b = VertexRDD(bVerts.partitionBy(new RangePartitioner(2, bVerts)))
// Try to join them. We expect (1L, 7).
val c = a.innerJoin(b) { (vid, x, y) => x + y }
// Silent failure: we get an empty set!
c.collect
{code}

VertexRDD should check equality of partitioners before using the fast zip join. If the partitioners are different, the two datasets should be automatically co-partitioned.



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