From 5e3ec1110495899a298313c4aa9c6c151c1f54da Mon Sep 17 00:00:00 2001 From: kj-ki Date: Tue, 6 Jan 2015 09:49:37 -0800 Subject: [Minor] Fix comments for GraphX 2D partitioning strategy The sum of vertices on matrix (v0 to v11) is 12. And, I think one same block overlaps in this strategy. This is minor PR, so I didn't file in JIRA. Author: kj-ki Closes #3904 from kj-ki/fix-partitionstrategy-comments and squashes the following commits: 79829d9 [kj-ki] Fix comments for 2D partitioning. --- .../src/main/scala/org/apache/spark/graphx/PartitionStrategy.scala | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) (limited to 'graphx') diff --git a/graphx/src/main/scala/org/apache/spark/graphx/PartitionStrategy.scala b/graphx/src/main/scala/org/apache/spark/graphx/PartitionStrategy.scala index 13033fee0e..7372dfbd9f 100644 --- a/graphx/src/main/scala/org/apache/spark/graphx/PartitionStrategy.scala +++ b/graphx/src/main/scala/org/apache/spark/graphx/PartitionStrategy.scala @@ -32,9 +32,9 @@ trait PartitionStrategy extends Serializable { object PartitionStrategy { /** * Assigns edges to partitions using a 2D partitioning of the sparse edge adjacency matrix, - * guaranteeing a `2 * sqrt(numParts)` bound on vertex replication. + * guaranteeing a `2 * sqrt(numParts) - 1` bound on vertex replication. * - * Suppose we have a graph with 11 vertices that we want to partition + * Suppose we have a graph with 12 vertices that we want to partition * over 9 machines. We can use the following sparse matrix representation: * *
@@ -61,7 +61,7 @@ object PartitionStrategy {
    * that edges adjacent to `v11` can only be in the first column of blocks `(P0, P3,
    * P6)` or the last
    * row of blocks `(P6, P7, P8)`.  As a consequence we can guarantee that `v11` will need to be
-   * replicated to at most `2 * sqrt(numParts)` machines.
+   * replicated to at most `2 * sqrt(numParts) - 1` machines.
    *
    * Notice that `P0` has many edges and as a consequence this partitioning would lead to poor work
    * balance.  To improve balance we first multiply each vertex id by a large prime to shuffle the
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