[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 <[email protected]> Closes apache#3904 from kj-ki/fix-partitionstrategy-comments and squashes the following commits: 79829d9 [kj-ki] Fix comments for 2D partitioning.
koeninger · Jan 6, 2015 · 5e3ec11 · 5e3ec11
1 parent a6394bc
commit 5e3ec11
Showing 1 changed file with 3 additions and 3 deletions.
diff --git 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:
    *
    * <pre>
@@ -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