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feat: performance improvement in GraphX CDLP #681

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Merged
SemyonSinchenko merged 1 commit into from
Sep 13, 2025
Merged

feat: performance improvement in GraphX CDLP #681

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4 changes: 0 additions & 4 deletions core/src/test/scala/org/graphframes/ldbc/TestLDBCCases.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -117,10 +117,6 @@ class TestLDBCCases extends SparkFunSuite with GraphFrameTestSparkContext {

Seq("graphx", "graphframes").foreach { algo =>
test(s"test undirected CDLP with LDBC for algo ${algo}") {
// I have no idea how to write it so it will work
if (scala.util.Properties.versionNumberString.startsWith("2.12") && algo == "graphx") {
cancel("CDLP implementations are broken in 2.12, see #571")
}
val testCase = ldbcTestCDLPUndirected
val cdlpResults = testCase._1.labelPropagation.setAlgorithm(algo).maxIter(testCase._3).run()
assert(cdlpResults.count() == testCase._1.vertices.count())
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27 changes: 8 additions & 19 deletions graphx/src/main/scala/org/apache/spark/graphframes/graphx/lib/LabelPropagation.scala
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Expand Up @@ -19,8 +19,6 @@ package org.apache.spark.graphframes.graphx.lib
import org.apache.spark.graphframes.graphx._

import scala.annotation.nowarn
import scala.collection.Map
import scala.collection.mutable
import scala.reflect.ClassTag

/** Label Propagation algorithm. */
Expand Down Expand Up @@ -53,26 +51,17 @@ object LabelPropagation {
require(maxSteps > 0, s"Maximum of steps must be greater than 0, but got ${maxSteps}")

val lpaGraph = graph.mapVertices { case (vid, _) => vid }
def sendMessage(e: EdgeTriplet[VertexId, ED]): Iterator[(VertexId, Map[VertexId, Long])] = {
Iterator((e.srcId, Map(e.dstAttr -> 1L)), (e.dstId, Map(e.srcAttr -> 1L)))
}
def mergeMessage(
count1: Map[VertexId, Long],
count2: Map[VertexId, Long]): Map[VertexId, Long] = {
// Mimics the optimization of breakOut, not present in Scala 2.13, while working in 2.12
val map = mutable.Map[VertexId, Long]()
(count1.keySet ++ count2.keySet).foreach { i =>
val count1Val = count1.getOrElse(i, 0L)
val count2Val = count2.getOrElse(i, 0L)
map.put(i, count1Val + count2Val)
}
map
def sendMessage(e: EdgeTriplet[VertexId, ED]): Iterator[(VertexId, Vector[Long])] = {
Iterator((e.srcId, Vector(e.dstAttr)), (e.dstId, Vector(e.srcAttr)))
}
def mergeMessage(left: Vector[Long], right: Vector[Long]): Vector[Long] = left ++ right

@nowarn
def vertexProgram(vid: VertexId, attr: Long, message: Map[VertexId, Long]): VertexId = {
if (message.isEmpty) attr else message.maxBy(_._2)._1
def vertexProgram(vid: VertexId, attr: Long, message: Vector[Long]): Long = {
if (message.isEmpty) attr
else message.groupBy(f => f).map(f => (f._1, f._2.size)).maxBy(f => (f._2, -f._1))._1
}
val initialMessage = Map[VertexId, Long]()
val initialMessage = Vector[Long]()
Pregel(lpaGraph, initialMessage, maxIterations = maxSteps)(
vprog = vertexProgram,
sendMsg = sendMessage,
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