graphframes · rjurney · Jan 17, 2025 · Jan 15, 2025 · Jan 15, 2025 · Jan 15, 2025
diff --git a/src/main/scala/org/graphframes/GraphFrame.scala b/src/main/scala/org/graphframes/GraphFrame.scala
@@ -52,8 +52,10 @@ class GraphFrame private(
   override def toString: String = {
     // We call select on the vertices and edges to ensure that ID, SRC, DST always come first
     // in the printed schema.
-    val v = vertices.select(ID, vertices.columns.filter(_ != ID) :_ *).toString
-    val e = edges.select(SRC, DST +: edges.columns.filter(c => c != SRC && c != DST) :_ *).toString
+    val vCols = (ID +: vertices.columns.filter(_ != ID).toIndexedSeq).map(col)
+    val eCols = (SRC +: DST +: edges.columns.filter(c => c != SRC && c != DST).toIndexedSeq).map(col)
+    val v = vertices.select(vCols.toSeq: _*).toString
+    val e = edges.select(eCols.toSeq: _*).toString
     "GraphFrame(v:" + v + ", e:" + e + ")"
   }
 
@@ -708,7 +710,7 @@ object GraphFrame extends Serializable with Logging {
   def fromEdges(e: DataFrame): GraphFrame = {
     val srcs = e.select(e("src").as("id"))
     val dsts = e.select(e("dst").as("id"))
-    val v = srcs.unionAll(dsts).distinct
+    val v = srcs.unionAll(dsts).distinct()
     v.persist(StorageLevel.MEMORY_AND_DISK)
     apply(v, e)
   }
@@ -802,7 +804,7 @@ object GraphFrame extends Serializable with Logging {
   private[graphframes] def colStar(df: DataFrame, col: String): Seq[String] = {
     df.schema(col).dataType match {
       case s: StructType =>
-        s.fieldNames.map(f => col + "." + f)
+        s.fieldNames.map(f => col + "." + f).toIndexedSeq
       case other =>
         throw new RuntimeException(s"Unknown error in GraphFrame. Expected column $col to be" +
           s" StructType, but found type: $other")
@@ -811,7 +813,7 @@ object GraphFrame extends Serializable with Logging {
 
   /** Nest all columns within a single StructType column with the given name */
   private[graphframes] def nestAsCol(df: DataFrame, name: String): Column = {
-    struct(df.columns.map(c => df(c)) :_*).as(name)
+    struct(df.columns.map(c => df(c)).toSeq: _*).as(name)
   }
 
   // ========== Motif finding ==========

diff --git a/src/main/scala/org/graphframes/examples/BeliefPropagation.scala b/src/main/scala/org/graphframes/examples/BeliefPropagation.scala
@@ -129,7 +129,7 @@ object BeliefPropagation {
   def runBPwithGraphX(g: GraphFrame, numIter: Int): GraphFrame = {
     // Choose colors for vertices for BP scheduling.
     val colorG = colorGraph(g)
-    val numColors: Int = colorG.vertices.select("color").distinct.count().toInt
+    val numColors: Int = colorG.vertices.select("color").distinct().count().toInt
 
     // Convert GraphFrame to GraphX, and initialize beliefs.
     val gx0 = colorG.toGraphX
@@ -206,7 +206,7 @@ object BeliefPropagation {
   def runBPwithGraphFrames(g: GraphFrame, numIter: Int): GraphFrame = {
     // Choose colors for vertices for BP scheduling.
     val colorG = colorGraph(g)
-    val numColors: Int = colorG.vertices.select("color").distinct.count().toInt
+    val numColors: Int = colorG.vertices.select("color").distinct().count().toInt
 
     // TODO: Handle vertices without any edges.
 

diff --git a/src/main/scala/org/graphframes/examples/Graphs.scala b/src/main/scala/org/graphframes/examples/Graphs.scala
@@ -122,12 +122,12 @@ class Graphs private[graphframes] () {
    */
   def ALSSyntheticData(): GraphFrame = {
     val sc = spark.sparkContext
-    val data = sc.parallelize(als_data).map { line =>
+    val data = sc.parallelize(als_data.toIndexedSeq).map { line =>
       val fields = line.split(",")
       (fields(0).toLong * 2, fields(1).toLong * 2 + 1, fields(2).toDouble)
     }
     val edges = spark.createDataFrame(data).toDF("src", "dst", "weight")
-    val vs = data.flatMap(r => r._1 :: r._2 :: Nil).collect().distinct.map(x => Tuple1(x))
+    val vs = data.flatMap(r => r._1 :: r._2 :: Nil).collect().distinct.map(x => Tuple1(x)).toIndexedSeq
     val vertices = spark.createDataFrame(vs).toDF("id")
     GraphFrame(vertices, edges)
   }

diff --git a/src/main/scala/org/graphframes/lib/BFS.scala b/src/main/scala/org/graphframes/lib/BFS.scala
@@ -218,7 +218,7 @@ private object BFS extends Logging with Serializable {
         }
       }
       val ordered = paths.columns.sortBy(rank _)
-      paths.select(ordered.map(col): _*)
+      paths.select(ordered.map(col).toSeq: _*)
     } else {
       logInfo(s"GraphFrame.bfs failed to find a path of length <= $maxPathLength.")
       // Return empty DataFrame

diff --git a/src/main/scala/org/graphframes/lib/GraphXConversions.scala b/src/main/scala/org/graphframes/lib/GraphXConversions.scala
@@ -104,10 +104,10 @@ private[graphframes] object GraphXConversions {
     val otherFields = df.schema.fieldNames.filter(_ != structName).map(col)
     if (renamedSubfields.isEmpty) {
       // Do not attempt to add an empty structure.
-      df.select(otherFields : _*)
+      df.select(otherFields.toSeq: _*)
     } else {
-      val renamedStruct = struct(renamedSubfields : _*).as(structName)
-      df.select(renamedStruct +: otherFields : _*)
+      val renamedStruct = struct(renamedSubfields.toSeq: _*).as(structName)
+      df.select((renamedStruct +: otherFields).toSeq: _*)
     }
   }
 

diff --git a/src/main/scala/org/graphframes/lib/ShortestPaths.scala b/src/main/scala/org/graphframes/lib/ShortestPaths.scala
@@ -19,7 +19,7 @@ package org.graphframes.lib
 
 import java.util
 
-import scala.collection.JavaConverters._
+import scala.jdk.CollectionConverters._
 
 import org.apache.spark.graphx.{lib => graphxlib}
 import org.apache.spark.sql.{Column, DataFrame, Row}
@@ -91,7 +91,7 @@ private object ShortestPaths {
       mapToLandmark(col(DISTANCE_ID))
     }
     val cols = graph.vertices.columns.map(col) :+ distanceCol.as(DISTANCE_ID)
-    g.vertices.select(cols: _*)
+    g.vertices.select(cols.toSeq: _*)
   }
 
   private val DISTANCE_ID = "distances"

diff --git a/src/main/scala/org/graphframes/lib/TriangleCount.scala b/src/main/scala/org/graphframes/lib/TriangleCount.scala
@@ -68,7 +68,7 @@ private object TriangleCount {
     val v = graph.vertices
     val countsCol = when(col("count").isNull, 0L).otherwise(col("count"))
     val newV = v.join(triangleCounts, v(ID) === triangleCounts(ID), "left_outer")
-      .select(countsCol.as(COUNT_ID) +: v.columns.map(v.apply) :_ *)
+      .select((countsCol.as(COUNT_ID) +: v.columns.map(v.apply)).toSeq: _*)
     newV
   }