Modified version of GraphLoader for Spark 1.0 that allows setting the edge storage level

MyGraphLoader.scala

package org.apache.spark.graphx

import org.apache.spark.{Logging, SparkContext}
import org.apache.spark.graphx.impl.{EdgePartitionBuilder, GraphImpl}
import org.apache.spark.storage.StorageLevel

object MyGraphLoader extends Logging {
  def edgeListFile(
      sc: SparkContext,
      path: String,
      canonicalOrientation: Boolean = false,
      minEdgePartitions: Int = 1,
      storageLevel: StorageLevel = StorageLevel.MEMORY_ONLY)
    : Graph[Int, Int] = {
    val startTime = System.currentTimeMillis

    // Parse the edge data table directly into edge partitions
    val lines = sc.textFile(path, minEdgePartitions).coalesce(minEdgePartitions)
    val edges = lines.mapPartitionsWithIndex { (pid, iter) =>
      val builder = new EdgePartitionBuilder[Int, Int]
      iter.foreach { line =>
        if (!line.isEmpty && line(0) != '#') {
          val lineArray = line.split("\\s+")
          if (lineArray.length < 2) {
            logWarning("Invalid line: " + line)
          }
          val srcId = lineArray(0).toLong
          val dstId = lineArray(1).toLong
          if (canonicalOrientation && srcId > dstId) {
            builder.add(dstId, srcId, 1)
          } else {
            builder.add(srcId, dstId, 1)
          }
        }
      }
      Iterator((pid, builder.toEdgePartition))
    }.persist(storageLevel)
    edges.count()

    logInfo("It took %d ms to load the edges".format(System.currentTimeMillis - startTime))

    val edgeRDD = new EdgeRDD(edges)
    val vertexRDD = VertexRDD.fromEdges(edgeRDD, edgeRDD.partitions.size, defaultVal = 1)

    GraphImpl.fromExistingRDDs(vertexRDD, edgeRDD)
  }
}