Spark GraphX：要求失败：初始容量无效
Spark GraphX : requirement failed: Invalid initial capacity
我是 Spark、Scala 的新手。
我正在尝试在此数据集中执行三角形计数：DataSet
对于业余爱好项目
这是我到目前为止编写的代码：
import org.apache.spark.SparkConf
import org.apache.spark.SparkContext
import org.apache.spark.graphx.Edge
import org.apache.spark.graphx.Graph
import org.apache.spark.graphx.Graph.graphToGraphOps
import org.apache.spark.graphx.PartitionStrategy
import org.apache.spark.rdd.RDD
import org.apache.spark.rdd.RDD.rddToPairRDDFunctions
object GraphXApps {
def main(args: Array[String]): Unit = {
val conf = new SparkConf()
.setAppName("GraphXApps")
.setSparkHome(System.getenv("SPARK_HOME"))
.setJars(SparkContext.jarOfClass(this.getClass).toList)
val sc = new SparkContext(conf)
// Load the edges in canonical order and partition the graph for triangle count
val edges: RDD[Edge[String]] =
sc.textFile(args(0)).map { line =>
val fields = line.split("\t")
Edge(fields(0).toLong, fields(1).toLong)
}
val graph : Graph[String, String] = Graph.fromEdges(edges.sortBy(_.srcId, ascending = true, 1), "defaultProperty").partitionBy(PartitionStrategy.RandomVertexCut)
// Find the triangle count for each vertex
val triCounts = graph.triangleCount().vertices
val triCountById = graph.vertices.join(triCounts).map(_._2._2)
// Print the result
println(triCountById.collect().mkString("\n"))
sc.stop()
}
}
但我收到此错误：java.lang.IllegalArgumentException：要求失败：初始容量无效
请让我知道哪里出错了。这真的很有帮助。
完整堆栈跟踪
16/10/31 01:03:08 ERROR TaskSetManager: Task 0 in stage 8.0 failed 1 times; aborting job
16/10/31 01:03:08 INFO TaskSchedulerImpl: Removed TaskSet 8.0, whose tasks have all completed, from pool
16/10/31 01:03:08 INFO TaskSchedulerImpl: Cancelling stage 8
16/10/31 01:03:08 INFO DAGScheduler: ShuffleMapStage 8 (mapPartitions at VertexRDDImpl.scala:245) failed in 0.131 s
16/10/31 01:03:08 INFO DAGScheduler: Job 0 failed: collect at GraphXApps.scala:47, took 3.128921 s
Exception in thread "main" org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 8.0 failed 1 times, most recent failure: Lost task 0.0 in stage 8.0 (TID 8, localhost): java.lang.IllegalArgumentException: requirement failed: Invalid initial capacity
at scala.Predef$.require(Predef.scala:224)
at org.apache.spark.util.collection.OpenHashSet$mcJ$sp.<init>(OpenHashSet.scala:51)
at org.apache.spark.util.collection.OpenHashSet$mcJ$sp.<init>(OpenHashSet.scala:57)
at org.apache.spark.graphx.lib.TriangleCount$$anonfun.apply(TriangleCount.scala:70)
at org.apache.spark.graphx.lib.TriangleCount$$anonfun.apply(TriangleCount.scala:69)
at org.apache.spark.graphx.impl.VertexPartitionBaseOps.map(VertexPartitionBaseOps.scala:61)
at org.apache.spark.graphx.impl.VertexRDDImpl$$anonfun$mapValues.apply(VertexRDDImpl.scala:102)
at org.apache.spark.graphx.impl.VertexRDDImpl$$anonfun$mapValues.apply(VertexRDDImpl.scala:102)
at scala.collection.Iterator$$anon.next(Iterator.scala:409)
at org.apache.spark.graphx.impl.VertexRDDImpl$$anonfun.apply(VertexRDDImpl.scala:156)
at org.apache.spark.graphx.impl.VertexRDDImpl$$anonfun.apply(VertexRDDImpl.scala:154)
at org.apache.spark.rdd.ZippedPartitionsRDD2.compute(ZippedPartitionsRDD.scala:89)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD$$anonfun.apply(RDD.scala:332)
at org.apache.spark.rdd.RDD$$anonfun.apply(RDD.scala:330)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator.apply(BlockManager.scala:919)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator.apply(BlockManager.scala:910)
at org.apache.spark.storage.BlockManager.doPut(BlockManager.scala:866)
at org.apache.spark.storage.BlockManager.doPutIterator(BlockManager.scala:910)
at org.apache.spark.storage.BlockManager.getOrElseUpdate(BlockManager.scala:668)
at org.apache.spark.rdd.RDD.getOrCompute(RDD.scala:330)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:281)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:79)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:47)
at org.apache.spark.scheduler.Task.run(Task.scala:85)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1450)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage.apply(DAGScheduler.scala:1438)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage.apply(DAGScheduler.scala:1437)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1437)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed.apply(DAGScheduler.scala:811)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed.apply(DAGScheduler.scala:811)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:811)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1659)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1618)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1607)
at org.apache.spark.util.EventLoop$$anon.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:632)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1871)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1884)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1897)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1911)
at org.apache.spark.rdd.RDD$$anonfun$collect.apply(RDD.scala:893)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:358)
at org.apache.spark.rdd.RDD.collect(RDD.scala:892)
at GraphXApps$.main(GraphXApps.scala:47)
at GraphXApps.main(GraphXApps.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:729)
at org.apache.spark.deploy.SparkSubmit$.doRunMain(SparkSubmit.scala:185)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:210)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:124)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: java.lang.IllegalArgumentException: requirement failed: Invalid initial capacity
at scala.Predef$.require(Predef.scala:224)
at org.apache.spark.util.collection.OpenHashSet$mcJ$sp.<init>(OpenHashSet.scala:51)
at org.apache.spark.util.collection.OpenHashSet$mcJ$sp.<init>(OpenHashSet.scala:57)
at org.apache.spark.graphx.lib.TriangleCount$$anonfun.apply(TriangleCount.scala:70)
at org.apache.spark.graphx.lib.TriangleCount$$anonfun.apply(TriangleCount.scala:69)
at org.apache.spark.graphx.impl.VertexPartitionBaseOps.map(VertexPartitionBaseOps.scala:61)
at org.apache.spark.graphx.impl.VertexRDDImpl$$anonfun$mapValues.apply(VertexRDDImpl.scala:102)
at org.apache.spark.graphx.impl.VertexRDDImpl$$anonfun$mapValues.apply(VertexRDDImpl.scala:102)
at scala.collection.Iterator$$anon.next(Iterator.scala:409)
at org.apache.spark.graphx.impl.VertexRDDImpl$$anonfun.apply(VertexRDDImpl.scala:156)
at org.apache.spark.graphx.impl.VertexRDDImpl$$anonfun.apply(VertexRDDImpl.scala:154)
at org.apache.spark.rdd.ZippedPartitionsRDD2.compute(ZippedPartitionsRDD.scala:89)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD$$anonfun.apply(RDD.scala:332)
at org.apache.spark.rdd.RDD$$anonfun.apply(RDD.scala:330)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator.apply(BlockManager.scala:919)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator.apply(BlockManager.scala:910)
at org.apache.spark.storage.BlockManager.doPut(BlockManager.scala:866)
at org.apache.spark.storage.BlockManager.doPutIterator(BlockManager.scala:910)
at org.apache.spark.storage.BlockManager.getOrElseUpdate(BlockManager.scala:668)
at org.apache.spark.rdd.RDD.getOrCompute(RDD.scala:330)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:281)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:79)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:47)
at org.apache.spark.scheduler.Task.run(Task.scala:85)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
这似乎是 Spark 2.0 中的一个错误（到目前为止，已针对 2.0、2.0.1 和 2.0.2 对此进行了测试）。 Jira [SPARK-18200]: GraphX Invalid initial capacity when running triangleCount 的创建就是为了解决这个问题。
如链接 notebook 中所述，您的代码应该可以与 Spark 1.6 一起工作。
但是正如您所指出的，它在 Spark 2.0 中失败了，如链接中所述 notebook。
在此期间，请尝试使用 Spark 1.6 或尝试使用 GraphFrames，如链接 notebook 中所述。
HTH！
我是 Spark、Scala 的新手。
我正在尝试在此数据集中执行三角形计数：DataSet
对于业余爱好项目
这是我到目前为止编写的代码：
import org.apache.spark.SparkConf
import org.apache.spark.SparkContext
import org.apache.spark.graphx.Edge
import org.apache.spark.graphx.Graph
import org.apache.spark.graphx.Graph.graphToGraphOps
import org.apache.spark.graphx.PartitionStrategy
import org.apache.spark.rdd.RDD
import org.apache.spark.rdd.RDD.rddToPairRDDFunctions
object GraphXApps {
def main(args: Array[String]): Unit = {
val conf = new SparkConf()
.setAppName("GraphXApps")
.setSparkHome(System.getenv("SPARK_HOME"))
.setJars(SparkContext.jarOfClass(this.getClass).toList)
val sc = new SparkContext(conf)
// Load the edges in canonical order and partition the graph for triangle count
val edges: RDD[Edge[String]] =
sc.textFile(args(0)).map { line =>
val fields = line.split("\t")
Edge(fields(0).toLong, fields(1).toLong)
}
val graph : Graph[String, String] = Graph.fromEdges(edges.sortBy(_.srcId, ascending = true, 1), "defaultProperty").partitionBy(PartitionStrategy.RandomVertexCut)
// Find the triangle count for each vertex
val triCounts = graph.triangleCount().vertices
val triCountById = graph.vertices.join(triCounts).map(_._2._2)
// Print the result
println(triCountById.collect().mkString("\n"))
sc.stop()
}
}
但我收到此错误：java.lang.IllegalArgumentException：要求失败：初始容量无效
请让我知道哪里出错了。这真的很有帮助。
完整堆栈跟踪
16/10/31 01:03:08 ERROR TaskSetManager: Task 0 in stage 8.0 failed 1 times; aborting job
16/10/31 01:03:08 INFO TaskSchedulerImpl: Removed TaskSet 8.0, whose tasks have all completed, from pool
16/10/31 01:03:08 INFO TaskSchedulerImpl: Cancelling stage 8
16/10/31 01:03:08 INFO DAGScheduler: ShuffleMapStage 8 (mapPartitions at VertexRDDImpl.scala:245) failed in 0.131 s
16/10/31 01:03:08 INFO DAGScheduler: Job 0 failed: collect at GraphXApps.scala:47, took 3.128921 s
Exception in thread "main" org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 8.0 failed 1 times, most recent failure: Lost task 0.0 in stage 8.0 (TID 8, localhost): java.lang.IllegalArgumentException: requirement failed: Invalid initial capacity
at scala.Predef$.require(Predef.scala:224)
at org.apache.spark.util.collection.OpenHashSet$mcJ$sp.<init>(OpenHashSet.scala:51)
at org.apache.spark.util.collection.OpenHashSet$mcJ$sp.<init>(OpenHashSet.scala:57)
at org.apache.spark.graphx.lib.TriangleCount$$anonfun.apply(TriangleCount.scala:70)
at org.apache.spark.graphx.lib.TriangleCount$$anonfun.apply(TriangleCount.scala:69)
at org.apache.spark.graphx.impl.VertexPartitionBaseOps.map(VertexPartitionBaseOps.scala:61)
at org.apache.spark.graphx.impl.VertexRDDImpl$$anonfun$mapValues.apply(VertexRDDImpl.scala:102)
at org.apache.spark.graphx.impl.VertexRDDImpl$$anonfun$mapValues.apply(VertexRDDImpl.scala:102)
at scala.collection.Iterator$$anon.next(Iterator.scala:409)
at org.apache.spark.graphx.impl.VertexRDDImpl$$anonfun.apply(VertexRDDImpl.scala:156)
at org.apache.spark.graphx.impl.VertexRDDImpl$$anonfun.apply(VertexRDDImpl.scala:154)
at org.apache.spark.rdd.ZippedPartitionsRDD2.compute(ZippedPartitionsRDD.scala:89)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD$$anonfun.apply(RDD.scala:332)
at org.apache.spark.rdd.RDD$$anonfun.apply(RDD.scala:330)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator.apply(BlockManager.scala:919)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator.apply(BlockManager.scala:910)
at org.apache.spark.storage.BlockManager.doPut(BlockManager.scala:866)
at org.apache.spark.storage.BlockManager.doPutIterator(BlockManager.scala:910)
at org.apache.spark.storage.BlockManager.getOrElseUpdate(BlockManager.scala:668)
at org.apache.spark.rdd.RDD.getOrCompute(RDD.scala:330)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:281)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:79)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:47)
at org.apache.spark.scheduler.Task.run(Task.scala:85)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1450)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage.apply(DAGScheduler.scala:1438)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage.apply(DAGScheduler.scala:1437)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1437)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed.apply(DAGScheduler.scala:811)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed.apply(DAGScheduler.scala:811)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:811)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1659)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1618)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1607)
at org.apache.spark.util.EventLoop$$anon.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:632)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1871)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1884)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1897)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1911)
at org.apache.spark.rdd.RDD$$anonfun$collect.apply(RDD.scala:893)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:358)
at org.apache.spark.rdd.RDD.collect(RDD.scala:892)
at GraphXApps$.main(GraphXApps.scala:47)
at GraphXApps.main(GraphXApps.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:729)
at org.apache.spark.deploy.SparkSubmit$.doRunMain(SparkSubmit.scala:185)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:210)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:124)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: java.lang.IllegalArgumentException: requirement failed: Invalid initial capacity
at scala.Predef$.require(Predef.scala:224)
at org.apache.spark.util.collection.OpenHashSet$mcJ$sp.<init>(OpenHashSet.scala:51)
at org.apache.spark.util.collection.OpenHashSet$mcJ$sp.<init>(OpenHashSet.scala:57)
at org.apache.spark.graphx.lib.TriangleCount$$anonfun.apply(TriangleCount.scala:70)
at org.apache.spark.graphx.lib.TriangleCount$$anonfun.apply(TriangleCount.scala:69)
at org.apache.spark.graphx.impl.VertexPartitionBaseOps.map(VertexPartitionBaseOps.scala:61)
at org.apache.spark.graphx.impl.VertexRDDImpl$$anonfun$mapValues.apply(VertexRDDImpl.scala:102)
at org.apache.spark.graphx.impl.VertexRDDImpl$$anonfun$mapValues.apply(VertexRDDImpl.scala:102)
at scala.collection.Iterator$$anon.next(Iterator.scala:409)
at org.apache.spark.graphx.impl.VertexRDDImpl$$anonfun.apply(VertexRDDImpl.scala:156)
at org.apache.spark.graphx.impl.VertexRDDImpl$$anonfun.apply(VertexRDDImpl.scala:154)
at org.apache.spark.rdd.ZippedPartitionsRDD2.compute(ZippedPartitionsRDD.scala:89)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD$$anonfun.apply(RDD.scala:332)
at org.apache.spark.rdd.RDD$$anonfun.apply(RDD.scala:330)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator.apply(BlockManager.scala:919)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator.apply(BlockManager.scala:910)
at org.apache.spark.storage.BlockManager.doPut(BlockManager.scala:866)
at org.apache.spark.storage.BlockManager.doPutIterator(BlockManager.scala:910)
at org.apache.spark.storage.BlockManager.getOrElseUpdate(BlockManager.scala:668)
at org.apache.spark.rdd.RDD.getOrCompute(RDD.scala:330)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:281)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:79)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:47)
at org.apache.spark.scheduler.Task.run(Task.scala:85)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
这似乎是 Spark 2.0 中的一个错误（到目前为止，已针对 2.0、2.0.1 和 2.0.2 对此进行了测试）。 Jira [SPARK-18200]: GraphX Invalid initial capacity when running triangleCount 的创建就是为了解决这个问题。
如链接 notebook 中所述，您的代码应该可以与 Spark 1.6 一起工作。
但是正如您所指出的，它在 Spark 2.0 中失败了，如链接中所述 notebook。
在此期间，请尝试使用 Spark 1.6 或尝试使用 GraphFrames，如链接 notebook 中所述。
HTH！