场景：在gremlin终端中通过Hadoop-gremlin批量导入生成json，
graph = GraphFactory.open('data/zl/hadoop-load-company-modern.properties')
blvp = BulkLoaderVertexProgram.build().bulkLoader(OneTimeBulkLoader).writeGraph('data/zl/company-hbase-es.properties').create(graph)
graph.compute(SparkGraphComputer).program(blvp).submit().get()
出现了如下错误：
Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 5.0 failed 1 times, most recent failure: Lost task 0.0 in stage 5.0 (TID 3, localhost): java.util.NoSuchElementException
at org.apache.tinkerpop.gremlin.process.traversal.util.DefaultTraversal.next(DefaultTraversal.java:204)
at org.apache.tinkerpop.gremlin.process.computer.bulkloading.BulkLoader.getVertexById(BulkLoader.java:116)
at org.apache.tinkerpop.gremlin.process.computer.bulkloading.BulkLoaderVertexProgram.lambda$executeInternal$4(BulkLoaderVertexProgram.java:251)
at java.util.Iterator.forEachRemaining(Unknown Source)
at org.apache.tinkerpop.gremlin.process.computer.bulkloading.BulkLoaderVertexProgram.executeInternal(BulkLoaderVertexProgram.java:249)
at org.apache.tinkerpop.gremlin.process.computer.bulkloading.BulkLoaderVertexProgram.execute(BulkLoaderVertexProgram.java:197)
at org.apache.tinkerpop.gremlin.spark.process.computer.SparkExecutor.lambda$null$5(SparkExecutor.java:118)
at org.apache.tinkerpop.gremlin.util.iterator.IteratorUtils$3.next(IteratorUtils.java:247)
at scala.collection.convert.Wrappers$JIteratorWrapper.next(Wrappers.scala:43)
at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:462)
at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:439)
at org.apache.spark.util.collection.ExternalSorter.insertAll(ExternalSorter.scala:189)
at org.apache.spark.shuffle.sort.SortShuffleWriter.write(SortShuffleWriter.scala:64)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:227)
at java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source)
at java.lang.Thread.run(Unknown Source)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1431)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1419)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1418)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1418)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:799)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:799)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:799)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1640)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1599)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1588)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:620)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1832)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1845)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1858)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1929)
at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1.apply(RDD.scala:920)
at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1.apply(RDD.scala:918)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:111)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:316)
at org.apache.spark.rdd.RDD.foreachPartition(RDD.scala:918)
at org.apache.spark.api.java.JavaRDDLike$class.foreachPartition(JavaRDDLike.scala:225)
at org.apache.spark.api.java.AbstractJavaRDDLike.foreachPartition(JavaRDDLike.scala:46)
at org.apache.tinkerpop.gremlin.spark.process.computer.SparkExecutor.executeVertexProgramIteration(SparkExecutor.java:179)
at org.apache.tinkerpop.gremlin.spark.process.computer.SparkGraphComputer.lambda$submitWithExecutor$0(SparkGraphComputer.java:279)
at java.util.concurrent.FutureTask.run(Unknown Source)
at java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source)
at java.lang.Thread.run(Unknown Source)
Caused by: java.util.NoSuchElementException
at org.apache.tinkerpop.gremlin.process.traversal.util.DefaultTraversal.next(DefaultTraversal.java:204)
at org.apache.tinkerpop.gremlin.process.computer.bulkloading.BulkLoader.getVertexById(BulkLoader.java:116)
at org.apache.tinkerpop.gremlin.process.computer.bulkloading.BulkLoaderVertexProgram.lambda$executeInternal$4(BulkLoaderVertexProgram.java:251)
at java.util.Iterator.forEachRemaining(Unknown Source)
at org.apache.tinkerpop.gremlin.process.computer.bulkloading.BulkLoaderVertexProgram.executeInternal(BulkLoaderVertexProgram.java:249)
at org.apache.tinkerpop.gremlin.process.computer.bulkloading.BulkLoaderVertexProgram.execute(BulkLoaderVertexProgram.java:197)
at org.apache.tinkerpop.gremlin.spark.process.computer.SparkExecutor.lambda$null$5(SparkExecutor.java:118)
at org.apache.tinkerpop.gremlin.util.iterator.IteratorUtils$3.next(IteratorUtils.java:247)
at scala.collection.convert.Wrappers$JIteratorWrapper.next(Wrappers.scala:43)
at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:462)
at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:439)
at org.apache.spark.util.collection.ExternalSorter.insertAll(ExternalSorter.scala:189)
at org.apache.spark.shuffle.sort.SortShuffleWriter.write(SortShuffleWriter.scala:64)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:227)
... 3 more
问题是java.util.NoSuchElementException，但是这个问题很不明确，我想知道更具体的错误，比如是json文件中的那条记录产生了这个影响等。
解决：让其打印更详细的信息
由上面错误知道在调用at org.apache.tinkerpop.gremlin.process.traversal.util.DefaultTraversal.next方法时出现了NoSuchElementException异常
经过查询知道org.apache.tinkerpop.gremlin.process.traversal.util.DefaultTraversal是gremlin-core-x.x.x.jar包中的类。
通过修改gremlin-core-xxx模块，在合适的方法处让其打印更详细的日志信息。
gremlin-core是tinkerpop项目中的一个模块，所以git clone https://github.com/apache/tinkerpop.git 修改gremlin-core模块，让其打印更详细信息。
最后将编译好的gremlin-core-x.x.x.jar替换掉janusgraph-0.2.0-hadoop2\lib目录中的版本
最后错误如下，让其打印出了顶点id边等信息，
16:13:27 ERROR org.apache.tinkerpop.gremlin.process.computer.bulkloading.BulkLoaderVertexProgram - ▒▒▒▒▒▒▒:sourceVertex=v[eefbad45-a079-4883-b936-42817618f094]edge=e[e4d13af5-ff29-4646-a06d-9ee20cfe8f8e][eefbad45-a079-4883-b936-42817618f094-class_staff_2_staff->82e1e894-3abc-41e5-ba16-7bba53a7df67]
16:13:27 ERROR org.apache.spark.executor.Executor - Managed memory leak detected; size = 5309058 bytes, TID = 3
16:13:27 ERROR org.apache.spark.executor.Executor - Exception in task 0.0 in stage 5.0 (TID 3)
java.util.NoSuchElementException
at org.apache.tinkerpop.gremlin.process.traversal.util.DefaultTraversal.next(DefaultTraversal.java:204)
at org.apache.tinkerpop.gremlin.process.computer.bulkloading.BulkLoader.getVertexById(BulkLoader.java:116)
at org.apache.tinkerpop.gremlin.process.computer.bulkloading.BulkLoaderVertexProgram.lambda$executeInternal$4(BulkLoaderVertexProgram.java:255)
at java.util.Iterator.forEachRemaining(Unknown Source)
- 经查看json文件，82e1e894-3abc-41e5-ba16-7bba53a7df67顶点的json数据和前一条数据并排放了，而导入的json文件中的json数据必须是一个顶点数据的json占一行。
结论
- json文件数据格式有误产生的，一个顶点的json数据应该占用一行，而不是并排放置。）
- 最后产生错误的原因很简单，但是找错却比较费事，其实针对上面这个问题，在知道json格式应该是单行显示情况下，通过上面的错误提示，采用小黄鸭调试法应该就能找出原因的，但是，桌子上没有小黄鸭！！！