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我使用boto3从S3读取文件，这表明它比sc.textFile(...)快得多。这些文件大约在300MB到1GB之间。这个过程是这样：PySpark在使用boto3读取大文件时抛出java.io.EOFException
data = sc.parallelize(list_of_files, numSlices=n_partitions) \
.flatMap(read_from_s3_and_split_lines)
events = data.aggregateByKey(...)
当运行这个过程中，我得到异常：
15/12/04 10:58:00 WARN TaskSetManager: Lost task 41.3 in stage 0.0 (TID 68, 10.83.25.233): org.apache.spark.SparkException: Python worker exited unexpectedly (crashed)
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:203)
at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:207)
at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:125)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:70)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:300)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
at org.apache.spark.api.python.PairwiseRDD.compute(PythonRDD.scala:342)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:300)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:88)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.io.EOFException
at java.io.DataInputStream.readInt(DataInputStream.java:392)
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:139)
... 15 more
很多时候，只是一些任务崩盘和工作能够恢复。但是，有些时候整个工作会在发生这些错误之后崩溃。我一直无法找到这个问题的根源，并且似乎根据我阅读的文件数量，我应用的确切转换次数出现和消失......读取单个文件时它永远不会失败。