How big do you expect the file to be? Spark has issues with single blocks over 2GB (see https://issues.apache.org/jira/browse/SPARK-1476 and https://issues.apache.org/jira/browse/SPARK-6235 for example)
If you don’t know, try running df.repartition(100).write.format… to get an idea of how big it would be, I assume it’s over 2 GB From: Zhang, Jingyu [mailto:jingyu.zh...@news.com.au] Sent: 16 November 2015 10:17 To: user <user@spark.apache.org> Subject: Size exceeds Integer.MAX_VALUE on EMR 4.0.0 Spark 1.4.1 I am using spark-csv to save files in s3, it shown Size exceeds. Please let me know how to fix it. Thanks. df.write() .format("com.databricks.spark.csv") .option("header", "true") .save("s3://newcars.csv"); java.lang.IllegalArgumentException: Size exceeds Integer.MAX_VALUE at sun.nio.ch.FileChannelImpl.map(FileChannelImpl.java:860) at org.apache.spark.storage.DiskStore$$anonfun$getBytes$2.apply(DiskStore.scala:125) at org.apache.spark.storage.DiskStore$$anonfun$getBytes$2.apply(DiskStore.scala:113) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1285) at org.apache.spark.storage.DiskStore.getBytes(DiskStore.scala:127) at org.apache.spark.storage.DiskStore.getBytes(DiskStore.scala:134) at org.apache.spark.storage.BlockManager.doGetLocal(BlockManager.scala:511) at org.apache.spark.storage.BlockManager.getLocal(BlockManager.scala:429) at org.apache.spark.storage.BlockManager.get(BlockManager.scala:617) at org.apache.spark.CacheManager.putInBlockManager(CacheManager.scala:154) at org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:78) at org.apache.spark.rdd.RDD.iterator(RDD.scala:242) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277) at org.apache.spark.rdd.RDD.iterator(RDD.scala:244) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277) at org.apache.spark.rdd.RDD.iterator(RDD.scala:244) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277) at org.apache.spark.rdd.RDD.iterator(RDD.scala:244) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277) at org.apache.spark.rdd.RDD.iterator(RDD.scala:244) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277) at org.apache.spark.rdd.RDD.iterator(RDD.scala:244) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:70) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41) at org.apache.spark.scheduler.Task.run(Task.scala:70) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615) at java.lang.Thread.run(Thread.java:745) This message and its attachments may contain legally privileged or confidential information. It is intended solely for the named addressee. If you are not the addressee indicated in this message or responsible for delivery of the message to the addressee, you may not copy or deliver this message or its attachments to anyone. Rather, you should permanently delete this message and its attachments and kindly notify the sender by reply e-mail. Any content of this message and its attachments which does not relate to the official business of the sending company must be taken not to have been sent or endorsed by that company or any of its related entities. No warranty is made that the e-mail or attachments are free from computer virus or other defect.
