Hi,
I've a `no space left on device` exception when pulling some 22GB data from
s3 block storage to the ephemeral HDFS. The cluster is on EC2 using
spark-ec2 script with 4 m1.large.
The code is basically:
val in = sc.textFile("s3://...")
in.saveAsTextFile("hdfs://...")
Spark creates 750 input partitions based on the input splits, when it
begins throwing this exception, there's no space left on the root file
system on some worker machine:
Filesystem 1K-blocks Used Available Use% Mounted on
/dev/xvda1 8256952 8256952 0 100% /
tmpfs 3816808 0 3816808 0% /dev/shm
/dev/xvdb 433455904 29840684 381596916 8% /mnt
/dev/xvdf 433455904 29437000 382000600 8% /mnt2
Before the job begins, only 35% is used.
Filesystem 1K-blocks Used Available Use% Mounted on
/dev/xvda1 8256952 2832256 5340840 35% /
tmpfs 3816808 0 3816808 0% /dev/shm
/dev/xvdb 433455904 29857768 381579832 8% /mnt
/dev/xvdf 433455904 29470104 381967496 8% /mnt2
Some suggestions on this problem? Does Spark caches/stores some data before
writing to HDFS?
Full stacktrace:
---------------------
java.io.IOException: No space left on device
at java.io.FileOutputStream.writeBytes(Native Method)
at java.io.FileOutputStream.write(FileOutputStream.java:345)
at java.io.BufferedOutputStream.write(BufferedOutputStream.java:122)
at
org.apache.hadoop.fs.s3.Jets3tFileSystemStore.retrieveBlock(Jets3tFileSystemStore.java:210)
at sun.reflect.GeneratedMethodAccessor5.invoke(Unknown Source)
at
sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at
org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:82)
at
org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:59)
at com.sun.proxy.$Proxy8.retrieveBlock(Unknown Source)
at org.apache.hadoop.fs.s3.S3InputStream.blockSeekTo(S3InputStream.java:160)
at org.apache.hadoop.fs.s3.S3InputStream.read(S3InputStream.java:119)
at java.io.DataInputStream.read(DataInputStream.java:100)
at org.apache.hadoop.util.LineReader.readLine(LineReader.java:134)
at
org.apache.hadoop.mapred.LineRecordReader.<init>(LineRecordReader.java:92)
at
org.apache.hadoop.mapred.TextInputFormat.getRecordReader(TextInputFormat.java:51)
at org.apache.spark.rdd.HadoopRDD$$anon$1.<init>(HadoopRDD.scala:156)
at org.apache.spark.rdd.HadoopRDD.compute(HadoopRDD.scala:149)
at org.apache.spark.rdd.HadoopRDD.compute(HadoopRDD.scala:64)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:241)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:232)
at org.apache.spark.rdd.MappedRDD.compute(MappedRDD.scala:31)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:241)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:232)
at org.apache.spark.rdd.MappedRDD.compute(MappedRDD.scala:31)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:241)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:232)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:109)
at org.apache.spark.scheduler.Task.run(Task.scala:53)
at
org.apache.spark.executor.Executor$TaskRunner$$anonfun$run$1.apply$mcV$sp(Executor.scala:213)
at
org.apache.spark.deploy.SparkHadoopUtil.runAsUser(SparkHadoopUtil.scala:49)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:178)
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:744)
--
*JU Han*
Data Engineer @ Botify.com
+33 0619608888
