Re: Saving calculation to single local file
Another option is merge partfiles after your app ends.
On 5 Jun 2015 20:37, Akhil Das ak...@sigmoidanalytics.com wrote:
you can simply do rdd.repartition(1).saveAsTextFile(...), it might not be
efficient if your output data is huge since one task will be doing the
whole writing.
Thanks
Best Regards
On Fri, Jun 5, 2015 at 3:46 PM, marcos rebelo ole...@gmail.com wrote:
Hi all
I'm running spark in a single local machine, no hadoop, just reading and
writing in local disk.
I need to have a single file as output of my calculation.
if I do rdd.saveAsTextFile(...) all runs ok but I get allot of files.
Since I need a single file I was considering to do something like:
Try {new FileWriter(outputPath)} match {
case Success(writer) =
try {
rdd.toLocalIterator.foreach({line =
val str = line.toString
writer.write(str)
}
}
}
...
}
I get:
[error] o.a.s.e.Executor - Exception in task 0.0 in stage 41.0 (TID 32)
java.lang.OutOfMemoryError: Java heap space
at java.util.Arrays.copyOf(Arrays.java:3236) ~[na:1.8.0_45]
at java.io.ByteArrayOutputStream.grow(ByteArrayOutputStream.java:118)
~[na:1.8.0_45]
at
java.io.ByteArrayOutputStream.ensureCapacity(ByteArrayOutputStream.java:93)
~[na:1.8.0_45]
at
java.io.ByteArrayOutputStream.write(ByteArrayOutputStream.java:153)
~[na:1.8.0_45]
at
java.io.ObjectOutputStream$BlockDataOutputStream.drain(ObjectOutputStream.java:1877)
~[na:1.8.0_45]
[error] o.a.s.u.SparkUncaughtExceptionHandler - Uncaught exception in
thread Thread[Executor task launch worker-1,5,main]
java.lang.OutOfMemoryError: Java heap space
at java.util.Arrays.copyOf(Arrays.java:3236) ~[na:1.8.0_45]
at java.io.ByteArrayOutputStream.grow(ByteArrayOutputStream.java:118)
~[na:1.8.0_45]
at
java.io.ByteArrayOutputStream.ensureCapacity(ByteArrayOutputStream.java:93)
~[na:1.8.0_45]
at
java.io.ByteArrayOutputStream.write(ByteArrayOutputStream.java:153)
~[na:1.8.0_45]
at
java.io.ObjectOutputStream$BlockDataOutputStream.drain(ObjectOutputStream.java:1877)
~[na:1.8.0_45]
[error] o.a.s.s.TaskSetManager - Task 0 in stage 41.0 failed 1 times;
aborting job
[warn] application - Can't write to /tmp/err1433498283479.csv: {}
org.apache.spark.SparkException: Job aborted due to stage failure: Task 0
in stage 41.0 failed 1 times, most recent failure: Lost task 0.0 in stage
41.0 (TID 32, localhost): java.lang.OutOfMemoryError: Java heap space
at java.util.Arrays.copyOf(Arrays.java:3236)
at java.io.ByteArrayOutputStream.grow(ByteArrayOutputStream.java:118)
at
java.io.ByteArrayOutputStream.ensureCapacity(ByteArrayOutputStream.java:93)
at java.io.ByteArrayOutputStream.write(ByteArrayOutputStream.java:153)
at
java.io.ObjectOutputStream$BlockDataOutputStream.drain(ObjectOutputStream.java:1877)
at
java.io.ObjectOutputStream$BlockDataOutputStream.setBlockDataMode(ObjectOutputStream.java:1786)
at
java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1189)
at java.io.ObjectOutputStream.writeObject(ObjectOutputStream.java:348)
at
org.apache.spark.serializer.JavaSerializationStream.writeObject(JavaSerializer.scala:44)
at
org.apache.spark.serializer.JavaSerializerInstance.serialize(JavaSerializer.scala:80)
at
org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at
java.util.concurrent.ThreadPoolExecutor$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$$failJobAndIndependentStages(DAGScheduler.scala:1204)
~[spark-core_2.10-1.3.1.jar:1.3.1]
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1193)
~[spark-core_2.10-1.3.1.jar:1.3.1]
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1192)
~[spark-core_2.10-1.3.1.jar:1.3.1]
at
scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
~[scala-library-2.10.5.jar:na]
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
~[scala-library-2.10.5.jar:na]
if this rdd.toLocalIterator.foreach(...) doesn't work, what is the better
solution?
Best Regards
Marcos
Saving calculation to single local file
Hi all
I'm running spark in a single local machine, no hadoop, just reading and
writing in local disk.
I need to have a single file as output of my calculation.
if I do rdd.saveAsTextFile(...) all runs ok but I get allot of files.
Since I need a single file I was considering to do something like:
Try {new FileWriter(outputPath)} match {
case Success(writer) =
try {
rdd.toLocalIterator.foreach({line =
val str = line.toString
writer.write(str)
}
}
}
...
}
I get:
[error] o.a.s.e.Executor - Exception in task 0.0 in stage 41.0 (TID 32)
java.lang.OutOfMemoryError: Java heap space
at java.util.Arrays.copyOf(Arrays.java:3236) ~[na:1.8.0_45]
at java.io.ByteArrayOutputStream.grow(ByteArrayOutputStream.java:118)
~[na:1.8.0_45]
at
java.io.ByteArrayOutputStream.ensureCapacity(ByteArrayOutputStream.java:93)
~[na:1.8.0_45]
at java.io.ByteArrayOutputStream.write(ByteArrayOutputStream.java:153)
~[na:1.8.0_45]
at
java.io.ObjectOutputStream$BlockDataOutputStream.drain(ObjectOutputStream.java:1877)
~[na:1.8.0_45]
[error] o.a.s.u.SparkUncaughtExceptionHandler - Uncaught exception in
thread Thread[Executor task launch worker-1,5,main]
java.lang.OutOfMemoryError: Java heap space
at java.util.Arrays.copyOf(Arrays.java:3236) ~[na:1.8.0_45]
at java.io.ByteArrayOutputStream.grow(ByteArrayOutputStream.java:118)
~[na:1.8.0_45]
at
java.io.ByteArrayOutputStream.ensureCapacity(ByteArrayOutputStream.java:93)
~[na:1.8.0_45]
at java.io.ByteArrayOutputStream.write(ByteArrayOutputStream.java:153)
~[na:1.8.0_45]
at
java.io.ObjectOutputStream$BlockDataOutputStream.drain(ObjectOutputStream.java:1877)
~[na:1.8.0_45]
[error] o.a.s.s.TaskSetManager - Task 0 in stage 41.0 failed 1 times;
aborting job
[warn] application - Can't write to /tmp/err1433498283479.csv: {}
org.apache.spark.SparkException: Job aborted due to stage failure: Task 0
in stage 41.0 failed 1 times, most recent failure: Lost task 0.0 in stage
41.0 (TID 32, localhost): java.lang.OutOfMemoryError: Java heap space
at java.util.Arrays.copyOf(Arrays.java:3236)
at java.io.ByteArrayOutputStream.grow(ByteArrayOutputStream.java:118)
at
java.io.ByteArrayOutputStream.ensureCapacity(ByteArrayOutputStream.java:93)
at java.io.ByteArrayOutputStream.write(ByteArrayOutputStream.java:153)
at
java.io.ObjectOutputStream$BlockDataOutputStream.drain(ObjectOutputStream.java:1877)
at
java.io.ObjectOutputStream$BlockDataOutputStream.setBlockDataMode(ObjectOutputStream.java:1786)
at java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1189)
at java.io.ObjectOutputStream.writeObject(ObjectOutputStream.java:348)
at
org.apache.spark.serializer.JavaSerializationStream.writeObject(JavaSerializer.scala:44)
at
org.apache.spark.serializer.JavaSerializerInstance.serialize(JavaSerializer.scala:80)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
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:1204)
~[spark-core_2.10-1.3.1.jar:1.3.1]
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1193)
~[spark-core_2.10-1.3.1.jar:1.3.1]
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1192)
~[spark-core_2.10-1.3.1.jar:1.3.1]
at
scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
~[scala-library-2.10.5.jar:na]
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
~[scala-library-2.10.5.jar:na]
if this rdd.toLocalIterator.foreach(...) doesn't work, what is the better
solution?
Best Regards
Marcos
Re: Saving calculation to single local file
Just repartition to 1 partition before writing.
On Fri, Jun 5, 2015 at 3:46 PM, marcos rebelo ole...@gmail.com wrote:
Hi all
I'm running spark in a single local machine, no hadoop, just reading and
writing in local disk.
I need to have a single file as output of my calculation.
if I do rdd.saveAsTextFile(...) all runs ok but I get allot of files.
Since I need a single file I was considering to do something like:
Try {new FileWriter(outputPath)} match {
case Success(writer) =
try {
rdd.toLocalIterator.foreach({line =
val str = line.toString
writer.write(str)
}
}
}
...
}
I get:
[error] o.a.s.e.Executor - Exception in task 0.0 in stage 41.0 (TID 32)
java.lang.OutOfMemoryError: Java heap space
at java.util.Arrays.copyOf(Arrays.java:3236) ~[na:1.8.0_45]
at java.io.ByteArrayOutputStream.grow(ByteArrayOutputStream.java:118)
~[na:1.8.0_45]
at
java.io.ByteArrayOutputStream.ensureCapacity(ByteArrayOutputStream.java:93)
~[na:1.8.0_45]
at java.io.ByteArrayOutputStream.write(ByteArrayOutputStream.java:153)
~[na:1.8.0_45]
at
java.io.ObjectOutputStream$BlockDataOutputStream.drain(ObjectOutputStream.java:1877)
~[na:1.8.0_45]
[error] o.a.s.u.SparkUncaughtExceptionHandler - Uncaught exception in
thread Thread[Executor task launch worker-1,5,main]
java.lang.OutOfMemoryError: Java heap space
at java.util.Arrays.copyOf(Arrays.java:3236) ~[na:1.8.0_45]
at java.io.ByteArrayOutputStream.grow(ByteArrayOutputStream.java:118)
~[na:1.8.0_45]
at
java.io.ByteArrayOutputStream.ensureCapacity(ByteArrayOutputStream.java:93)
~[na:1.8.0_45]
at java.io.ByteArrayOutputStream.write(ByteArrayOutputStream.java:153)
~[na:1.8.0_45]
at
java.io.ObjectOutputStream$BlockDataOutputStream.drain(ObjectOutputStream.java:1877)
~[na:1.8.0_45]
[error] o.a.s.s.TaskSetManager - Task 0 in stage 41.0 failed 1 times;
aborting job
[warn] application - Can't write to /tmp/err1433498283479.csv: {}
org.apache.spark.SparkException: Job aborted due to stage failure: Task 0
in stage 41.0 failed 1 times, most recent failure: Lost task 0.0 in stage
41.0 (TID 32, localhost): java.lang.OutOfMemoryError: Java heap space
at java.util.Arrays.copyOf(Arrays.java:3236)
at java.io.ByteArrayOutputStream.grow(ByteArrayOutputStream.java:118)
at
java.io.ByteArrayOutputStream.ensureCapacity(ByteArrayOutputStream.java:93)
at java.io.ByteArrayOutputStream.write(ByteArrayOutputStream.java:153)
at
java.io.ObjectOutputStream$BlockDataOutputStream.drain(ObjectOutputStream.java:1877)
at
java.io.ObjectOutputStream$BlockDataOutputStream.setBlockDataMode(ObjectOutputStream.java:1786)
at
java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1189)
at java.io.ObjectOutputStream.writeObject(ObjectOutputStream.java:348)
at
org.apache.spark.serializer.JavaSerializationStream.writeObject(JavaSerializer.scala:44)
at
org.apache.spark.serializer.JavaSerializerInstance.serialize(JavaSerializer.scala:80)
at
org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at
java.util.concurrent.ThreadPoolExecutor$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$$failJobAndIndependentStages(DAGScheduler.scala:1204)
~[spark-core_2.10-1.3.1.jar:1.3.1]
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1193)
~[spark-core_2.10-1.3.1.jar:1.3.1]
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1192)
~[spark-core_2.10-1.3.1.jar:1.3.1]
at
scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
~[scala-library-2.10.5.jar:na]
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
~[scala-library-2.10.5.jar:na]
if this rdd.toLocalIterator.foreach(...) doesn't work, what is the better
solution?
Best Regards
Marcos
--
Best Regards,
Ayan Guha
Re: Saving calculation to single local file
you can simply do rdd.repartition(1).saveAsTextFile(...), it might not be
efficient if your output data is huge since one task will be doing the
whole writing.
Thanks
Best Regards
On Fri, Jun 5, 2015 at 3:46 PM, marcos rebelo ole...@gmail.com wrote:
Hi all
I'm running spark in a single local machine, no hadoop, just reading and
writing in local disk.
I need to have a single file as output of my calculation.
if I do rdd.saveAsTextFile(...) all runs ok but I get allot of files.
Since I need a single file I was considering to do something like:
Try {new FileWriter(outputPath)} match {
case Success(writer) =
try {
rdd.toLocalIterator.foreach({line =
val str = line.toString
writer.write(str)
}
}
}
...
}
I get:
[error] o.a.s.e.Executor - Exception in task 0.0 in stage 41.0 (TID 32)
java.lang.OutOfMemoryError: Java heap space
at java.util.Arrays.copyOf(Arrays.java:3236) ~[na:1.8.0_45]
at java.io.ByteArrayOutputStream.grow(ByteArrayOutputStream.java:118)
~[na:1.8.0_45]
at
java.io.ByteArrayOutputStream.ensureCapacity(ByteArrayOutputStream.java:93)
~[na:1.8.0_45]
at java.io.ByteArrayOutputStream.write(ByteArrayOutputStream.java:153)
~[na:1.8.0_45]
at
java.io.ObjectOutputStream$BlockDataOutputStream.drain(ObjectOutputStream.java:1877)
~[na:1.8.0_45]
[error] o.a.s.u.SparkUncaughtExceptionHandler - Uncaught exception in
thread Thread[Executor task launch worker-1,5,main]
java.lang.OutOfMemoryError: Java heap space
at java.util.Arrays.copyOf(Arrays.java:3236) ~[na:1.8.0_45]
at java.io.ByteArrayOutputStream.grow(ByteArrayOutputStream.java:118)
~[na:1.8.0_45]
at
java.io.ByteArrayOutputStream.ensureCapacity(ByteArrayOutputStream.java:93)
~[na:1.8.0_45]
at java.io.ByteArrayOutputStream.write(ByteArrayOutputStream.java:153)
~[na:1.8.0_45]
at
java.io.ObjectOutputStream$BlockDataOutputStream.drain(ObjectOutputStream.java:1877)
~[na:1.8.0_45]
[error] o.a.s.s.TaskSetManager - Task 0 in stage 41.0 failed 1 times;
aborting job
[warn] application - Can't write to /tmp/err1433498283479.csv: {}
org.apache.spark.SparkException: Job aborted due to stage failure: Task 0
in stage 41.0 failed 1 times, most recent failure: Lost task 0.0 in stage
41.0 (TID 32, localhost): java.lang.OutOfMemoryError: Java heap space
at java.util.Arrays.copyOf(Arrays.java:3236)
at java.io.ByteArrayOutputStream.grow(ByteArrayOutputStream.java:118)
at
java.io.ByteArrayOutputStream.ensureCapacity(ByteArrayOutputStream.java:93)
at java.io.ByteArrayOutputStream.write(ByteArrayOutputStream.java:153)
at
java.io.ObjectOutputStream$BlockDataOutputStream.drain(ObjectOutputStream.java:1877)
at
java.io.ObjectOutputStream$BlockDataOutputStream.setBlockDataMode(ObjectOutputStream.java:1786)
at
java.io.ObjectOutputStream.writeObject0(ObjectOutputStream.java:1189)
at java.io.ObjectOutputStream.writeObject(ObjectOutputStream.java:348)
at
org.apache.spark.serializer.JavaSerializationStream.writeObject(JavaSerializer.scala:44)
at
org.apache.spark.serializer.JavaSerializerInstance.serialize(JavaSerializer.scala:80)
at
org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
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:1204)
~[spark-core_2.10-1.3.1.jar:1.3.1]
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1193)
~[spark-core_2.10-1.3.1.jar:1.3.1]
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1192)
~[spark-core_2.10-1.3.1.jar:1.3.1]
at
scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
~[scala-library-2.10.5.jar:na]
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
~[scala-library-2.10.5.jar:na]
if this rdd.toLocalIterator.foreach(...) doesn't work, what is the better
solution?
Best Regards
Marcos
