a
similar exception:
java.lang.OutOfMemoryError: unable to create new native thread
at java.lang.Thread.start0(Native Method)
at java.lang.Thread.start(Thread.java:714)
I increased nproc (i.e. ulimit -u) 10 fold, but it doesn't help.
Does anyone know how to avoid those kinds of errors?
Noteworthy
in spark on large jobs which all share a
similar exception:
java.lang.OutOfMemoryError: unable to create new native thread
at java.lang.Thread.start0(Native Method)
at java.lang.Thread.start(Thread.java:714)
I increased nproc (i.e. ulimit -u) 10 fold, but it doesn't help.
Does anyone know
Hello,
I am seeing various crashes in spark on large jobs which all share a
similar exception:
java.lang.OutOfMemoryError: unable to create new native thread
at java.lang.Thread.start0(Native Method)
at java.lang.Thread.start(Thread.java:714)
I increased nproc (i.e. ulimit -u) 10 fold
?
If so then I think you need to make more, smaller executors instead?
On Tue, Mar 24, 2015 at 7:38 PM, Thomas Gerber thomas.ger...@radius.com wrote:
Hello,
I am seeing various crashes in spark on large jobs which all share a similar
exception:
java.lang.OutOfMemoryError: unable to create new
in spark on large jobs which all share a
similar exception:
java.lang.OutOfMemoryError: unable to create new native thread
at java.lang.Thread.start0(Native Method)
at java.lang.Thread.start(Thread.java:714)
I increased nproc (i.e. ulimit -u) 10 fold, but it doesn't help.
Does anyone know
kras...@gmail.com
Cc: Sandy Ryza sandy.r...@cloudera.com, user@spark.apache.org
user@spark.apache.org
Subject: Re: java.lang.OutOfMemoryError: GC overhead limit exceeded
I have yarn configured with yarn.nodemanager.vmem-check-enabled=false and
yarn.nodemanager.pmem-check-enabled=false to avoid
Hi Antony,
If you look in the YARN NodeManager logs, do you see that it's killing the
executors? Or are they crashing for a different reason?
-Sandy
On Tue, Jan 27, 2015 at 12:43 PM, Antony Mayi antonym...@yahoo.com.invalid
wrote:
Hi,
I am using spark.yarn.executor.memoryOverhead=8192 yet
Hi,
I am using spark.yarn.executor.memoryOverhead=8192 yet getting executors
crashed with this error.
does that mean I have genuinely not enough RAM or is this matter of config
tuning?
other config options used:spark.storage.memoryFraction=0.3
SPARK_EXECUTOR_MEMORY=14G
running spark 1.2.0 as
sandy.r...@cloudera.com
Date: Tuesday, January 27, 2015 at 3:33 PM
To: Antony Mayi antonym...@yahoo.com
Cc: user@spark.apache.org user@spark.apache.org
Subject: Re: java.lang.OutOfMemoryError: GC overhead limit exceeded
Hi Antony,
If you look in the YARN NodeManager logs, do you see that it's
, 2015 at 3:33 PM
To: Antony Mayi antonym...@yahoo.com
Cc: user@spark.apache.org user@spark.apache.org
Subject: Re: java.lang.OutOfMemoryError: GC overhead limit exceeded
Hi Antony,
If you look in the YARN NodeManager logs, do you see that it's killing the
executors? Or are they crashing
: Re: java.lang.OutOfMemoryError: GC overhead limit exceeded
Since it's an executor running OOM it doesn't look like a container being
killed by YARN to me. As a starting point, can you repartition your job
into smaller tasks?
-Sven
On Tue, Jan 27, 2015 at 2:34 PM, Guru Medasani gdm...@outlook.com
17:02:53 ERROR executor.Executor: Exception in task 21.0 in
stage 12.0 (TID 1312)java.lang.OutOfMemoryError: GC overhead limit exceeded
at java.lang.Integer.valueOf(Integer.java:642) at
scala.runtime.BoxesRunTime.boxToInteger(BoxesRunTime.java:70
Hi Jay,
Please try increasing executor memory (if the available memory is more
than 2GB) and reduce numBlocks in ALS. The current implementation
stores all subproblems in memory and hence the memory requirement is
significant when k is large. You can also try reducing k and see
whether the
I am not sure this can help you. I have 57 million rating,about 4million user
and 4k items. I used 7-14 total-executor-cores,executal-memory 13g,cluster
have 4 nodes,each have 4cores,max memory 16g.
I found set as follows may help avoid this problem:
Hi,How many clients and how many products do you have?CheersGen
jaykatukuri wrote
Hi all,I am running into an out of memory error while running ALS using
MLLIB on a reasonably small data set consisting of around 6 Million
ratings.The stack trace is below:java.lang.OutOfMemoryError: Java heap
How many working nodes do these 100 executors locate at?
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only option is to split you problem further by increasing parallelism My
understanding is by increasing the number of partitions, is that right?
That didn't seem to help because it is seem the partitions are not uniformly
sized. My observation is when I increase the number of partitions, it
ERROR Executor: Exception in task 0.0 in stage 0.0 (TID
1566)
java.lang.OutOfMemoryError: Requested array size exceeds VM limit
at java.util.Arrays.copyOf(Arrays.java:2271)
at
java.io.ByteArrayOutputStream.grow(ByteArrayOutputStream.java:113
Executor: Exception in task 0.0 in stage 0.0 (TID 1566)
java.lang.OutOfMemoryError: Requested array size exceeds VM limit
at java.util.Arrays.copyOf(Arrays.java:2271)
at java.io.ByteArrayOutputStream.grow(ByteArrayOutputStream.java:113
map of 3925 MB to disk (1 time so far)
14/10/11 13:05:17 INFO ExternalAppendOnlyMap: Thread 63 spilling in-memory
map of 3925 MB to disk (2 times so far)
14/10/11 13:09:15 ERROR Executor: Exception in task 0.0 in stage 0.0 (TID
1566)
java.lang.OutOfMemoryError: Requested array size exceeds VM
map of 3925 MB to disk (1 time so far)
14/10/11 13:05:17 INFO ExternalAppendOnlyMap: Thread 63 spilling
in-memory map of 3925 MB to disk (2 times so far)
14/10/11 13:09:15 ERROR Executor: Exception in task 0.0 in stage 0.0 (TID
1566)
java.lang.OutOfMemoryError: Requested array size exceeds VM
in-memory map of 3925 MB to disk (1 time so far)
14/10/11 13:05:17 INFO ExternalAppendOnlyMap: Thread 63 spilling
in-memory map of 3925 MB to disk (2 times so far)
14/10/11 13:09:15 ERROR Executor: Exception in task 0.0 in stage 0.0
(TID 1566)
java.lang.OutOfMemoryError: Requested array size
0.0 in stage 0.0
(TID 1566)
java.lang.OutOfMemoryError: Requested array size exceeds VM limit
at java.util.Arrays.copyOf(Arrays.java:2271)
at
java.io.ByteArrayOutputStream.grow(ByteArrayOutputStream.java:113)
at
java.io.ByteArrayOutputStream.ensureCapacity
:34602], 1 messages pending
14/10/20 22:38:41 INFO ConnectionManager: Accepted connection from
[cse-hadoop-113/192.168.0.113]
Exception in thread pool-5-thread-3 java.lang.OutOfMemoryError: Java heap
space
at java.nio.HeapByteBuffer.init(HeapByteBuffer.java:57
\*
* --conf spark.driver.memory=2g \*
* target/scala-2.10/my-job_2.10-1.0.jar*
I get the following error :
*Exception in thread stdin writer for List(patch_matching_similarity)
java.lang.OutOfMemoryError: Java heap space*
* at java.util.Arrays.copyOf(Arrays.java:2271
] \
--conf spark.executor.memory=4g \
--conf spark.driver.memory=2g \
target/scala-2.10/my-job_2.10-1.0.jar
I get the following error :
Exception in thread stdin writer for List(patch_matching_similarity)
java.lang.OutOfMemoryError: Java heap space
at java.util.Arrays.copyOf
7000x7000 is not tall-and-skinny matrix. Storing the dense matrix
requires 784MB. The driver needs more storage for collecting result
from executors as well as making a copy for LAPACK's dgesvd. So you
need more memory. Do you need the full SVD? If not, try to use a small
k, e.g, 50. -Xiangrui
On
Hi Xianguri,
After setting SVD to smaller value (200) its working.
Thanks,
Shailesh
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Note, the data is random numbers (double).
Any suggestions/pointers will be highly appreciated.
Thanks,
Shailesh
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Sent from the
/09/24 15:40:38 INFO ContextCleaner: Cleaned broadcast 4
Exception in thread main java.lang.OutOfMemoryError: Java heap space
at breeze.linalg.svd$Svd_DM_Impl$.apply(svd.scala:48)
at breeze.linalg.svd$Svd_DM_Impl$.apply(svd.scala:32)
at breeze.generic.UFunc$class.apply
) associated
with image id. My goal is to draw these primitives on the corresponding
image. So my first attempt is to join images and primitives by image ids
and then do the drawing.
But, when I do
*primitives.join(images) *
I got the following error :
*java.lang.OutOfMemoryError: Java heap space
Hi guys,
My Spark Streaming application have this java.lang.OutOfMemoryError: GC
overhead limit exceeded error in SparkStreaming driver program. I have
done the following to debug with it：
1. improved the driver memory from 1GB to 2GB, this error came after 22
hrs. When the memory was 1GB
map
output locations for shuffle 2 to sp...@idp11.foo.bar:33925
14/08/27 22:36:30 INFO spark.MapOutputTrackerMaster: Size of output statuses
for shuffle 2 is 1263 bytes
14/08/27 22:37:06 WARN scheduler.TaskSetManager: Lost task 0.0 in stage 3.0
(TID 2028, idp11.foo.bar): java.lang.OutOfMemoryError
I got a 40 node cdh 5.1 cluster and attempting to run a simple spark app that
processes about 10-15GB raw data but I keep running into this error:
java.lang.OutOfMemoryError: GC overhead limit exceeded
Each node has 8 cores and 2GB memory. I notice the heap size on the
executors is set
to run a simple spark app that
processes about 10-15GB raw data but I keep running into this error:
java.lang.OutOfMemoryError: GC overhead limit exceeded
Each node has 8 cores and 2GB memory. I notice the heap size on the
executors is set to 512MB with total heap size on each executor
(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:744)14/07/31 09:48:17 ERROR
ExecutorUncaughtExceptionHandler: Uncaught exception in thread Thread[Executor
task launch worker-3,5,main]java.lang.OutOfMemoryError: Java heap space at
java.util.Arrays.copyOf(Arrays.java:2271
blocks
14/07/31 09:48:09 INFO BlockFetcherIterator$BasicBlockFetcherIterator:
Started 0 remote fetches in 1 ms
14/07/31 09:48:09 INFO BlockFetcherIterator$BasicBlockFetcherIterator:
Started 0 remote fetches in 1 ms
14/07/31 09:48:17 ERROR Executor: Exception in task ID 5
java.lang.OutOfMemoryError
Hi Yifan
This works for me:
export SPARK_JAVA_OPTS=-Xms10g -Xmx40g -XX:MaxPermSize=10g
export ADD_JARS=/home/abel/spark/MLI/target/MLI-assembly-1.0.jar
export SPARK_MEM=40g
./spark-shell
Regards
On Mon, Jul 21, 2014 at 7:48 AM, Yifan LI iamyifa...@gmail.com wrote:
Hi,
I am trying to load
Thanks, Abel.
Best,
Yifan LI
On Jul 21, 2014, at 4:16 PM, Abel Coronado Iruegas acoronadoirue...@gmail.com
wrote:
Hi Yifan
This works for me:
export SPARK_JAVA_OPTS=-Xms10g -Xmx40g -XX:MaxPermSize=10g
export ADD_JARS=/home/abel/spark/MLI/target/MLI-assembly-1.0.jar
export
Hi all,
I faced with the next exception during map step:
java.lang.OutOfMemoryError (java.lang.OutOfMemoryError: GC overhead limit
exceeded)
java.lang.reflect.Array.newInstance(Array.java:70)
com.esotericsoftware.kryo.serializers.DefaultArraySerializers$ObjectArraySerializer.read
.
On Tue, Jul 8, 2014 at 9:27 AM, Konstantin Kudryavtsev
kudryavtsev.konstan...@gmail.com wrote:
Hi all,
I faced with the next exception during map step:
java.lang.OutOfMemoryError (java.lang.OutOfMemoryError: GC overhead limit
exceeded)
java.lang.reflect.Array.newInstance(Array.java:70
kudryavtsev.konstan...@gmail.com wrote:
Hi all,
I faced with the next exception during map step:
java.lang.OutOfMemoryError (java.lang.OutOfMemoryError: GC overhead limit
exceeded)
java.lang.reflect.Array.newInstance(Array.java:70
to caching or serializing.
On Tue, Jul 8, 2014 at 9:27 AM, Konstantin Kudryavtsev
kudryavtsev.konstan...@gmail.com wrote:
Hi all,
I faced with the next exception during map step:
java.lang.OutOfMemoryError (java.lang.OutOfMemoryError: GC overhead
limit exceeded
.
java.lang.OutOfMemoryError: Java heap space
at
org.jboss.netty.buffer.HeapChannelBuffer.init(HeapChannelBuffer.java:42)
---
The specifics of the job is as follows:
- It reads 168016 files on the HDFS, by calling
sc.textFile(hdfs://cluster01/user/data/*/*/*.csv)
- The total size of the files is 164,111,123,686
.
-Original Message-
From: innowireless TaeYun Kim [mailto:taeyun@innowireless.co.kr]
Sent: Wednesday, July 02, 2014 5:58 PM
To: user@spark.apache.org
Subject: Help: WARN AbstractNioSelector: Unexpected exception in the
selector loop. java.lang.OutOfMemoryError: Java heap space
Hi
. java.lang.OutOfMemoryError: Java heap space
Also, the machine on which the driver program runs constantly uses about
7~8% of 100Mbps network connection.
Is the driver program involved in the reduceByKey() somehow?
BTW, currently an accumulator is used, but the network usage does not drop
even when accumulator
lightweight.
I
On Wed, Jun 18, 2014 at 5:17 PM, Shivani Rao raoshiv...@gmail.com
wrote:
I am trying to process a file that contains 4 log lines (not very long)
and then write my parsed out case classes to a destination folder, and I
get the following error:
java.lang.OutOfMemoryError: Java
:
java.lang.OutOfMemoryError: Java heap space
at
org.apache.hadoop.io.WritableUtils.readCompressedStringArray(WritableUtils.java:183)
at
org.apache.hadoop.conf.Configuration.readFields(Configuration.java:2244)
at
org.apache.hadoop.io.ObjectWritable.readObject(ObjectWritable.java:280
folder,
and I get the following error:
java.lang.OutOfMemoryError: Java heap space
at
org.apache.hadoop.io.WritableUtils.readCompressedStringArray(WritableUtils.java:183)
at
org.apache.hadoop.conf.Configuration.readFields(Configuration.java:2244
the following error:
java.lang.OutOfMemoryError: Java heap space
at
org.apache.hadoop.io.WritableUtils.readCompressedStringArray(WritableUtils.java:183)
at
org.apache.hadoop.conf.Configuration.readFields(Configuration.java:2244)
at
org.apache.hadoop.io.ObjectWritable.readObject
:
java.lang.OutOfMemoryError: Java heap space
at
org.apache.hadoop.io.WritableUtils.readCompressedStringArray(WritableUtils.java:183)
at
org.apache.hadoop.conf.Configuration.readFields(Configuration.java:2244)
at org.apache.hadoop.io.ObjectWritable.readObject(ObjectWritable.java:280
Once you have generated the final RDD before submitting it to reducer try to
repartition the RDD either using coalesce(partitions) or repartition() into
known partitions. 2. Rule of thumb to create number of data partitions (3 *
num_executors * cores_per_executor).
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I am trying to process a file that contains 4 log lines (not very long) and
then write my parsed out case classes to a destination folder, and I get
the following error:
java.lang.OutOfMemoryError: Java heap space
at
org.apache.hadoop.io.WritableUtils.readCompressedStringArray
, Jun 18, 2014 at 5:17 PM, Shivani Rao raoshiv...@gmail.com wrote:
I am trying to process a file that contains 4 log lines (not very long)
and then write my parsed out case classes to a destination folder, and I
get the following error:
java.lang.OutOfMemoryError: Java heap space
error when I try to save the transformed data set.
java.lang.OutOfMemoryError (java.lang.OutOfMemoryError: GC overhead limit
exceeded)
java.util.Arrays.copyOfRange(Arrays.java:3209)
java.lang.String.init(String.java:215)
java.lang.StringBuilder.toString(StringBuilder.java:430
: Uncaught exception in thread Result resolver
thread-2
java.lang.OutOfMemoryError: Java heap space
at java.nio.HeapByteBuffer.init(HeapByteBuffer.java:39)
at java.nio.ByteBuffer.allocate(ByteBuffer.java:312)
at org.apache.spark.storage.BlockMessage.set(BlockMessage.scala:94
400-500 mB of text, but I get this error whenever I try to collect:
java.lang.OutOfMemoryError: Java heap space
at java.nio.HeapByteBuffer.init(HeapByteBuffer.java:39)
at java.nio.ByteBuffer.allocate(ByteBuffer.java:312)
at org.apache.spark.storage.BlockMessage.set
Try repartitioning the RDD using coalsce(int partitions) before performing
any transforms.
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geoLocation1 g1 INNER JOIN geoBlocks1 g2 ON (g1.locId =
g2.locId)
I am getting following error as follows.
Exception in thread main org.apache.spark.SparkException: Job aborted:
Task 1.0:7 failed 4 times (most recent failure: Exception failure:
java.lang.OutOfMemoryError: Java heap space
geoBlocks1 g2 ON (g1.locId =
g2.locId)
I am getting following error as follows.
Exception in thread main org.apache.spark.SparkException: Job aborted:
Task 1.0:7 failed 4 times (most recent failure: Exception failure:
java.lang.OutOfMemoryError: Java heap space
(Method.java:622)
at org.apache.spark.deploy.SparkSubmit$.launch(SparkSubmit.scala:256)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:54)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
*Caused by: java.lang.OutOfMemoryError: unable to create new native thread
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