Hi,I'm using MLLib to train a random forest. It's working fine to depth 15,
but if I use depth 20 I get a*java.lang.OutOfMemoryError: Requested array
size exceeds VM limit* on the driver, from the collectAsMap operation in
DecisionTree.scala, around line 642.It doesn't happen un
.set("spark.serializer",
"org.apache.spark.serializer.KryoSerializer").set("spark.kryoserializer.buffer.mb",
"256")
java.lang.OutOfMemoryError: Requested array size exceeds VM limit
at java.util.Arrays.copyOf(Arrays.java:2271)
at
java.i
ry.
On Mon, Feb 23, 2015 at 6:44 PM, insperatum wrote:
> Hi, I'm using MLLib to train a random forest. It's working fine to depth 15,
> but if I use depth 20 I get a java.lang.OutOfMemoryError: Requested array
> size exceeds VM limit on the driver, from the collectAsMap opera
kSetManager: Lost task 0.0 in stage 3.0
(TID 2028, idp11.foo.bar): java.lang.OutOfMemoryError: Requested array size
exceeds VM limit
java.util.Arrays.copyOf(Arrays.java:3230)
java.io.ByteArrayOutputStream.grow(ByteArrayOutputStream.java:113)
java.io.ByteArrayOutputStream.ensureCapacity(ByteArrayO
Hi,
I’m using Spark 1.1.0 and I’m having some issues to setup memory options.
I get “Requested array size exceeds VM limit” and I’m probably missing
something regarding memory configuration
(https://spark.apache.org/docs/1.1.0/configuration.html).
My server has 30G of memory and this are my
st 4
14/11/03 20:46:00 WARN BlockManager: Putting block rdd_19_5 failed
14/11/03 20:46:00 ERROR Executor: Exception in task 5.0 in stage 3.0 (TID
70)
java.lang.OutOfMemoryError: Requested array size exceeds VM limit
at java.util.Arrays.copyOf(Arrays.java:2271)
at
java.io.ByteArrayO
For uniform partitioning, you can try custom Partitioner.
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> COUNT(*)
> FROM
>p_all_tx
> WHERE
>date_prefix >= "20150500"
>AND date_prefix <= "20150700"
>AND sanitizeddetails.merchantaccountid = 'Rvr7StMZSTQj';
java.lan
8Gb of memory
where as it only has 5Gb and hence it exceeds the VM Limit.
Thanks
Best Regards
On Mon, Oct 20, 2014 at 4:42 PM, Arian Pasquali
wrote:
> Hi,
> I’m using Spark 1.1.0 and I’m having some issues to setup memory options.
> I get “Requested array size exceeds VM limit” and I’m
of
> memory where as it only has 5Gb and hence it exceeds the VM Limit.
>
>
>
> Thanks
> Best Regards
>
> On Mon, Oct 20, 2014 at 4:42 PM, Arian Pasquali
> wrote:
>
>> Hi,
>> I’m using Spark 1.1.0 and I’m having some issues to setup memory options.
&g
erIterator$BasicBlockFetcherIterator:
>>> Getting 1566 non-empty blocks out of 1566 blocks
>>> 14/10/11 13:00:16 INFO BlockFetcherIterator$BasicBlockFetcherIterator:
>>> Started 0 remote fetches in 4 ms
>>> 14/10/11 13:02:06 INFO ExternalAppendOnlyMap:
Hi,
The array size you (or the serializer) tries to allocate is just too big
for the JVM. No configuration can help :
https://plumbr.eu/outofmemoryerror/requested-array-size-exceeds-vm-limit
The only option is to split you problem further by increasing parallelism.
Guillaume
Hi,
I’m using
Hi,
>
> The array size you (or the serializer) tries to allocate is just too big
> for the JVM. No configuration can help :
>
> https://plumbr.eu/outofmemoryerror/requested-array-size-exceeds-vm-limit
>
> The only option is to split you problem further by increasing parallelism.
can provide.
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I am trying to read an XML file which is 1GB is size. I am getting an
error 'java.lang.OutOfMemoryError: Requested array size exceeds VM limit'
after reading 7 partitions in local mode. In Yarn mode, it
throws 'java.lang.OutOfMemoryError: Java heap space' error after readin
ricks/spark-xml/issues if you still face this
problem?
I will try to take a look at my best.
Thank you.
2016-11-16 9:12 GMT+09:00 Arun Patel :
> I am trying to read an XML file which is 1GB is size. I am getting an
> error 'java.lang.OutOfMemoryError: Requested array size exceeds V
f you still face this problem?
>
> I will try to take a look at my best.
>
>
> Thank you.
>
>
> 2016-11-16 9:12 GMT+09:00 Arun Patel :
>
>> I am trying to read an XML file which is 1GB is size. I am getting an
>> error 'java.lang.OutOfMemoryErr
//github.com/databricks/spark-xml/issues if you still face this
>> problem?
>>
>> I will try to take a look at my best.
>>
>>
>> Thank you.
>>
>>
>> 2016-11-16 9:12 GMT+09:00 Arun Patel :
>>
>>> I am trying to read an XML file w
to doubly sure if you don't mind?.
>>>
>>>
>>> Lastly, do you mind if I ask to open an issue in
>>> https://github.com/databricks/spark-xml/issues if you still face this
>>> problem?
>>>
>>> I will try to take a look at my best
using hive SQL but for the both cases, it throws me below
error with no further description on error.
hive_context.sql("select * from test.base_table where
date='{0}'".format(part_dt))
sqlcontext.read.parquet("/path/to/partion/")
#
# java.lang.OutOfMemoryError: R
Have you seen this thread ?
http://search-hadoop.com/m/q3RTtyXr2N13hf9O&subj=java+lang+OutOfMemoryError+Requested+array+size+exceeds+VM+limit
On Wed, May 4, 2016 at 2:44 PM, Bijay Kumar Pathak wrote:
> Hi,
>
> I am reading the parquet file around 50+ G which has 4013 partitio
;.format(part_dt))
> sqlcontext.read.parquet("/path/to/partion/")
>
> #
> # java.lang.OutOfMemoryError: Requested array size exceeds VM limit
> # -XX:OnOutOfMemoryError="kill -9 %p"
> # Executing /bin/sh -c "kill -9 16953"...
>
>
> What cou
esn't work, throws java.lang.OutOfMemoryError: Requested array size
exceeds VM limit
df.write.mode('overwrite').partitionBy('e_dt','c_dt').parquet("/path/to/file/")
Thanks,
Bijay
On Wed, May 4, 2016 at 3:02 PM, Prajwal Tuladhar wrote:
> If you are run
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