I had that issue too and from what I gathered, it is an expected
optimization... Try using repartiion instead
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On Feb 3, 2021, 11:55, at 11:55, James Yu wrote:
>Hi Team,
>
>We are running into this poor performance issue and seeking your
>suggestion on how to improve
you can specify the schema programmatically
https://spark.apache.org/docs/latest/sql-programming-guide.html#programmatically-specifying-the-schema
On Wed, Oct 11, 2017 at 3:35 PM, sk skk wrote:
> Can we create a dataframe from a Java pair rdd of String . I don’t have a
> schema as it will be a
Sounds like such a small job , if you running in on a cluster have you
consider simply running it locally (master = local) ?
On Wed, Sep 27, 2017 at 7:06 AM, navneet sharma wrote:
> Hi,
>
> I am running spark job taking total 18s, in that 8 seconds for actual
> processing logic(business logic)
This works for us
yarn.nodemanager.aux-services
mapreduce_shuffle,spark_shuffle
yarn.nodemanager.aux-services.mapreduce_shuffle.class
org.apache.hadoop.mapred.ShuffleHandler
yarn.nodemanager.aux-services.spark_shuffle.class
org.apache.spark.network.yarn.Yarn
aps and generate your lists
}
On Wed, Dec 23, 2015 at 10:49 AM, Yasemin Kaya wrote:
> How can i use mapPartion? Could u give me an example?
>
> 2015-12-23 17:26 GMT+02:00 Stéphane Verlet :
>
>> You should be able to do that using mapPartition
>>
>> On Wed, Dec
You should be able to do that using mapPartition
On Wed, Dec 23, 2015 at 8:24 AM, Ted Yu wrote:
> bq. {a=1, b=1, c=2, d=2}
>
> Can you elaborate your criteria a bit more ? The above seems to be a Set,
> not a Map.
>
> Cheers
>
> On Wed, Dec 23, 2015 at 7:11 AM, Yasemin Kaya wrote:
>
>> Hi,
>>
>
illing the app in spark UI doesn't kill the process launched via script
>
>
> On Friday, November 20, 2015, Stéphane Verlet
> wrote:
>
>> I solved the first issue by adding a shutdown hook in my code. The
>> shutdown hook get call when you exit your script (
I solved the first issue by adding a shutdown hook in my code. The shutdown
hook get call when you exit your script (ctrl-C , kill … but nor kill -9)
val shutdownHook = scala.sys.addShutdownHook {
try {
sparkContext.stop()
//Make sure to kill any other threads or thread pool you may be ru
sqlContext.sql().map(row=> ((row.getString(0),
row.getString(1)),row.getInt(2)))
On Wed, Nov 4, 2015 at 1:44 PM, pratik khadloya wrote:
> Hello,
>
> Is it possible to have a pair RDD from the below SQL query.
> The pair being ((item_id, flight_id), metric1)
>
> item_id, flight_id are part of gr
Create a custom key class implement the equals methods and make sure the
hash method is compatible.
Use that key to map and join your row.
On Sat, May 9, 2015 at 4:02 PM, Mathieu D wrote:
> Hi folks,
>
> I need to join RDDs having composite keys like this : (K1, K2 ... Kn).
>
> The joining ru
>From your pseudo code, it would be sequential and done twice
1+2+3
then 1+2+4
If you do a .cache() in step 2 then you would have 1+2+3 , then 4
I ran several steps in parrallel from the same program but never using the
same source RDD so I do not know the limitations there. I simply started
Yes , It is working with this in spark-env.sh
export JAVA_LIBRARY_PATH=$JAVA_LIBRARY_PATH:$HADOOP_HOME/lib/native
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$HADOOP_HOME/lib/native
export SPARK_LIBRARY_PATH=$SPARK_LIBRARY_PATH:$HADOOP_HOME/lib/native
export
SPARK_CLASSPATH=$SPARK_CLASSPATH:$HADOOP_HO
Disclaimer : I am new at Spark
I did something similar in a prototype which works but I that did not test
at scale yet
val agg =3D users.mapValues(_ =3D> 1)..aggregateByKey(new
CustomAggregation())(CustomAggregation.sequenceOp, CustomAggregation.comboO=
p)
class CustomAggregation() extends
I first saw this using SparkSQL but the result is the same with plain
Spark.
14/11/07 19:46:36 ERROR Executor: Exception in task 1.0 in stage 0.0 (TID 1)
java.lang.UnsatisfiedLinkError:
org.apache.hadoop.util.NativeCodeLoader.buildSupportsSnappy()Z
at org.apache.hadoop.util.NativeCodeLoader.buildS
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