Hello,
Is Kubernetes Dynamic executor scaling for spark is available in latest
release of spark
I mean scaling the executors based on the work load vs preallocating number
of executors for a spark job
Thanks,
Purna
Thanks this is a great news
Can you please lemme if dynamic resource allocation is available in spark
2.4?
I’m using spark 2.3.2 on Kubernetes, do I still need to provide executor
memory options as part of spark submit command or spark will manage
required executor memory based on the spark job s
Hello ,
We're running spark 2.3.1 on kubernetes v1.11.0 and our driver pods from
k8s are getting stuck in initializing state like so:
NAME
READY STATUS RESTARTS AGE
my-pod-fd79926b819d3b34b05250e23347d0e7-driver 0/1 Init:0/1 0
18h
And from
We're running spark 2.3.1 on kubernetes v1.11.0 and our driver pods from
k8s are getting stuck in initializing state like so:
NAME
READY STATUS RESTARTS AGE
my-pod-fd79926b819d3b34b05250e23347d0e7-driver 0/1 Init:0/1 0
18h
And from *kubectl
Resurfacing The question to get more attention
Hello,
>
> im running Spark 2.3 job on kubernetes cluster
>>
>> kubectl version
>>
>> Client Version: version.Info{Major:"1", Minor:"9",
>> GitVersion:"v1.9.3", GitCommit:"d2835416544f298c919e2ead3be3d0864b52323b",
>> GitTreeState:"clean", BuildDa
Hello,
im running Spark 2.3 job on kubernetes cluster
>
> kubectl version
>
> Client Version: version.Info{Major:"1", Minor:"9",
> GitVersion:"v1.9.3", GitCommit:"d2835416544f298c919e2ead3be3d0864b52323b",
> GitTreeState:"clean", BuildDate:"2018-02-09T21:51:06Z",
> GoVersion:"go1.9.4", Compile
im running Spark 2.3 job on kubernetes cluster
kubectl version
Client Version: version.Info{Major:"1", Minor:"9", GitVersion:"v1.9.3",
GitCommit:"d2835416544f298c919e2ead3be3d0864b52323b", GitTreeState:"clean",
BuildDate:"2018-02-09T21:51:06Z", GoVersion:"go1.9.4", Compiler:"gc",
Platform:"da
at
io.netty.util.concurrent.DefaultThreadFactory$DefaultRunnableDecorator.run(DefaultThreadFactory.java:138)
at java.lang.Thread.run(Thread.java:
On Tue, Jul 31, 2018 at 8:32 AM purna pradeep
wrote:
>
> Hello,
>>
>>
>>
>> I’m getting below error in spark d
> Hello,
>
>
>
> I’m getting below error in spark driver pod logs and executor pods are
> getting killed midway through while the job is running and even driver pod
> Terminated with below intermittent error ,this happens if I run multiple
> jobs in parallel.
>
>
>
> Not able to see executor logs
Hello,
I’m getting below error in spark driver pod logs and executor pods are
getting killed midway through while the job is running and even driver pod
Terminated with below intermittent error ,this happens if I run multiple
jobs in parallel.
Not able to see executor logs as executor pods a
Hello,
I’m getting below error in spark driver pod logs and executor pods are getting
killed midway through while the job is running and even driver pod Terminated
with below intermittent error ,this happens if I run multiple jobs in parallel.
Not able to see executor logs as executor pods are
> Hello,
>
>
>
> When I’m trying to set below options to spark-submit command on k8s Master
> getting below error in spark-driver pod logs
>
>
>
> --conf spark.executor.extraJavaOptions=" -Dhttps.proxyHost=myhost
> -Dhttps.proxyPort=8099 -Dhttp.useproxy=true -Dhttps.protocols=TLSv1.2" \
>
> --conf
Hello,
When I’m trying to set below options to spark-submit command on k8s Master
getting below error in spark-driver pod logs
--conf spark.executor.extraJavaOptions=" -Dhttps.proxyHost=myhost
-Dhttps.proxyPort=8099 -Dhttp.useproxy=true -Dhttps.protocols=TLSv1.2" \
--conf spark.driver.extraJ
Hello,
When I’m trying to set below options to spark-submit command on k8s Master
getting below error in spark-driver pod logs
--conf spark.executor.extraJavaOptions=" -Dhttps.proxyHost=myhost
-Dhttps.proxyPort=8099 -Dhttp.useproxy=true -Dhttps.protocols=TLSv1.2" \
--conf spark.driver.extraJ
Hello,
When I run spark-submit on k8s cluster I’m
Seeing driver pod stuck in Running state and when I pulled driver pod logs
I’m able to see below log
I do understand that this warning might be because of lack of cpu/ Memory ,
but I expect driver pod be in “Pending” state rather than “ Running”
im reading below json in spark
{"bucket": "B01", "actionType": "A1", "preaction": "NULL",
"postaction": "NULL"}
{"bucket": "B02", "actionType": "A2", "preaction": "NULL",
"postaction": "NULL"}
{"bucket": "B03", "actionType": "A3", "preaction": "NULL",
"postaction": "NULL"}
val df=
y exit/crashloop due to
> lack of resource.
>
> On Tue, May 29, 2018 at 3:18 PM, purna pradeep
> wrote:
>
>> Hello,
>>
>> I’m getting below error when I spark-submit a Spark 2.3 app on
>> Kubernetes *v1.8.3* , some of the executor pods were killed with below
Hello,
I’m getting below error when I spark-submit a Spark 2.3 app on Kubernetes
*v1.8.3* , some of the executor pods were killed with below error as soon
as they come up
Exception in thread "main" java.lang.reflect.UndeclaredThrowableException
at
org.apache.hadoop.security.Use
Hello,
I’m getting below intermittent error when I spark-submit a Spark 2.3 app on
Kubernetes v1.8.3 , some of the executor pods were killed with below error as
soon as they come up
Exception in thread "main" java.lang.reflect.UndeclaredThrowableException
at
org.apache.hadoo
Hello,
I’m getting below intermittent error when I spark-submit a Spark 2.3 app on
Kubernetes v1.8.3 , some of the executor pods were killed with below error as
soon as they come up
Exception in thread "main" java.lang.reflect.UndeclaredThrowableException
at
org.apache.hadoo
Hello,
Currently I observe dead pods are not getting garbage collected (aka spark
driver pods which have completed execution). So pods could sit in the
namespace for weeks potentially. This makes listing, parsing, and reading
pods slower and well as having junk sit on the cluster.
I believe minim
Hi,
What would be the recommended approach to wait for spark driver pod to
complete the currently running job before it gets evicted to new nodes
while maintenance on the current node is goingon (kernel upgrade,hardware
maintenance etc..) using drain command
I don’t think I can use PoDisruptionBu
Hello,
Would like to know if anyone tried oozie with spark 2.3 actions on
Kubernetes for scheduling spark jobs .
Thanks,
Purna
yes “REST application that submits a Spark job to a k8s cluster by running
spark-submit programmatically” and also would like to expose as a
Kubernetes service so that clients can access as any other Rest api
On Wed, Apr 4, 2018 at 12:25 PM Yinan Li wrote:
> Hi Kittu,
>
> What do you mean by "a
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automatically submits the applications to run on a Kubernetes cluster.
>
> Yinan
>
> On Tue, Mar 20, 2018 at 7:47 PM, purna pradeep
> wrote:
>
>> Im using kubernetes cluster on AWS to run spark jobs ,im using spark 2.3
>> ,now i want to run spark-submit from AWS lam
Im using kubernetes cluster on AWS to run spark jobs ,im using spark 2.3
,now i want to run spark-submit from AWS lambda function to k8s
master,would like to know if there is any REST interface to run Spark
submit on k8s Master
ssue
> https://github.com/apache-spark-on-k8s/spark/issues/558 might help.
>
>
> On Sun, Mar 11, 2018 at 5:01 PM, purna pradeep
> wrote:
>
>> Getting below errors when I’m trying to run spark-submit on k8 cluster
>>
>>
>> *Error 1*:This looks like a warning it doesn’
Getting below errors when I’m trying to run spark-submit on k8 cluster
*Error 1*:This looks like a warning it doesn’t interrupt the app running
inside executor pod but keeps on getting this warning
*2018-03-09 11:15:21 WARN WatchConnectionManager:192 - Exec Failure*
*java.io.EOFExcepti
Im trying to run spark-submit to kubernetes cluster with spark 2.3 docker
container image
The challenge im facing is application have a mainapplication.jar and other
dependency files & jars which are located in Remote location like AWS s3
,but as per spark 2.3 documentation there is something call
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Hi all,
Im performing spark submit using Spark rest api POST operation on 6066 port
with below config
> Launch Command:
> "/usr/lib/jvm/java-1.8.0-openjdk-1.8.0.141-1.b16.el7_3.x86_64/jre/bin/java"
> "-cp" "/usr/local/spark/conf/:/usr/local/spark/jars/*" "-Xmx4096M"
> "-Dspark.eventLog.enabled=t
Hi,
I'm using spark standalone in aws ec2 .And I'm using spark rest
API http::8080/Json to get completed apps but the Json completed
apps as empty array though the job ran successfully.
with @ayan sql
>
> spark.sql("select *, row_number(), last_value(income) over (partition by
> id order by income_age_ts desc) r from t")
>
>
> On Tue, Aug 29, 2017 at 11:30 PM, purna pradeep
> wrote:
>
>> @ayan,
>>
>> Thanks for your response
>>
4/20/17| 1|
> | 4/20/12| DS|102| 13000| 5/9/17| 1|
> +++---+--+-+---+
>
> This should be better because it uses all in-built optimizations in Spark.
>
> Best
> Ayan
>
> On Wed, Aug 30, 2017 at 11:06 AM, purna pradeep
>
Please click on unnamed text/html link for better view
On Tue, Aug 29, 2017 at 8:11 PM purna pradeep
wrote:
>
> -- Forwarded message -
> From: Mamillapalli, Purna Pradeep <
> purnapradeep.mamillapa...@capitalone.com>
> Date: Tue, Aug 29, 2017 at 8:0
se(pexpense.toDouble,
> cexpense.toDouble))
>
>
>
>
>
> On Tue, Aug 29, 2017 at 6:53 AM, purna pradeep
> wrote:
>
>> I have data in a DataFrame with below columns
>>
>> 1)Fileformat is csv
>> 2)All below column datatypes are String
>>
>> employeei
-- Forwarded message -
From: Mamillapalli, Purna Pradeep
Date: Tue, Aug 29, 2017 at 8:08 PM
Subject: Spark question
To: purna pradeep
Below is the input Dataframe(In real this is a very large Dataframe)
EmployeeID
INCOME
INCOME AGE TS
JoinDate
Dept
101
19000
4/20/17
4
I have data in a DataFrame with below columns
1)Fileformat is csv
2)All below column datatypes are String
employeeid,pexpense,cexpense
Now I need to create a new DataFrame which has new column called `expense`,
which is calculated based on columns `pexpense`, `cexpense`.
The tricky part is
And also is query.stop() is graceful stop operation?what happens to already
received data will it be processed ?
On Tue, Aug 15, 2017 at 7:21 PM purna pradeep
wrote:
> Ok thanks
>
> Few more
>
> 1.when I looked into the documentation it says onQueryprogress is not
> thre
hronous
> unpersist+persist will probably take longer as it has to reload the data.
>
>
> On Tue, Aug 15, 2017 at 2:29 PM, purna pradeep
> wrote:
>
>> Thanks tathagata das actually I'm planning to something like this
>>
>> activeQuery.stop()
>>
>>
t; activeQuery.stop()
> activeQuery = startQuery()
>}
>
>activeQuery.awaitTermination(100) // wait for 100 ms.
>// if there is any error it will throw exception and quit the loop
>// otherwise it will keep checking the condition every 100ms}
>
>
.apache.org/docs/latest/structured-streaming-programming-guide.html#recovering-from-failures-with-checkpointing
>
> Though I think that this currently doesn't work with the console sink.
>
> On Tue, Aug 15, 2017 at 9:40 AM, purna pradeep
> wrote:
>
>> Hi,
>>
Hi,
>
> I'm trying to restart a streaming query to refresh cached data frame
>
> Where and how should I restart streaming query
>
val sparkSes = SparkSession
.builder
.config("spark.master", "local")
.appName("StreamingCahcePoc")
.getOrCreate()
import sparkSes.
Im working on structered streaming application wherein im reading from
Kafka as stream and for each batch of streams i need to perform S3 lookup
file (which is nearly 200gb) to fetch some attributes .So im using
df.persist() (basically caching the lookup) but i need to refresh the
dataframe as the
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