Re: Monitoring Spark Jobs

2015-06-10 Thread Himanshu Mehra
Hi Sam,

You might want to have a look at spark UI which runs by default at
localhost://8080. You can also configure Apache Ganglia to monitor over your
cluster resources. 

Thank you
Regards
Himanshu Mehra



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Re: Monitoring Spark Jobs

2015-06-07 Thread Otis Gospodnetić
Hi Sam,

Have a look at Sematext's SPM for your Spark monitoring needs. If the
problem is CPU, IO, Network, etc. as Ahkil mentioned, you'll see that in
SPM, too.
As for the number of jobs running, you have see a chart with that at
http://sematext.com/spm/integrations/spark-monitoring.html

Otis
--
Monitoring * Alerting * Anomaly Detection * Centralized Log Management
Solr  Elasticsearch Support * http://sematext.com/


On Sun, Jun 7, 2015 at 6:37 AM, SamyaMaiti samya.maiti2...@gmail.com
wrote:

 Hi All,

 I have a Spark SQL application to fetch data from Hive, on top I have a
 akka
 layer to run multiple Queries in parallel.

 *Please suggest a mechanism, so as to figure out the number of spark jobs
 running in the cluster at a given instance of time. *

 I need to do the above as, I see the average response time increasing with
 increase in number of requests, in-spite of increasing the number of cores
 in the cluster. I suspect there is a bottleneck somewhere else.

 Regards,
 Sam



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Re: Monitoring Spark Jobs

2015-06-07 Thread Akhil Das
It could be a CPU, IO, Network bottleneck, you need to figure out where
exactly its chocking. You can use certain monitoring utilities (like top)
to understand it better.

Thanks
Best Regards

On Sun, Jun 7, 2015 at 4:07 PM, SamyaMaiti samya.maiti2...@gmail.com
wrote:

 Hi All,

 I have a Spark SQL application to fetch data from Hive, on top I have a
 akka
 layer to run multiple Queries in parallel.

 *Please suggest a mechanism, so as to figure out the number of spark jobs
 running in the cluster at a given instance of time. *

 I need to do the above as, I see the average response time increasing with
 increase in number of requests, in-spite of increasing the number of cores
 in the cluster. I suspect there is a bottleneck somewhere else.

 Regards,
 Sam



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