On Wed, May 27, 2015 at 1:51 AM, Tousif tousif.pa...@gmail.com wrote:
Hi ,
Is there a way to share a resource file across all workers similar to
hdfs. That resource/config file will have to be updated run time. i'm not
looking at using hdfs for now.
--
Regards
Tousif Khazi
--
Hello!
I'm interesting in running the storm topologies on yarn.
I was looking at the yahoo project https://github.com/yahoo/storm-yarn, and
I could observed that there is no activity since 7 months ago. Also, the
issues and requests lists are not updated.
Therefore I have some questions:
1. Is
Hi ,
If file is small you can pass them as json serialized object in storm
config while submiting topology and get from config map at spout and bolt.
Thanks,
_Nipur
On May 27, 2015 3:22 PM, Chris Bedford ch...@buildlackey.com wrote:
On Wed, May 27, 2015 at 1:51 AM, Tousif
Hi ,
Is there a way to share a resource file across all workers similar to hdfs.
That resource/config file will have to be updated run time. i'm not looking
at using hdfs for now.
--
Regards
Tousif Khazi
I have heard Nathan Marz mention Mesos.
How is yarn / storm-yarn / slider-yarn different from Mesos?
These are the links I found to Mesos:
https://github.com/mesos/storm
https://github.com/nathanmarz/storm-mesos
http://mesos.apache.org/
Thank you for your time!
+
Jeff
Mesos is very similar to YARN. It is a resource scheduler. Storm in the past
had support for mesos, through a separate repo
https://github.com/nathanmarz/storm-mesos
it might still work with the latest versions of storm. I don't know. The
concept here is that there was a special layer
storm-yarn was originally done as a proof of concept. We had plans to take it
further, but the amount of work required to make it production ready on a very
heavily used cluster was more then we were willing to invest at the time. Most
of that work was around network scheduling, isolation and
I also developed a prototype/proof-of-concept (read: duck tape and bailer
twine) for running Storm on YARN.
I took a slightly different approach than Yahoo’s storm-yarn and Slider which
from a high level allow you to spin up a Storm cluster on top of YARN. In my
PoC a topology is treated as a
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Thanks Bobby, for the detailed answer.
So it sounds like , it is better not to combine Storm with batch workloads at
this point (yarn, mesos or ec2), due to the network saturation and timeout
threats.
Is this behavior also seen in other streaming frameworks
Hi Nathan,
I want to do real time computation using storm, which one is best storm or
trident. i need to handle huge amount of data , exactly once please help me
Thanks!
Date: Wed, 27 May 2015 12:40:43 -0400
Subject: Re: Status of running storm on yarn (the yahoo project)
From:
Mesosphere has official support for Storm on Mesos:
https://github.com/mesos/storm
On Wed, May 27, 2015 at 11:14 AM, rajesh_kall...@dellteam.com wrote:
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Thanks Bobby, for the detailed answer.
So it sounds like , it is better not to combine Storm with
Not sure if you fixed the issue but I think the problem may come from the
max spout pending.
You are using Trident and this value is the max number of pending BATCHES
and not number
of tuples so let say your topic has 10 partitions and max spout pending
is set to 10 and the max
fetch size is set
If it is really static thing, you can serialize it and pass to Bolt's
constructor.
If you don't want to spend serialization cost, you can store it to file
(and include it to resources of jar) and load it from preparation of Bolt.
If you want to have small jar, you can use external storage. (RDB,
http://www.meetup.com/Bay-Area-Stream-Processing/events/219086133/
Thursday, June 4, 2015
6:45 PM
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The previous reply was from March 10th so Bill may have resolved this issue but
here is some info that can be useful to other folks in the future.
You can set the JVM flags to do a heapdump on OOM using
-XX:+HeapDumpOnOutOfMemoryError.
You can then analyze
Hi Storm fellows, I've got a simple question and would like to have a
quick answer.
Let's say a storm topology is running on a cluster without any supervision,
at the beginning it is behaving properly and have a balanced distribution.
But you know, sometimes errors may occur and bring down the
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