Hello Thomas,
Thank you very much for the response. Disabling the feature allowed me to move
from 1.2.3 => 2.2.0.
I understand the intent of the feature however in my case the end result was
one node getting all the load and eventual netty heap space exceptions.
Perhaps I should look at that... or perhaps I'll just leave the feature
disabled.
Again - thanks for the reply - VERY helpful.
On Saturday, November 14, 2020, 01:05:03 PM EST, Thomas L. Redman
<tomred...@mchsi.com> wrote:
I have seen this same thing. I sent a query on this list, and. after some
time, got a response. The issue is reportedly the result of a new feature. I
would assume this feature is CLEARLY broken, as I had built a test topology
that was clearly compute-bound, not IO bound, and there were adjustments to
change ratio of compute/IO. I have not tested this fix, I am too close to
release, I just rolled back to version 1.2.3.
From version 2.1.0 forward, not matter how I changed this compute/net IO
ratio, tuples were not distributed across nodes. Now, I could only reproduce
this with anchored (acked) tuples. But if you anchored tuples, you could never
span more than one node, which defeats the purpose of using Storm. Following is
that email from Kishor Patil identifying the issue (and a way to disable that
feature!!!):
From: Kishor Patil <kishorvpa...@apache.org>
Subject: Re: Significant Bug
Date: October 29, 2020 at 8:07:18 AM CDT
To: <d...@storm.apache.org>
Reply-To: d...@storm.apache.org
Hello Thomas,
Apologies for delay in responding here. I tested the topology code provided in
storm-issue repo.
*only one machine gets peggeg*: Although it appears, his is not a bug. This is
related to Locality Awareness. Please refer to
https://github.com/apache/storm/blob/master/docs/LocalityAwareness.md
It appears spout to bolt ratio is 200, so if there are enough bolt's on single
node to handle events generated by the spout, it won't send events out to
another node unless it runs out of capacity on single node. If you do not like
this and want to distribute events evenly, you can try disabling this feature.
You can turn off LoadAwareShuffleGrouping by setting
topology.disable.loadaware.messaging to true.
-Kishor
On 2020/10/28 15:21:54, "Thomas L. Redman" <tomred...@mchsi.com> wrote:
What’s the word on this? I sent this out some time ago, including a GitHub
project that clearly demonstrates the brokenness, yet I have not heard a word.
Is there anybody supporting Storm?
On Sep 30, 2020, at 9:03 AM, Thomas L. Redman <tomred...@mchsi.com> wrote:
I believe I have encountered a significant bug. It seems topologies employing
anchored tuples do not distribute across multiple nodes, regardless of the
computation demands of the bolts. It works fine on a single node, but when
throwing multiple nodes into the mix, only one machine gets pegged. When we
disable anchoring, it will distribute across all nodes just fine, pegging each
machine appropriately.
This bug manifests from version 2.1 forward. I first encountered this issue
with my own production cluster on an app that does significant NLP computation
across hundreds of millions of documents. This topology is fairly complex, so I
developed a very simple exemplar that demonstrates the issue with only one
spout and bolt. I pushed this demonstration up to github to provide the
developers with a mechanism to easily isolate the bug, and maybe provide some
workaround. I used gradle to build this simple topology and software and
package the results. This code is well documented, so it should be fairly
simple to reproduce the issue. I first encountered this issue on 3 32 core
nodes, but when I started experimenting, I set up a test cluster with 8 cores,
and then I increased each node to 16 cores, and plenty of memory in every case.
The topology can be accessed from github at
https://github.com/cowchipkid/storm-issue.git
<https://github.com/cowchipkid/storm-issue.git>. Please feel free to respond to
me directory if you have any questions that are beyond the scope of this mail
list.
Hope this helps. Please let me know how this goes, I will upgrade to 2.2.0
again for my next release.
On Nov 13, 2020, at 12:53 PM, Michael Giroux <michael_a_gir...@yahoo.com> wrote:
Hello, all,
I have a topology with 16 workers running across 4 nodes. This topology has a
bolt "transform" with executors=1 producing a stream that is comsumed by a bolt
"ontology" with executors=160. Everything is configured as shufflegrouping.
With Storm 1.2.3 all of the "ontology" bolts get their fair share of tuples.
When I run Storm 2.2.0 only the "ontology" bolts that are on the same node as
the single "transform" bolt get tuples.
Same cluster - same baseline code - only difference is binding in the new maven
artifact.
No errors in the logs.
Any thoughts would be welcome. Thanks!
