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Mihael Hategan wrote:
<blockquote cite="mid:1187065878.4015.19.camel@blabla.mcs.anl.gov"
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<pre wrap="">On Mon, 2007-08-13 at 23:07 -0500, Ioan Raicu wrote:
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<pre wrap="">small != not at all
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<pre wrap="">Check out these two graphs, showing the # of active tasks within
Falkon! Active tasks = queued+pending+active+done_and_not_delivered.
<a class="moz-txt-link-freetext" href="http://people.cs.uchicago.edu/~iraicu/research/docs/MolDyn/244-mol-success-8-10-07/number-of-active-tasks.jpg">http://people.cs.uchicago.edu/~iraicu/research/docs/MolDyn/244-mol-success-8-10-07/number-of-active-tasks.jpg</a>
<a class="moz-txt-link-freetext" href="http://people.cs.uchicago.edu/~iraicu/research/docs/MolDyn/244-mol-success-8-10-07/number-of-active-tasks-zoom.jpg">http://people.cs.uchicago.edu/~iraicu/research/docs/MolDyn/244-mol-success-8-10-07/number-of-active-tasks-zoom.jpg</a>
Notice that after 3600 some seconds (after all the jobs that failed
had failed), the # of active tasks in Falkon oscillates between 100
and 101 active tasks! The # presented on these graphs are taken from
the median value per minute (the raw samples were 60 samples per
minute). Notice that only at the very end of the experiment, at 30K+
seconds, the # of active tasks increases to a max of 109 for a brief
period of time before it drops towards 0 as the workflow completes. I
did notice that towards the end of the workflow, the jobs were
typically shorter, and perhaps that somehow influenced the # of active
tasks within Falkon... So, when I said not at all, I was refering to
this flat line 100~101 active tasks that is shown in these figures!
</pre>
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<pre wrap=""><!---->
Then say "it appears (from x and y) that the number of concurrent jobs
does not increase by an observable amount". This is not the same as "the
score does not increase at all".
</pre>
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You are playing with words here... the bottom line is that after 19K+
jobs and several hours of successful jobs, there was no indication that
the heuristic was adapting to the new conditions, in which no jobs were
failing!<br>
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<pre wrap="">
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<pre wrap="">So you are saying that 19K+ successful jobs was not enough to
counteract the 10K+ failed jobs from the early part of the
experiment?
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<pre wrap="">Yep. 19*1/5 = 3.8 < 10.
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<pre wrap="">Can this ratio (1:5) be changed?
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<pre wrap="">Yes. The scheduler has two relevant properties: successFactor (currently
0.1) and failureFactor (currently -0.5). The term "factor" is not used
formally, since these get added to the current score.
</pre>
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<pre wrap="">From this experiment, it would seem that the euristic is a slow
learner... maybe you ahve ideas on how to make it more quick to adapt
to changes?
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<pre wrap="">That could perhaps be done.
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<pre wrap="">In the context in which jobs are sent to non-busy workers, the system
would tend to produce lots of failed jobs if it takes little time
(compared to the normal run-time of a job) for a bad worker to fail a
job. This *IS* why the swift scheduler throttles in the beginning: to
avoid sending a large number of jobs to a resource that is broken.
</pre>
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<pre wrap="">But not the whole resource is broken...
</pre>
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<pre wrap="">No, just slightly more than 1/3 of it. At least that's how it appears
from the outside.
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<pre wrap="">But a failed job should not be given the same weight as a succesful
job, in my oppinion.
</pre>
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<pre wrap=""><!---->
Nope. I'd punish failures quite harshly. That's because the expected
behavior is for things to work. I would not want a site that fails half
the jobs to be anywhere near keeping a constant score.
</pre>
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That is fine, but you have a case (such as this one) in which this is
not ideal... how do you propose we adapt to cover this corner case? <br>
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<pre wrap=""> For example, it seems to me that you are giving the failed jobs 5
times more weight than succesful jobs, but in reality it should be the
other way around. Failed jobs usually will fail quickly (as in the
case that we have in MolDyn), or they will fail slowly (within the
lifetime of the resource allocation). On the other hand, most
successful jobs will likely take more time to complete that it takes
for a job to fail (if it fails quickly). Perhaps instead of
</pre>
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<pre wrap="">successFactor (currently
0.1) and failureFactor (currently -0.5)
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<pre wrap="">it should be more like:
successFactor: +1*(executionTime)
failureFactor: -1*(failureTime)
</pre>
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<pre wrap=""><!---->
That's a very good idea. Biasing score based on run-time (at least when
known). Please note: you should still fix Falkon to not do that thing
it's doing.
</pre>
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Its not clear to me this should be done all the time, Falkon needs to
know why the failure happened to decide to throttle!<br>
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<pre wrap="">
</pre>
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<pre wrap="">The 1 could of course be changed with some other weight to give
preference to successful jobs, or to failed jobs. With this kind of
strategy, the problems we are facing with throttling when there are
large # of short failures wouldn't be happening! Do you see any
drawbacks to this approach?
</pre>
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<pre wrap=""><!---->
None that are obvious. It's in fact a good thing if the goal is
performance, since it takes execution time into account. I've had manual
"punishments" for connection time-outs because they take a long time to
happen. But this time biasing naturally integrates that kind of stuff.
So thanks.
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<pre wrap="">that is the whole point here...
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<pre wrap="">This point comes because you KNOW how things work internally. All Swift
sees is 10K failed jobs out of 29K.
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<pre wrap="">anyways, I think this is a valid case that we need to discuss how to
handle, to make the entire Swift+Falkon more robust!
BTW, here is another experiment with MolDyn that shows the throttling
and this heuristic behaving as I would expected!
<a class="moz-txt-link-freetext" href="http://people.cs.uchicago.edu/~iraicu/research/docs/MolDyn/244-mol-failed/summary_graph.jpg">http://people.cs.uchicago.edu/~iraicu/research/docs/MolDyn/244-mol-failed/summary_graph.jpg</a>
Notice the queue lenth (blue line) at around 11K seconds dropped
sharply, but then grew back up. That sudden drop was many jobs
failing fast on a bad node, and the sudden growth back up was Swift
re-submitting almost the same # of jobs that failed back to Falkon.
</pre>
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<pre wrap="">That failing many jobs fast behavior is not right, regardless of whether
Swift can deal with it or not.
</pre>
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<pre wrap="">If its a machine error, then it would be best to not fail many jobs
fast...
however, if its an app error, you want to fail the tasks as fast as
possible to fail the entire workflow faster,
</pre>
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<pre wrap=""><!---->
But you can't distinguish between the two. The best you can do is assume
that the failure is a linear combination between broken application and
broken node. If it's broken node, rescheduling would do (which does not
happen in your case: jobs keep being sent to the worker that is not
busy, and that's the broken one). If it's a broken application, then the
way to distinguish it from the other one is that after a bunch of
retries on different nodes, it still fails. Notice that different nodes
is essential here.
</pre>
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Right, I could try to keep track of statistics on each node, and when
failures happen, try to determine if its a system wide failure (all
nodes reporting errors), or are the faiures isolated on a single (or
small set) node(s)... I'll have to think about how to do this
efficiently!<br>
<blockquote cite="mid:1187065878.4015.19.camel@blabla.mcs.anl.gov"
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<pre wrap="">
</pre>
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<pre wrap=""> so the app can be fixed and the workflow retried! For example, say
you had 1000 tasks (all independent), and had a wrong path set to the
app... with the current Falkon behaviour, the entire workflow would
likely fail within some 10~20 seconds of it submitting the first task!
However, if Falkon does some "smart" throttling when it sees failures,
its going to take time proportional to the failures to fail the
workflow!
</pre>
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<pre wrap=""><!---->
You're missing the part where all nodes fail the jobs equally, thus not
creating the inequality we're talking about (the ones where broken nodes
get higher chances of getting more jobs).
</pre>
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Right, maybe we can use this to distinguish between node failure and
app failure!<br>
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<pre wrap="">
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<pre wrap=""> Essentially, I am not a bit fan of throttling task dispatch due to
failed executions, unless we know why these tasks failed!
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<pre wrap=""><!---->
Stop putting exclamation marks after every sentence. It diminishes the
meaning of it!
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So you are going from playing with words to picking on my exclamation!
:)<br>
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<pre wrap="">
Well, you can't know why these tasks failed. That's the whole problem.
You're dealing with incomplete information and you have to devise
heuristics that get things done efficiently.
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But Swift might know why it failed, it has a bunch of STDOUT/STDERR
that it always captures! Falkon might capture the same output, but its
optional ;( Could these outputs not be parsed for certain well know
errors, and have different exit codes to mean different kinds of errors?<br>
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<pre wrap=""> Exit codes are not usually enough in general, unless we define our
own and the app and wrapper scripts generate these particular exit
codes that Falkon can intercept and interpret reliably!
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<pre wrap=""><!---->
That would be an improvement, but probably not a universally valid
assumption. So I wouldn't design with only that in mind.
</pre>
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But it would be an improvement over what we currently have...<br>
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<pre wrap="">
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<pre wrap="">Frankly I'd rather Swift not be the part
to deal with it because it has to resort to heuristics, whereas Falkon
has direct knowledge of which nodes do what.
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<pre wrap="">That's fine, but I don't think Falkon can do it alone, it needs
context and failure definition, which I believe only the application
and Swift could say for certain!
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<pre wrap=""><!---->
Nope, they can't. Swift does not meddle with semantics of applications.
They're all equally valuable functions.
Now, there's stuff you can do to improve things, I'm guessing. You can
choose not to, and then we can keep having this discussion. There might
be stuff Swift can do, but it's not insight into applications, so you'll
have to ask for something else.
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Any suggestions?<br>
<br>
Ioan<br>
<blockquote cite="mid:1187065878.4015.19.camel@blabla.mcs.anl.gov"
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<pre wrap="">
Mihael
</pre>
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<pre wrap="">Ioan
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<pre wrap=""><!---->
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