[Rock-dev] Questions Regarding Typelib

Alexander Duda Alexander.Duda at dfki.de
Mon Jun 9 19:46:45 CEST 2014


Am 09.06.2014 um 19:08 schrieb Janosch Machowinski <Janosch.Machowinski at dfki.de>:

> Seriously, got to hell.
> You know what s the problem with you, whenever one is motivated,
> to fix a problem with rock and it not done the way you think it is the 
> best, you start bashing around. Btw, a correct response would be, great,
> you looked into it and made it faster, go on.

Seriously, it is great that you are looking into it. But you are also asking other people to help you costing them quite a bit of their free time. Therefore, I think it is also fair for them to criticize specific steps which might have little impact on the overall replay speed.

At the beginning, you were complaining about the replay speed and not about the loading and alignment which you are currently improving. And like Sylvain said. I also do not believe that the replay speed is so slow because of the current pocolog implementation. It is slow because of how rock-replay works (at least one callback per sample etc.). 

Anyway, I am a bit puzzled why you have different number of samples for the same log files.

Greets Alex


> 
> A lot of people think that the log replay tools are slow as hell, and that 
> it is annoying to wait 20 seconds every time rock replay starts up.
> 
> Just to finish this, it is slow as hell, I just did tests with logdata I generated
> using Mars :
> time rock-replay ~/Arbeit/asguard/bundles/asguard/logs/current
> pocolog.rb[INFO]: building index ...
> pocolog.rb[INFO]: done
> pocolog.rb[INFO]: building index ...
> pocolog.rb[INFO]: done
> pocolog.rb[INFO]: building index ...
> pocolog.rb[INFO]: done
> pocolog.rb[INFO]: building index ...
> pocolog.rb[INFO]: done
> pocolog.rb[INFO]: building index ...
> pocolog.rb[INFO]: done
> Aligning streams. This can take a long time
> pocolog.rb[INFO]: Got 77 streams with 295166 samples
> pocolog.rb[INFO]: Stream Aligner index created
> 
> real    0m20.860s
> user    0m19.605s
> sys     0m1.008s
> 
> time ./multiIndexer ~/Arbeit/asguard/bundles/asguard/logs/current/*.log
> Building multi file index 
>  100% Done
> Processed 295169 of 295169 samples 
> 
> real    0m1.089s
> user    0m0.780s
> sys     0m0.304s
> 
> This is a hug speedup, and it is worth it. 
>     Janosch
> 
> 
> On 09.06.2014 17:04, Sylvain Joyeux wrote:
>> 
>> Created a dataset of one minute with 100 streams. Each stream is at 100Hz, so that's 600k samples. It took 4.6 seconds to generate the index and 0.8 seconds to load the file index (from warm cache, so with probably little I/O overhead).
>> How long did the stream alignment take ? This is the part were usually the problem is, as you can't get better than
>> O((log n)*s) there, were n is the number of streams and s the amount of samples.
>> ??? What are you talking about ? This is only the asymptotic curve. The alignment takes 4.6 seconds.
>> 
>> 
>> C++ *is* faster. Of course it is. From what I see, not fast enough to justify the refactoring that you are proposing.
>> Ohh yes, it does. Recently I did a log of localization debugging. You can't jump data in this case (and a lot of other usecases too) which means you have to replay the whole logstream. If the replay is double as fast, it means you need half
>> the time for debugging. So in my eyes it is 100% worth the effort.
>> Except that making twice as fast the part that is currently taking 10% of the replay time only will make the overall process 5% faster. Even making it 100 times faster will only save 9%. This is from what I see what you are attempting, as what takes the most time is I/O and typelib demarshalling. 
>> 
>> In other words: you are attempting to optimize something without having done any profiling. This is a cardinal sin.
>>  
>> 
>> Again, you are *not* giving the right measurements. Speed factors and durations are meaningless if we don't know how many samples each stream has, and how long each stream lasts. Just "it is 24x times faster" means nothing.
>> You got the C++ implementation, just run multiIndexTester on your testdata and compare the results.
>> 
>> Sylvain 
> 
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Dipl.-Ing. Alexander Duda
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