Re: [gdal-dev] Re: JAVA API - Performance
Ivan
ivan.lucena at pmldnet.com
Wed Nov 18 16:05:24 EST 2009
Even,
I just got it to work with the new API today. That is great!
And just liike you said, the advantage is in usability not performance.
Thanks,
Ivan
> -------Original Message-------
> From: Even Rouault <even.rouault at mines-paris.org>
> Subject: Re: [gdal-dev] Re: JAVA API - Performance
> Sent: Nov 14 '09 17:32
>
> Selon Ivan <ivan.lucena at pmldnet.com>:
>
> I've commited new API that adds ReadRaster() and WriteRaster() methods that use
> the regular Java arrays (byte[], short[], int[], float[], double[]). See
> http://gdal.org/java
>
> On my PC,
> http://trac.osgeo.org/gdal/browser/trunk/gdal/swig/java/apps/GDALTestIO.java
> runs in about 20.3s for the ReadRaster()/WriteRaster() case, and in about 24.7s
> for the ReadRaster_Direct()/WriteRaster_Direct() case. Not a big advantage
> (which tends to not any advantage at all when run with the -server flag, as both
> run in about 21.3 s !), but regular Java arrays are a bit easier to use than
> ByteBuffer (especially that with Sun JVM 1.6, the array() method on ByteBuffer
> is not implemented).
>
> > Even,
> >
> > You are right. The point is how to take full advantage of the GDAL Java API
> > choosing the right
> > approach to deal with the raster buffer on the client side.
> >
> > Best regards,
> >
> > Ivan
> >
> > Even Rouault wrote:
> > > Selon Ivan <ivan.lucena at pmldnet.com>:
> > >
> > > Ivan,
> > >
> > > I'm not sure what you are really measuring if you compare a C++ code versus
> > its
> > > translation to Java code. I think it just reflects the known slowdown of
> > Java
> > > when doing intensive computations in comparison to native code. The 0.2
> > second
> > > difference between the regular array version and the ByteBuffer one is the
> > > interesting result, not the 1.2/1.0 second difference between C++ and Java.
> > >
> > >> Caio Simone,
> > >>
> > >> I just downloaded imageio-ext to check how it does that but it looks like
> > I
> > >> don't need to do that now, I can take you report instead. Thank you very
> > >> much. I will take a look on array pinning for a start.
> > >>
> > >> I translated the GDAL Proximity [1] code to Java and I timed both of then
> > >> with the same input, a 1024x1024 byte image with just one pixel as feature
> > at
> > >> the center of the image.
> > >>
> > >> It took 0.3 seconds in C++ and 1.5 seconds in Java!
> > >>
> > >> I then translated the buffers to regular arrays and it went down a little
> > >> bit, 1.3 seconds.
> > >>
> > >> It is still a big disadvantage. I believe that the buffer-to-buffer
> > >> translation is the guilt time waster in that case.
> > >>
> > >> [1] http://trac.osgeo.org/gdal/browser/trunk/gdal/alg/gdalproximity.cpp
> > >>
> > >> My best regards,
> > >>
> > >> Ivan
> > >>
> > >>> -------Original Message-------
> > >>> From: Simone Giannecchini <simone.giannecchini at geo-solutions.it>
> > >>> Subject: Re: [gdal-dev] Re: JAVA API - Performance
> > >>> Sent: Nov 10 '09 12:36
> > >>>
> > >>> Ciao Even,
> > >>> just wanted to add my 2 cents.
> > >>>
> > >>> As you know for the imageio-ext project we have been using the
> > >>> GDAL-JNI bindings (actually a modified version of them) for a while in
> > >>> order to allow Java users to leverage on GDAL using the ImageIO
> > >>> framework which standard in Java.
> > >>> This way we also enabled GeoTools and GeoServer to use GDAL as a
> > >> datasource.
> > >>> In the past I have done quite some performance tests to add some
> > >>> new/different methods to them and I can summarise our findings as
> > >>> follows:
> > >>>
> > >>> - DirectByteBuffer vs regular arrays -
> > >>> DBB is expensive to allocate but prevent the VM from performing copies
> > >>> when having to move data to and from java and native code since they
> > >>> live on the native space not on the java heap; On the other side the
> > >>> regular arrays are fast to allocate but they are "usually" copied when
> > >>> moved across from/to java and native code since the JVM cannot leave
> > >>> the native code mess with the java heap space since the garbage
> > >>> collector would not be very happy about that. I said "usually" since
> > >>> there is a technique called array pinning that we can suggest the JVM
> > >>> to use to avoid the copy of regular array; however this mechanism is
> > >>> not guaranteed to be implemented and/or to work on each call (same
> > >>> reason as above, GC is not happy about this technique).
> > >>>
> > >>> If you can pool the DBB and/or use a few large DBB, where the cost of
> > >>> the copy would overcome the cost of its creation then DBB are much
> > >>> better than regular arrays. As an instance I noticed that using when
> > >>> reading striped tiff files regular arrays where faster, but as the
> > >>> tile size increases (and therefore the cost of a copy overcomes the
> > >>> cost of a DBB creation) the DBB performs much better
> > >>>
> > >>> - DirectByteBuffer and the impact on some JVM -
> > >>> Now in the past we decided to stick with DBB and give
> > >>> GeoServer/GeoTools users the capability to retile data on the fly.
> > >>> However lately, during the WMS performance shootout we noticed on some
> > >>> linux machines JVm soldi crashed, not nice (means restarting the
> > >>> GeoServer!!!).
> > >>> We investigated a bit in depth and the problem was that somehow the
> > >>> JVM was failing to allocate some internal images during the rendering
> > >>> process and then dying with a NullPointerException (apparently the SUN
> > >>> Java2D engineers did not use to check for out of memory errors in the
> > >>> java native space). Well, what happens is that if you use too much of
> > >>> the Java native space for your own objects, it is likely that the JVM
> > >>> itself will start to malfunction (you can find articles on the web on
> > >>> the memory model of a Java process, I don't think I am good enough to
> > >>> explain it ) since it cannot allocate its own objects.
> > >>>
> > >>> In the end we decide to leave DBB and go back to regular arrays with
> > >>> array pinning. This ensured us robustness and we did not see much
> > >>> performance degradation (which means that array pinning in the end
> > >>> works). This has been implemented by modifying the SWIG bindings for
> > >>> GDAL in order to use a byte array instead of a DBB and then use
> > >>> ByteArray utils to convert between different native type (short, int,
> > >>> etc..).
> > >>>
> > >>> - Conclusion -
> > >>> We might want to spend some time in the mid term to contribute some of
> > >>> this work back (or probably provide funding), but anyway, it would be
> > >>> great to have the capability to switch between DBB and regular arrays
> > >>> since both have flaws.
> > >>> However atm if I were asked I would say to go with regular arrays as
> > >>> we do in the imageio-ext project.
> > >>>
> > >>> Ciao,
> > >>> Simone.
> > >>> -------------------------------------------------------
> > >>> Ing. Simone Giannecchini
> > >>> GeoSolutions S.A.S.
> > >>> Founder - Software Engineer
> > >>> Via Carignoni 51
> > >>> 55041 Camaiore (LU)
> > >>> Italy
> > >>>
> > >>> phone: +39 0584983027
> > >>> fax: +39 0584983027
> > >>> mob: +39 333 8128928
> > >>>
> > >>>
> > >>> http://www.geo-solutions.it
> > >>> http://geo-solutions.blogspot.com/
> > >>> http://simboss.blogspot.com/
> > >>> http://www.linkedin.com/in/simonegiannecchini
> > >>>
> > >>> -------------------------------------------------------
> > >>>
> > >>>
> > >>>
> > >>> On Tue, Nov 10, 2009 at 12:00 PM, Even Rouault
> > >>> <even.rouault at mines-paris.org> wrote:
> > >>> > Selon Ivan <ivan.lucena at pmldnet.com>:
> > >>> >
> > >>> > Ivan,
> > >>> >
> > >>> > thanks for your testing (CC'ing the list as it is of general
> > interest).
> > >>> > Actually, I also read on some sites that using ByteBuffer object
> > versus
> > >> regular
> > >>> > Java arrays is not always a win. Plus the fact that we must use a
> > direct
> > >> buffer
> > >>> > that has an extra allocation cost according to the Javadoc. So
> > >> ByteBuffer might
> > >>> > be interesting if you just want to pass big arrays between native
> > code,
> > >> for
> > >>> > example if you read an array from a dataset and then write it to
> > another
> > >> one
> > >>> > without accessing it from the Java side. When you mention that
> > accessing
> > >> through
> > >>> > the byte[] array was faster, did you get it with the array() method
> > >> instead ?
> > >>> > I'm wondering what the performance overhead of this call is.
> > >>> >
> > >>> > As ByteBuffer is not at all a requirement for the interface with the
> > >> native
> > >>> > code, it would be technically possible to add an alternative API that
> > >> would use
> > >>> > the regular Java array types.
> > >>> >
> > >>> > Would you mind opening an enhancement ticket about that ? Thanks
> > >>> >
> > >>> > Even
> > >>> >
> > >>> >> Even,
> > >>> >>
> > >>> >> I did some test with the GDAL Java API and some simple raster
> > >> operations
> > >>> >> like the GDAL Proximity algorthm and I noticed that the performance
> > >> while
> > >>> >> accessing pixels with <type>Buffer.get(i), <type>Buffer.put(i,value)
> > is
> > >> not
> > >>> >> as good as if you copy then to (or from) a "regular" array, like
> > >> float[],
> > >>> >> double[], integer[] and byte[].
> > >>> >>
> > >>> >> The reason for that is obvious, get() and put() are funtion calls and
> > >>> >> contains a lot of code for range check.
> > >>> >>
> > >>> >> If I understand it correctly, ByteBuffer is the ideal or maybe the
> > only
> > >>> >> way to get access to Buffers from C libraries thought a Java wrapper.
> > >> But
> > >>> >> do you it would be possible to incapsulate the buffer conversion at
> > the
> > >>> >> wrapper code so that users would be able to read and write direct to
> > >>> >> regular Java arrays?
> > >>> >>
> > >>> >> Just a suggestion,
> > >>> >>
> > >>> >> Ivan
> > >>> >>
> > >>> >
> > >>> >
> > >>> > _______________________________________________
> > >>> > gdal-dev mailing list
> > >>> > gdal-dev at lists.osgeo.org
> > >>> > http://lists.osgeo.org/mailman/listinfo/gdal-dev
> > >>> >
> > >>>
> > >
> > >
> > >
> >
> >
>
>
>
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