I guess the use cases as documented look really compelling. There might be more comments from code review perspective and below is more from a use case perspective only.
I was wondering if you have any latency measurements for the tests you ran. If the image processing calls ( in the process function overridden from the Toolkit class ) are time consuming it might not be an ideal use case for a streaming engine? A very old "blog" (2012) talks about latencies anywhere between tens of milliseconds to almost a second depending on the use case and image size. Of course there were hardware improvements and those numbers might no longer hold good and hence the question (of course the latencies depend on hardware being used as well ) This brings me to the next question in general about Apex to the community : what is considered an acceptable tolerance level in terms of latencies for streaming compute engine like Apex. Is there a way to tune the acceptable tolerance level depending on the use case ? I keep reading from the mailing lists that the aspect of tuple processing is part of the main thread and hence should be as fast as possible. Regards Ananth > On 12 May 2017, at 9:05 pm, Aditya gholba <adi...@datatorrent.com> wrote: > > Hello, > I have been working on an image processing library for Malhar and few of > the operators are ready. I would like to merge them in Malhar contrib. You > can read about the operators and the applications I have created so far > here. > <https://docs.google.com/document/d/19OrqHJ_QzbuB0XZ4bzdQ9yjN2dGfDhsuMX6XUjDpqYw/edit> > > Link to my GitHub <https://github.com/adiv2/imIO4> > > All suggestions and opinions are welcome. > > > Thanks, > Aditya.
