dataflow

I have never worked with TPL before so I was wondering whether this can be done with it: My application creates a gif image animation file from a lot of frames. I start with a list of Bitmap which represents the frames of the gif file and need to do the following for each frame: paint a number of text/bitmaps onto the frame crop the frame resize the frame reduce the image to 256 colors Obviously this process can be done in parallel for all the frames in the list but for each frame the order of steps needs to be the same. After that, I need to write all the frames to the gif file. Therefore all

I'm using the textbook "VHDL: Programming By Example" by Douglas L Perry, Fourth Edition. He gave an example of the Dataflow programming model in page 4: Code I: ENTITY mux IS PORT ( a, b, c, d : IN BIT; s0, s1 : IN BIT; x, : OUT BIT); END mux; ARCHITECTURE dataflow OF mux IS SIGNAL select : INTEGER; BEGIN select <= 0 WHEN s0 = ‘0’ AND s1 = ‘0’ ELSE 1 WHEN s0 = ‘1’ AND s1 = ‘0’ ELSE 2 WHEN s0 = ‘0’ AND s1 = ‘1’ ELSE 3; x <= a AFTER 0.5 NS WHEN select = 0 ELSE b AFTER 0.5 NS WHEN select = 1 ELSE c AFTER 0.5 NS WHEN select = 2 ELSE d AFTER 0.5 NS; END dataflow; Now in page 17, Code II LIBRARY

I have a requirement to make a scalable process. The process has mainly I/O operations with some minor CPU operations (mainly deserializing strings). The process query the database for a list of urls, then fetches data from these urls, deserilize the downloaded data to objects, then persist some of the data into crm dynamics and also to another database. Afterwards I need to update the first database which urls were processed. Part of the requirement is to make the parallelism degree configurable. Initially I thought to implement it via a sequence of tasks with await and limit the parallelism

I am trying to accomplish something like this: Batch PCollection in Beam/Dataflow The answer in the above link is in Java, whereas the language I'm working with is Python. Thus, I require some help getting a similar construction. Specifically I have this: p = beam.Pipeline (options = pipeline_options) lines = p | 'File reading' >> ReadFromText (known_args.input) After this, I need to create another PCollection but with a List of N rows of "lines" since my use case requires a group of rows. I can not operate line by line. I tried a ParDo Function using variables for count associating with the

As it currently stands, this question is not a good fit for our Q&A format. We expect answers to be supported by facts, references, or expertise, but this question will likely solicit debate, arguments, polling, or extended discussion. If you feel that this question can be improved and possibly reopened, visit the help center for guidance. I am looking for a Dataflow / Concurrent Programming API for Java. I know there's DataRush , but it's not free. What I'm interested in specifically is multicore data processing, and not distributed, which rules out MapReduce or Hadoop . Any thoughts? Thanks,

According to release notes of dataflow 2.X, IntraBundleParallelization is removed. Is there a way to control/increase parallelism of DoFns on dataflow 2.1.0 ? I was getting better performance when I used IntrabundleParallelization on 1.9.0 version of dataflow. It was removed because its implementation keeps a handle on the ProcessContext of a ProcessElement call after the call completes, and this is unsafe and not guaranteed to work. However, I agree that it was a useful abstraction, and it is unfortunate that we don't have a replacement yet. As a workaround, you can try the following: In your