Staying behind doesn't imply one is better than the other and I didn't mean that in any way but I fail to see how an abstraction framework like Beam can stay ahead of the underlying execution engines?
For example, If a new feature is added into the underlying execution engine that doesn't fit the interface of Beam or breaks then I would think the interface would need to be changed. Another example would say the underlying execution engines take different kind's of parameters for the same feature then it isn't so straight forward to come up with an interface since there might be very little in common in the first place so, in that sense, I fail to see how Beam can stay ahead. "Of course the API itself is Spark-specific, but it borrows heavily (among other things) on ideas that Beam itself pioneered long before Spark 2.0" Good to know. "one of the things Beam has focused on was a language portability framework" Sure but how important is this for a typical user? Do people stop using a particular tool because it is in an X language? I personally would put features first over language portability and it's completely fine that may not be in line with Beam's priorities. All said I can agree Beam focus on language portability is great. On Tue, Apr 30, 2019 at 2:48 AM Maximilian Michels <m...@apache.org> wrote: > > I wouldn't say one is, or will always be, in front of or behind another. > > That's a great way to phrase it. I think it is very common to jump to > the conclusion that one system is better than the other. In reality it's > often much more complicated. > > For example, one of the things Beam has focused on was a language > portability framework. Do I get this with Flink? No. Does that mean Beam > is better than Flink? No. Maybe a better question would be, do I want to > be able to run Python pipelines? > > This is just an example, there are many more factors to consider. > > Cheers, > Max > > On 30.04.19 10:59, Robert Bradshaw wrote: > > Though we all certainly have our biases, I think it's fair to say that > > all of these systems are constantly innovating, borrowing ideas from > > one another, and have their strengths and weaknesses. I wouldn't say > > one is, or will always be, in front of or behind another. > > > > Take, as the given example Spark Structured Streaming. Of course the > > API itself is spark-specific, but it borrows heavily (among other > > things) on ideas that Beam itself pioneered long before Spark 2.0, > > specifically the unification of batch and streaming processing into a > > single API, and the event-time based windowing (triggering) model for > > consistently and correctly handling distributed, out-of-order data > > streams. > > > > Of course there are also operational differences. Spark, for example, > > is very tied to the micro-batch style of execution whereas Flink is > > fundamentally very continuous, and Beam delegates to the underlying > > runner. > > > > It is certainly Beam's goal to keep overhead minimal, and one of the > > primary selling points is the flexibility of portability (of both the > > execution runtime and the SDK) as your needs change. > > > > - Robert > > > > > > On Tue, Apr 30, 2019 at 5:29 AM <kanth...@gmail.com> wrote: > >> > >> Ofcourse! I suspect beam will always be one or two step backwards to > the new functionality that is available or yet to come. > >> > >> For example: Spark Structured Streaming is still not available, no CEP > apis yet and much more. > >> > >> Sent from my iPhone > >> > >> On Apr 30, 2019, at 12:11 AM, Pankaj Chand <pankajchanda...@gmail.com> > wrote: > >> > >> Will Beam add any overhead or lack certain API/functions available in > Spark/Flink? >
