Thanks for the explanation! Very nice set of features. Looking forward to check it out myself :-)
2014-08-18 21:38 GMT+02:00 Gyula Fóra <gyula.f...@gmail.com>: > Hey, > > The simple reduce is like what you said yes. But there are also grouped > reduce which you can use by calling .groupBy(keyposition) and then reduce. > > Also there is reduce for windows: batchReduce and windowReduce batch gives > you a sliding window over a predefined number of records, and window reduce > gices you the same but by time. (also there are grouped versions of these) > > Cheers, > Gyula > > > On Mon, Aug 18, 2014 at 9:19 PM, Fabian Hueske <fhue...@apache.org> wrote: > > > Hi folks, > > > > great work! > > > > Looking at the example I have a quick question. What's the semantics of > the > > Reduce operator? I guess its not a window reduce. > > Is it backed by a hash table and every input tuple updates the hash table > > and returns the updated value? > > > > Cheers, Fabian > > > > > > 2014-08-18 20:53 GMT+02:00 Stephan Ewen <se...@apache.org>: > > > > > The streaming code is in "flink-addons", for new/experimental code. > > > > > > Documents should come over the next days/weeks, definitely before we > make > > > this part of the core. > > > > > > Right now, I would suggest to have a look at some of the examples, to > > get a > > > feeling for the addon, check for example this here: > > > > > > > > > https://github.com/apache/incubator-flink/tree/master/flink-addons/flink-streaming/flink-streaming-examples/src/main/java/org/apache/flink/streaming/examples/wordcount > > > > > > (The example reads a file for simplicity, but the project also provides > > > connectors for Kafka, RabbitMQ, ...) > > > > > >
