Hi Peter, I just omitted the filter part. Sorry for that.
Actually, as the javadoc explained, by default a DataStream with iteration will never terminate. That's because in a stream environment with iteration, the operator will never know whether the feedback stream has reached its end (though the data source is terminated, *there may be unknowable subsequent data*) and that's why it needs a timeout value to make the judgement, just like many other function calls in network connection. In other words, you know the feedback stream will be empty in the future, but the operator doesn't. Thus we provide it a maximum waiting time for the next record. Internally, this mechanism is implemented via a blocking queue (the related code can be found here <https://github.com/apache/flink/blob/12b4185c6c09101b64e12a84c33dc4d28f95cff9/flink-streaming-java/src/main/java/org/apache/flink/streaming/runtime/tasks/StreamIterationHead.java#L80> ). Hope everything is considered this time : ) Best, Xingcan On Sat, Sep 2, 2017 at 10:08 PM, Peter Ertl <peter.e...@gmx.net> wrote: > > Am 02.09.2017 um 04:45 schrieb Xingcan Cui <xingc...@gmail.com>: > > In your codes, all the the long values will subtract 1 and be sent back to > the iterate operator, endlessly. > > > > Is this true? shouldn't > > val iterationResult2 = env.generateSequence(1, 4).iterate(it => { > (it.filter(_ > 0).map(_ - 1), it.filter(_ > 0).map(_ => 'y')) // dump > meaningless 'y' chars just to do anything > }) > iterationResult2.print() > > > produce the following _feedback_ streams? > > initial input to #iterate(): [1 2 3 4] > > iteration #1 : [1 2 3] > iteration #2 : [1 2] > iteration #3 : [1] > iteration #4 : [] => empty feedback stream => cause termination? (which > actually only happens when setting a timeout value) > > Best regards > Peter > > >
