This is a really minor issue, but it confused me during testing.
The WindowOperator initial watermark is -1:
https://github.com/apache/flink/blob/master/flink-streaming-java/src/main/java/org/apache/flink/streaming/runtime/operators/windowing/WindowOperator.java#L136
Whereas TimestampsAndPunctua
I'm wondering whether the accumulator value maintained by a
FoldFunction is automatically checkpointed?
In general, but specifically when using the WindowedStream.apply
variant that takes a FoldFunction:
public DataStream apply(R initialValue,
FoldFunction foldFunction,
Ha, never mind, I realized I can just put the unique key into the
aggregate object maintained by the FoldFunction.
I'm still curious why RichWindowFunction (and RichFoldFunction) aren't
supported for Scala WindowedStream.apply.
Mike
On Thu, Mar 3, 2016 at 4:50 PM, Michael Radf
flink-streaming-java/src/main/java/org/apache/flink/streaming/api/windowing/triggers/EventTimeTrigger.java
>
> Kostas Kloudas worked on extending it, so maybe he could share his version
> of the trigger as well.
>
> Cheers,
> Aljoscha
>
> On 01 Mar 2016, at 18:35, Michael Radford
I'm evaluating Flink for a reporting application that will keep
various aggregates updated in a database. It will be consuming from
Kafka queues that are replicated from remote data centers, so in case
there is a long outage in replication, I need to decide what to do
about windowing and late data.
