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From Martin Neumann <mneum...@sics.se>
Subject Re: Event time in Flink streaming
Date Tue, 08 Sep 2015 18:20:43 GMT

I want to give TimeTriggerPolicy a try and see how much of a problem it
will be in this use case. Is there any example on how to use it? I looked
at the API descriptions but I'm confused now.

cheers Martin

On Fri, Aug 28, 2015 at 5:35 PM, Martin Neumann <mneumann@sics.se> wrote:

> The stream consists of logs from different machines with synchronized
> clocks. As a result timestamps are not strictly increasing but there is a
> bound on how much out of order they can be. (One aim is to detect events go
> out of order more then a certain amount indication some problem in the
> system setup)
> I will look at the example policies and see if I can find a way to make it
> work with 0.9.
> I am aware of Google Dataflow and the discussion on Flink, though I just
> recently learned more about the field, so I didn't have to much useful to
> say. This might change if I get some more experience with the usecase I'm
> working on.
> cheers Martin
> On Fri, Aug 28, 2015 at 5:06 PM, Aljoscha Krettek <aljoscha@apache.org>
> wrote:
>> Hi Martin,
>> the answer depends, because the current windowing implementation has some
>> problems. We are working on improving it in the 0.10 release, though.
>> If your elements arrive with strictly increasing timestamps and you have
>> parallelism=1 or don't perform any re-partitioning of data (which a
>> groupBy() does, for example) then what Matthias proposed works for you. If
>> not then you can get intro problems with out-of-order elements and windows
>> will be incorrectly determined.
>> If you are interested in what we are working on for 0.10, please look at
>> the design documents here
>> https://cwiki.apache.org/confluence/display/FLINK/Streams+and+Operations+on+Streams
>> here
>> https://cwiki.apache.org/confluence/display/FLINK/Time+and+Order+in+Streams.
>> The basic idea is to make windows work correctly when elements arrive not
>> ordered by timestamps. For this we want use watermarks as popularized, for
>> example, by Google Dataflow.
>> Please ask if you have questions about this or are interested in joining
>> the discussion (the design as not yet finalized, both API and
>> implementation). :D
>> Cheers,
>> Aljoscha
>> P.S. I have some proof-of-concept work in a branch of mine, if you
>> interested in my work there I could give you access to it.
>> On Fri, 28 Aug 2015 at 16:11 Matthias J. Sax <
>> mjsax@informatik.hu-berlin.de> wrote:
>>> Hi Martin,
>>> you need to implement you own policy. However, this should be be
>>> complicated. Have a look at "TimeTriggerPolicy". You just need to
>>> provide a "Timestamp" implementation that extracts you ts-attribute from
>>> the tuples.
>>> -Matthias
>>> On 08/28/2015 03:58 PM, Martin Neumann wrote:
>>> > Hej,
>>> >
>>> > I have a stream of timestamped events I want to process in Flink
>>> streaming.
>>> > Di I have to write my own policies to do so, or can define time based
>>> > windows to use the timestamps instead of the system time?
>>> >
>>> > cheers Martin

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