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From Fabian Hueske <fhue...@gmail.com>
Subject Re: Enriching DataStream using static DataSet in Flink streaming
Date Wed, 04 Apr 2018 13:42:25 GMT

This type of applications are not super well supported by Flink, yet. The
missing feature is on the roadmap and called Side Inputs [1].
There are (at least) two alternatives but both have some drawbacks:

1) Ingest the static data set as regular DataStream, keyBy the static and
the actual stream, connect them, and join the results in a CoFlatMap or
CoProcessFunction. The problem with this approach is that you cannot
control in a Co*Function which input to consume. Therefore, you will
consume records from the stream that you want to enrich before you consumed
all records of the static data set. You can deal with the problem, by
either putting the records to enrich into state and join them when the
static record arrived or you discard the data.
2) You load the static data set in the open() method of a
RichFlatMapFunction. The problem here is that the data is not partitioned
by user id. Each parallel task would need to hold a full copy of the static
data set.

Best, Fabian


2018-04-04 9:41 GMT+02:00 vijay kansal <vijaykansal3@gmail.com>:

> Hi All
> I am writing a Flink streaming program in which I need to enrich a
> DataStream of user events using some static data set (information base, IB).
> For E.g. Let's say we have a static data set of buyers and we have an
> incoming clickstream of events, for each event we want to add a boolean
> flag indicating whether the doer of the event is a buyer or not.
> An ideal way to achieve this would be to partition the incoming stream by
> user id, have the buyers set available in a DataSet partitioned again by
> user id and then do a look up for each event in the stream into this
> DataSet.
> Since Flink does not allow using DataSets in a streaming program, how can
> I achieve the above ?
> Another option could be to use Managed Operator State to store buyers set,
> but how can I keep this state distributed by user id so as to avoid network
> i/o in individual event look ups ? In case of memory state backend, does
> state remain distributed by some key, or is it replicated across all
> operator subtasks ?
> What is the right design pattern to achieve the above enriching
> requirement in a Flink streaming program ?
> Thanks
> Vijay Kansal
> Software Development Engineer
> LimeRoad

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