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From Mich Talebzadeh <mich.talebza...@gmail.com>
Subject Re: Streaming Data
Date Tue, 09 Apr 2019 20:48:41 GMT
use Spark streaming to receive topics from Kafka and process through some
kind of rule engine based on incoming tickers.

Sound like a variation of Lambda architecture. You have the batch layer
sorted out and now looking for speed layer with some form of dashboard.

Something similar to below but much simplified


[image: image.png]
HTH


Dr Mich Talebzadeh



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On Tue, 9 Apr 2019 at 21:26, Nick Torenvliet <natorenvliet@gmail.com> wrote:

> Hi all,
>
> Just looking for some general guidance.
>
> We have a kafka -> druid pipeline we intend to use in an industrial setting
> to monitor process data.
>
> Our kafka system recieves messages on a single topic.
>
> The messages are {"timestamp": yy:mm:ddThh:mm:ss.mmm, "plant_equipment_id":
> "id_string", "sensorvalue": float}
>
> For our POC there are about 2000 unique plant_equipment ids, this will
> quickly grow to 20,000.
>
> The kafka topic streams into druid
>
> We are building some node.js/react browser based apps for analytics and
> real time stream monitoring.
>
> We are thinking that for visualizing historical data sets we will hit druid
> for data.
>
> For real time streaming we are wondering what our best option is.
>
> One option is to just hit druid semi regularly and update the on screen
> visualization as data arrives from there.
>
> Another option is to stream subset of the topics (somehow) from kafka using
> some streams interface.
>
> With all the stock ticker apps out there, I have to imagine this is a
> really common use case.
>
> Anyone have any thoughts as to what we are best to do?
>
> Nick
>

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