We are looking for a consultant or contractor that can come onsite to our 
Ogden, Utah location in the US, to help with a Kafka set up and maintenance 
project.  What we need is someone with the knowledge and experience to build 
out the Kafka environment from scratch.  

We are thinking they would need to be onsite for 6-12 months  to set it up, and 
mentor some of our team so they can get up to speed to do the maintenance once 
the contractor is gone.  If anyone has the experience setting up Kafka from 
scratch in a Linux environment, maintain node clusters, and help train others 
on the team how to do it, and you are interested in a long term project working 
at the client site, I would love to start up  a discussion, to see if we could 
use you for the role. 

I would also be interested in hearing about any consulting firms that might 
have resources that could help with this role. 

Matt Stone


-----Original Message-----
From: Matt Daum [mailto:m...@setfive.com] 
Sent: Friday, March 2, 2018 1:11 PM
To: users@kafka.apache.org
Subject: Re: Kafka Setup for Daily counts on wide array of keys

Actually it looks like the better way would be to output the counts to a new 
topic then ingest that topic into the DB itself.  Is that the correct way?

On Fri, Mar 2, 2018 at 9:24 AM, Matt Daum <m...@setfive.com> wrote:

> I am new to Kafka but I think I have a good use case for it.  I am 
> trying to build daily counts of requests based on a number of 
> different attributes in a high throughput system (~1 million 
> requests/sec. across all  8 servers).  The different attributes are 
> unbounded in terms of values, and some will spread across 100's of 
> millions values.  This is my current through process, let me know 
> where I could be more efficient or if there is a better way to do it.
>
> I'll create an AVRO object "Impression" which has all the attributes 
> of the inbound request.  My application servers then will on each 
> request create and send this to a single kafka topic.
>
> I'll then have a consumer which creates a stream from the topic.  From 
> there I'll use the windowed timeframes and groupBy to group by the 
> attributes on each given day.  At the end of the day I'd need to read 
> out the data store to an external system for storage.  Since I won't 
> know all the values I'd need something similar to the KVStore.all() 
> but for WindowedKV Stores.  This appears that it'd be possible in 1.1 
> with this
> commit: https://github.com/apache/kafka/commit/
> 1d1c8575961bf6bce7decb049be7f10ca76bd0c5 .
>
> Is this the best approach to doing this?  Or would I be better using 
> the stream to listen and then an external DB like Aerospike to store 
> the counts and read out of it directly end of day.
>
> Thanks for the help!
> Daum
>

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