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From <jaroslav.s...@accenture.com>
Subject RE: ?
Date Fri, 16 Oct 2015 13:59:50 GMT
Hello Ivan

Many thanks for great news. We start to prototype ☺
jaro

From: Ivan Veselovskiy [mailto:iveselovskiy@gridgain.com]
Sent: Thursday, October 15, 2015 7:47 PM
To: user@ignite.apache.org
Subject: Re: ?

Hi, Jaroslav,
In my understanding, with Ignite the answers to all the questions are in general positive.
Possibly one of the most challenging tasks there is to adjust cache affinity function to achieve
best data/data & data/compute collocation to gain the best performance.
Documentation on affinity collocation can be found there: https://apacheignite.readme.io/docs/affinity-collocation
.

On Thu, Oct 15, 2015 at 7:30 PM, <jaroslav.saxa@accenture.com<mailto:jaroslav.saxa@accenture.com>>
wrote:
Hello Ignite users,

Let me share my exaltation from things you’re doing.
Let me explain my problem/challenge – sorry I had not time to deeply dive into prototyping
yet and I have to make decision very quickly so I use this way to ask general  questions which
could help me to decide whether to include Ignite into short list for following prototyping
of Poc for our solution.

I really appreciate if anybody could respond  to my maybe un-competent queries (Q).

Our challenge:


•       We have files “BLOBs” which represents binary vectors.

•       We’d like to load them into Ignite data grid as distributed key values c

•       We are up to implement capability where the service [cid:image001.png@01D1082B.B8BE7300]
 (our service layer) is getting binary vector (in the same format as stored in file system
-> Ignite data grid) and we need to

o   perform “search” in our gallery which vector is most close to vector on the input.
To calculate the distance (or probability of match) between 2 vectors we have encapsulated
in external lib(jar) which basically expose 1:1 match (vector1, vector2) capability. So we
need to perform 1:1 match over all vectors we have stored. As the number of vectors in the
galley is huge and number of requests to compare is also impressive – this is tack for memory
computing.

•       What’s more, there is service [cid:image002.png@01D1082B.B8BE7300] which continuously
adds new records into our gallery

Can you please confirm that following setup/approach with Ignite would work?

•       Will we  be able to load distributed data [cid:image003.png@01D1082B.B8BE7300] from
file storage into grid nodes in distributed manner?

•       Will we be able to from service [cid:image001.png@01D1082B.B8BE7300] trigger on
every grid node computation function [cid:image004.png@01D1082B.B8BE7300]  which will :

o   Go over all data (vectors) which are distributed on the current node [cid:image005.png@01D1082B.B8BE7300]
?

o   Call external lib be called from computation function [cid:image004.png@01D1082B.B8BE7300]

o   Can we pass parameter to computation function [cid:image004.png@01D1082B.B8BE7300]

o   Can computation function be deployed on nodes w/o needing to broadcast it from service
(computation trigger) ?

o   Is there any support from ignite to run computation function [cid:image004.png@01D1082B.B8BE7300]
in parallel on certain node?

•       We will be able to update data on computation nodes from service [cid:image002.png@01D1082B.B8BE7300]
(add new records), so new requests from service [cid:image001.png@01D1082B.B8BE7300] will
be able to process updated gallery of vectors in memory

Thank you so MUCH
jaro

[cid:image006.png@01D1082B.B8BE7300]

Jaroslav Saxa
Accenture – Technology Architecture
Plynarenska 7/C, 829 01 Bratislava
Mobile: +421-904-706113
Email: jaroslav.saxa@accenture.com<mailto:jaroslav.saxa@accenture.com>


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