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https://issues.apache.org/jira/browse/IGNITE-11137?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Anton Dmitriev updated IGNITE-11137:
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Description:
Currently we have integration between machine learning and SQL implemented in
IGNITE-11138, IGNITE-11071 and IGNITE-11072. This functionality allows to work
with model storage in a straight forward way, user can save model without any
checking so that it might be overridden; model is extracted on each predict
call and it's very inefficient. The goal of this task is to:
* Add existence checking to model saving functionality and meaningful exception
messages;
* Add model caching into predict call so that model is not required to be
deserialized on each call.
was:
We want to wrap Model storage by IgniteModelStorage.
This wrapper should:
* hide all serialization/deserialization activities for models
* check args and work with paths which not exist yet
* cache used models from storage
> [ML] IgniteModelStorage
> -----------------------
>
> Key: IGNITE-11137
> URL: https://issues.apache.org/jira/browse/IGNITE-11137
> Project: Ignite
> Issue Type: Improvement
> Components: ml
> Reporter: Yury Babak
> Assignee: Anton Dmitriev
> Priority: Major
> Fix For: 2.8
>
>
> Currently we have integration between machine learning and SQL implemented in
> IGNITE-11138, IGNITE-11071 and IGNITE-11072. This functionality allows to
> work with model storage in a straight forward way, user can save model
> without any checking so that it might be overridden; model is extracted on
> each predict call and it's very inefficient. The goal of this task is to:
> * Add existence checking to model saving functionality and meaningful
> exception messages;
> * Add model caching into predict call so that model is not required to be
> deserialized on each call.
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