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https://issues.apache.org/jira/browse/OAK-6571?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16136870#comment-16136870
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Thomas Mueller commented on OAK-6571:
-------------------------------------
I wonder if we easily capture "relative" requests, in the above example
"/content/site/jcr:content", then "./left-column", "./item1", "../item2",
versus just capturing absolute paths. Sure, it's possible to "reverse engineer"
the relative paths from the absolute paths, but it might be less exact to do
that. Maybe the RNN will detect the (prefix-) pattern automatically, but let's
see.
> Prefetching the DocumentStore cache using machine learning
> ----------------------------------------------------------
>
> Key: OAK-6571
> URL: https://issues.apache.org/jira/browse/OAK-6571
> Project: Jackrabbit Oak
> Issue Type: Story
> Components: cache, documentmk
> Reporter: Tomek Rękawek
> Fix For: 1.8
>
> Attachments: OAK-6571-api.patch
>
>
> The idea is that we can analyse the series of requests made by the
> DocumentStore, eg.:
> /content/site/jcr:content
> /content/site/jcr:content/left-column
> /content/site/jcr:content/left-column/item1
> /content/site/jcr:content/left-column/item2
> to predict the future requests and prefetch them. This way we can limit the
> number of required requests, the connection latency, etc.
> In order to group the requests together, we can use the thread name as a
> common property. For instance, if Oak is used with Sling, then a single HTTP
> request usually is served by a single thread and it's name contains the HTTP
> request line.
> Implementing this story will require intercepting the MongoDB/RDB requests
> made by the DocumentStore and preparing an algorithm analysing and predicting
> the future calls. The attached patch [^OAK-6571-api.patch] contains a
> proposal of interface which may be used to join these two parts.
> We can start with a simple algorithm trying to exact match the current
> requests to the already existing sequence and it's not enough look for more
> sophisticated mechanism.
> Resources:
> * [Intelligent web caching using machine learning
> methods|http://www.nnw.cz/doi/2011/NNW.2011.21.025.pdf]
> * [Hidden Markov Model|https://en.wikipedia.org/wiki/Hidden_Markov_model]
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