[OAK-6571] Prefetching the DocumentStore cache using machine learning

• Type: Story
• Status: Open
• Priority: Major
• Resolution: Unresolved
• Component/s: cache, documentmk
• Assignee: Unassigned
• Reporter: Tomek Rękawek
• Created: 22/Aug/17 11:45
• Updated: 08/Oct/19 15:22

Description

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.patch contains:

• a proposal of interface which may be used to join these two parts,
• a very early integration with the DocumentMK,
• a naive implementation of the algorithm, which simply logs the request sequences.

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
• Hidden Markov Model