openml / openml/server-api

Move to a better update strategy for Elastic search

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#233 3 comments 0 reactions 0 assignees View on GitHub

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enhancement
Dominant language
Python
Stars
16
Forks
50
PR merge metrics
No merged PRs in 30d

Description

We want to eventually move away from the REST API having to trigger the elastic search update. For this we intend to consider tools like logstash. For example, if something is updated, we want to use logstash's monitoring to automatically trigger an ES update.

(We do not need to use logstash, but this seems like a decent option for now)

Since this is a bit complicated, I will try to do this in steps.

  1. Figure out ES indexes we maintain (and their fields) and what they are used for.
  2. Set up monitoring using logstash for the indexes
  3. Look at the current update strategy and use the monitoring from step 2 to automatically trigger an ES update

Contributor guide

No contributing guide indexed for this repository

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start by inventorying the Elasticsearch indexes maintained by the server API, including their fields and uses. Then review the current REST-triggered update strategy and consider the proposed Logstash monitoring approach; done means updates are automatically triggered without relying on the REST API.

Written by the indexing model from the issue text.

Assessment

Tech stack
elasticsearch, python
Domain
backend, databases, search
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
30/100

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