feathr-ai/feathr

API to query features materialized to offline

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#289 opened on May 20, 2022

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 (3 comments) (2 reactions) (0 assignees)Scala (1,929 stars) (244 forks)batch import
good first issue

Description

Today for features materialized to online(Redis), we provide a simple API to query it.

Some users may want to materialize features to offline store(delta lake) and query it later on. This API doesn't exist yet.

We should add this API so users can query features generated by Feathr.

The API should be consistent with online API:

    res = client.get_online_features(online_test_table, '265', [
                                     'f_location_avg_fare', 'f_location_max_fare'])

    res = client.multi_get_online_features(online_test_table,
                                           ['239', '265'],
                                           ['f_location_avg_fare', 'f_location_max_fare'])

The API can be like(this is still up for discussion):

feathrClient.getFeatures([f1, f2], feature_table)

feathrClient.joinFeature([f1, f2], feature_table, observation_table)

Contributor guide

Tech stack
pythonscala
Domain
apidatabackend
Issue type
feature
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
4
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
3-5 days
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
stale
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
mostly clear
Prerequisites
Feathr online API knowledgeDelta Lake understandingPython client development
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
30
Research direction
The issue proposes adding two new APIs to the Python client: getFeatures and joinFeature. The implementation should follow the pattern of the existing online API (get online features, multi get online features). Look at the Feathr client source code, particularly the online query implementation, to understand the required remote calls. Since the offline store is Delta Lake, incorporate Spark or Delta Lake reading logic. Review the discussion in the issue comments for additional requirements.
API to query features materialized to offline · feathr-ai/feathr#289 | Good First Issue