feathr-ai/feathr

API to query features materialized to offline

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#289 opened on 2022年5月20日

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

説明

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)

コントリビューターガイド

技術スタック
pythonscala
領域
apidatabackend
Issue 種別
feature
難度新しい貢献者にとっての実装難度です。1 は非常に小さな変更、5 は専門的な作業です。
4
推定時間経験ある貢献者が調査、実装、テスト、pull request 準備にかけるおおよその時間範囲です。
3-5 days
活動状況Issue が今どれだけ取り組みやすいかを示します。新しい、活発、古い、ブロック中、またはメンテナー入力待ちなどです。
stale
明確さ期待される変更、受け入れ条件、次の手順がどれだけ明確かを示します。
mostly clear
前提条件
Feathr online API knowledgeDelta Lake understandingPython client development
初心者向け度初回貢献者にどれだけ取り組みやすいかを 1-100 で推定したスコアです。
30
調査方針
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