feathr-ai/feathr

API to query features materialized to offline

Open

#289 创建于 2022年5月20日

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 (3 评论) (2 反应) (0 负责人)Scala (1,929 star) (244 fork)batch import
good first issue

描述

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)

贡献者指南

技术栈
pythonscala
领域
apidatabackend
议题类型
feature
难度面向新贡献者的预计实现难度，1 表示很小改动，5 表示专家级工作。
4
预计时间有经验贡献者完成调查、实现、测试并准备 pull request 的粗略时间范围。
3-5 days
活动状态议题当前的可参与程度：新鲜、活跃、陈旧、阻塞或等待维护者输入。
stale
清晰度议题是否清楚说明期望改动、验收标准和下一步。
mostly clear
前置要求
Feathr online API knowledgeDelta Lake understandingPython client development
新手友好度1-100 的估计分数，表示该议题对首次贡献者的友好程度。
30
研究方向
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.