feathr-ai/feathr

Stream features to offline storage

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#530 创建于 2022年7月29日

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 (4 评论) (0 反应) (1 负责人)Scala (1,929 star) (244 fork)batch import
good first issuescala

描述

We now support stream features to online table(Redis).

It's a popular ask by users.

The main code is added by this https://github.com/linkedin/feathr/pull/137. Existing user guide: https://github.com/linkedin/feathr/blob/f3d6ba57425d550f19730403115c0523f6c3ffe6/docs/how-to-guides/streaming-source-ingestion.md.

Difficulty: medium

贡献者指南

技术栈
scalaredis
领域
backenddata
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。
3
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。
1-2 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
Basic understanding of Feathr streaming ingestionFamiliarity with offline storage (e.g., HDFS, S3)Knowledge of Scala and Spark
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
Review the existing implementation for online storage (Redis) in PR #137 and the streaming source ingestion guide linked in the issue. Identify the code structure for offline sinks and understand the data writing pattern. Investigate how to adapt the streaming pipeline to write to offline storage like HDFS or S3, considering the format and consistency requirements. Check the current assignee's work and any comments for approach consensus.
Stream features to offline storage · feathr-ai/feathr#530 | Good First Issue