Chronon, Airbnb的ML特征平台，现已开源

A feature platform that offers observability and management tools, allows ML practitioners to use a variety of data sources, while handling the complexity of data engineering, and provides low latency streaming.

一个提供可观察性和管理工具的特征平台，允许机器学习从业者使用各种数据源，同时处理数据工程的复杂性，并提供低延迟的流式处理。

By: Varant Zanoyan, Nikhil Simha Raprolu

By: Varant Zanoyan, Nikhil Simha Raprolu

Chronon allows ML practitioners to use a variety of data sources as inputs to feature transformations. It handles the complexity of data plumbing, such as batch and streaming compute, provides low latency serving, and offers a host of observability and management tools.

Chronon允许机器学习从业者使用各种数据源作为特征转换的输入。它处理数据管道的复杂性，如批处理和流处理计算，提供低延迟的服务，并提供一系列的可观察性和管理工具。

Airbnb is happy to announce that Chronon, our ML Feature Platform, is now open source. Join our community Discord channel to chat with us.

Airbnb很高兴宣布 Chronon，我们的ML特征平台，现在是开源的。加入我们的 社区Discord频道 与我们交流。

We’re excited to be making this announcement along with our partners at Stripe, who are early adopters and co-maintainers of the project.

我们很高兴能与我们的合作伙伴Stripe一起宣布这一消息，他们是该项目的早期采用者和共同维护者。

This blog post covers the main motivation and functionality of Chronon. For an overview of core concepts in Chronon, please see this previous post.

本博客文章介绍了Chronon的主要动机和功能。有关Chronon中核心概念的概述，请参阅此前的文章。

Background

背景

We built Chronon to relieve a common pain point for ML practitioners: they were spending the majority of their time managing the data that powers their models rather than on modeling itself.

我们创建Chronon是为了解决机器学习从业者常见的痛点：他们花费大部分时间来管理驱动模型的数据，而不是进行建模本身。

Prior to Chronon, practitioners would use one of the following two approaches:

在Chronon之前，从业者可以使用以下两种方法之一：

1. Replicate offline-online: ML practitioners train the model with data from the data warehouse, then figure out ways to replicate those features in the online environment. The benefit of this approach is that it allows practitioners to utilize the full data warehouse, both the data sources and powerful tools for large-scale data transformation. The downside is that this leaves no...