介绍 Netflix 的 TimeSeries 数据抽象层

By Rajiv Shringi, Vinay Chella, Kaidan Fullerton, Oleksii Tkachuk, Joey Lynch

由Rajiv Shringi，Vinay Chella，Kaidan Fullerton，Oleksii Tkachuk，Joey Lynch撰写

Introduction

介绍

As Netflix continues to expand and diversify into various sectors like Video on Demand and Gaming, the ability to ingest and store vast amounts of temporal data — often reaching petabytes — with millisecond access latency has become increasingly vital. In previous blog posts, we introduced the Key-Value Data Abstraction Layer and the Data Gateway Platform, both of which are integral to Netflix’s data architecture. The Key-Value Abstraction offers a flexible, scalable solution for storing and accessing structured key-value data, while the Data Gateway Platform provides essential infrastructure for protecting, configuring, and deploying the data tier.

随着Netflix不断扩大和多元化进入诸如视频点播和游戏等各个领域，能够摄取和存储大量时间数据（通常达到PB级）并具有毫秒级访问延迟的能力变得越来越重要。在之前的博客文章中，我们介绍了键值数据抽象层和数据网关平台，它们都是Netflix数据架构的重要组成部分。键值抽象提供了一种灵活、可扩展的解决方案，用于存储和访问结构化键值数据，而数据网关平台为保护、配置和部署数据层提供了基础设施。

Building on these foundational abstractions, we developed the TimeSeries Abstraction — a versatile and scalable solution designed to efficiently store and query large volumes of temporal event data with low millisecond latencies, all in a cost-effective manner across various use cases.

在这些基础抽象的基础上，我们开发了TimeSeries抽象——一种多功能且可扩展的解决方案，旨在以成本效益的方式在各种用例中高效存储和查询大量的时间事件数据，并具有低毫秒级的延迟。

In this post, we will delve into the architecture, design principles, and real-world applications of the TimeSeries Abstraction, demonstrating how it enhances our platform’s ability to manage temporal data at scale.

在本文中，我们将深入探讨时间序列抽象的架构、设计原则和实际应用，展示它如何增强我们平台在大规模管理时间数据方面的能力。

Note: Contrary to what the name may suggest, this system is not built as a general-purpose time series database. We do not use it for metrics, histograms, timers, or any such near-real time analytics use case. Those use cases are well served by the Netflix Atlas telemetry system. Instead, we focus on addressing the challenge of storing and accessing extremely high-throughpu...