如何以及为什么Netflix构建了一个实时分布式图：第一部分 — 在互联网规模下摄取和处理数据流

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This is the first entry of a multi-part blog series describing how we built a Real-Time Distributed Graph (RDG). In Part 1, we will discuss the motivation for creating the RDG and the architecture of the data processing pipeline that populates it.

这是描述我们如何构建实时分布式 图 (RDG) 的多部分博客系列的第一篇文章。在第一部分中，我们将讨论创建 RDG 的动机以及填充它的数据处理管道的架构。

Introduction

介绍

The Netflix product experience historically consisted of a single core offering: streaming video on demand. Our members logged into the app, browsed, and watched titles such as Stranger Things, Squid Game, and Bridgerton. Although this is still the core of our product, our business has changed significantly over the last few years. For example, we introduced ad-supported plans, live programming events (e.g., Jake Paul vs. Mike Tyson and NFL Christmas Day Games), and mobile games as part of a Netflix subscription. This evolution of our business has created a new class of problems where we have to analyze member interactions with the app across different business verticals. Let’s walk through a simple example scenario:

Netflix 产品体验历史上由单一核心产品组成：按需流媒体视频。我们的会员登录应用程序，浏览并观看《怪奇物语》、《鱿鱼游戏》和《布里杰顿》等标题。尽管这仍然是我们产品的核心，但我们的业务在过去几年中发生了显著变化。例如，我们推出了支持广告的计划、直播节目事件（例如，杰克·保罗 vs. 迈克·泰森和 NFL 圣诞节比赛），以及作为 Netflix 订阅一部分的移动游戏。我们业务的这种演变创造了一类新问题，我们必须分析会员在不同业务垂直领域与应用程序的互动。让我们通过一个简单的示例场景来了解：

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Imagine a Netflix member logging into the app on their smartphone and beginning to watch an episode of Stranger Things.
想象一下，一个 Netflix 会员在智能手机上登录应用程序并开始观看《怪奇物语》的一个剧集。
Eventually, they decide to watch on a bigger screen, so they log into the app on a smart TV in their home and continue watching the same episode.
最终，他们决定在更大的屏幕上观看，因此他们在家中的智能电视上登录应用程序并继续观看同一集。
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