Netflix的分布式计数器抽象

By: Rajiv Shringi, Oleksii Tkachuk, Kartik Sathyanarayanan

作者：Rajiv Shringi，Oleksii Tkachuk，Kartik Sathyanarayanan

Introduction

介绍

In our previous blog post, we introduced Netflix’s TimeSeries Abstraction, a distributed service designed to store and query large volumes of temporal event data with low millisecond latencies. Today, we’re excited to present the Distributed Counter Abstraction. This counting service, built on top of the TimeSeries Abstraction, enables distributed counting at scale while maintaining similar low latency performance. As with all our abstractions, we use our Data Gateway Control Plane to shard, configure, and deploy this service globally.

在我们之前的博客文章中，我们介绍了Netflix的时间序列抽象，这是一种分布式服务，旨在以低毫秒延迟存储和查询大量的时间事件数据。今天，我们很高兴地介绍分布式计数器抽象。这种计数服务建立在时间序列抽象之上，能够在保持类似低延迟性能的同时实现大规模的分布式计数。与我们所有的抽象一样，我们使用我们的数据网关控制平面来分片、配置和全球部署此服务。

Distributed counting is a challenging problem in computer science. In this blog post, we’ll explore the diverse counting requirements at Netflix, the challenges of achieving accurate counts in near real-time, and the rationale behind our chosen approach, including the necessary trade-offs.

分布式计数是计算机科学中的一个挑战性问题。在这篇博客文章中，我们将探讨Netflix的各种计数需求，实现近实时准确计数的挑战，以及我们选择的方法背后的理由，包括必要的权衡。

Note: When it comes to distributed counters, terms such as ‘accurate’ or ‘precise’ should be taken with a grain of salt. In this context, they refer to a count very close to accurate, presented with minimal delays.

注意：当涉及到分布式计数器时，诸如“准确”或“精确”之类的术语应谨慎对待。在这种情况下，它们指的是非常接近准确的计数，并且呈现时延最小。

Use Cases and Requirements

用例和需求

At Netflix, our counting use cases include tracking millions of user interactions, monitoring how often specific features or experiences are shown to users, and counting multiple facets of data during A/B test experiments, among others.

在Netflix，我们的计数用例包括跟踪数百万用户互动，监控特定功能或体验向用户展示的频率，以及在A/B测试实验期间计数多方面的数据等。

At Netflix, these use cases can be classified into two broad categories:

在Netflix，这些用例可以分为两大类：

Best-Effort: For this category, the count doesn’t have to be very accurate or durable. However, this category ...