知鸦日报2023-06-06

作为一个平台型的业务，关系链服务对外提供一对多关系点查、全量关系列表、关系计数等基础查询，综合查询峰值QPS近百万，被动态、评论等核心业务依赖。

In November 2022, we introduced a brand new tier — Basic with ads. This tier extended existing infrastructure by adding new backend components and a new remote call to our ads partner on the playback path. As we were gearing up for launch, we wanted to ensure it would go as smoothly as possible. To do this, we devised a novel way to simulate the projected traffic weeks ahead of launch by building upon the traffic migration framework described here. We used this simulation to help us surface problems of scale and validate our Ads algorithms.

This article talks about a novel HDMI technology and how it is used within the Netflix Application to improve a user’s experience.

At Grab, data engineers work with large sets of data on a daily basis. They design and build advanced machine learning models that provide strategic insights using all of the data that flow through the Grab Platform. This enables us to provide a better experience to our users, for example by increasing the supply of drivers in areas where our predictive models indicate a surge in demand in a timely fashion.

Grab has a mature privacy programme that complies with applicable privacy laws and regulations and we use tools to help identify, assess, and appropriately manage our privacy risks. To ensure that our users’ data are well-protected and avoid any human-related errors, we always take extra measures to secure this data.

However, data engineers will still require access to actual production data in order to tune effective machine learning models and ensure the models work as intended in production.

In this article, we will describe how the Grab’s data streaming team (Coban), along with the data platform and user teams, have enforced Personally Identifiable Information (PII) masking on machine learning data streaming pipelines. This ensures that we uphold a high standard and embody a privacy by design culture, while enabling data engineers to refine their models with sanitised production data.

Grab’s real-time data platform team, Coban, has been running its stream processing framework on Kubernetes, as detailed in Plumbing at scale. We’ve also written another article (Scaling Kafka consumers) about vertical pod autoscaling (VPA) and the benefits of using it.

视频典型画面不正常主要包含画面卡顿、画面模糊、画面不显示、画面花屏这 4 类问题。本文主要介绍的是画面花屏的情况，这里的画面花屏包含了花屏、闪屏、绿屏、黑屏。视频花屏是多媒体工程师最常见的问题之一，也是最棘手的问题之一，笔者此前也数次遇到这样的问题，今天在此总结分享下经验，希望阅读到这篇文章的小伙伴们都能够有所收获。

从最初的探索，再到现在的团队成员共同完善 Flutter 单元测试，期间踩了不少坑也积累了不少经验，现将这些内容分享出来，希望能给对 Flutter 单元测试感兴趣的同学带来一些帮助。

‍本文从基础概率到引出业界通用c10k问题，然后通过代码演示从BIO,到NIO再到多路复用的演进历程。​​

想在网页中实现实时音频变声效果该如何实现呢，之前遇到这种处理音视频的需求，可能会想到需要借助C代码实现。

在本篇文章中，我们探讨了如何升级到JDK 17，并使用最新一代垃圾回收器ZGC。经过实践和测试，我们发现升级后的系统在垃圾回收方面表现出色，暂停时间被有效控制在1毫秒内。

日志领域是Elasticsearch（ES）最重要也是规模最大的应用场景之一。这得益于 ES 有高性能倒排索引、灵活的 schema、易用的分布式架构，支持高吞吐写入、高性能查询，同时有强大的数据治理生态、端到端的完整解决方案。但原生 ES 在高吞吐写入、低成本存储、高性能查询等方面还有非常大的优化空间，本文重点剖析腾讯云大数据 ES 团队在这三个方面的内核增强优化。

我们在进行软件开发时要想实现可维护、可扩展，就需要尽量复用代码，并且降低代码的耦合度。设计模式就是一种可以提高代码可复用性、可维护性、可扩展性以及可读性的解决方案。大家熟知的23种设计模式，可以分为创建型模式、结构型模式和行为型模式三大类。本专题着眼于实际开发过程中常用的几种设计模式，从理论和实战两个角度进行讨论和分享，力求逻辑清晰、表述简洁，帮助大家在项目中合理运用设计模式，保障代码的可靠性。