市面上已有lottie，svga，pag等优秀的矢量动画库，但是在B站业务场景下，并不能完美的解决自身业务痛点。B站拥有着一套自研的渲染引擎 Chronos，目前已支撑了移动端视频播放界面弹幕等视频特效业务，部分视频中的弹幕特效，以及大部分视频中的三连组件。Chronos 拥有对GPU接口的抽象和渲染管线，我们可以在Chronos基础上，完成一个矢量动画绘制模块，解决B站部分场景下特效动画的痛点。

217 Technology lddgo Shared on 2022-09-14

Web 水印技术在信息安全和版权保护等领域有着广泛的应用，对防止信息泄露或知识产品被侵犯有重要意义。水印根据可见性可分为可见水印和不可见水印（盲水印），本文将分别予以介绍，带你探秘 web 水印技术。

152 Technology lddgo Shared on 2022-09-14

对互联网公司来说，数据安全一直是极为重视和敏感的话题。涉及客户安全数据或者一些商业性敏感数据，如身份证号、手机号、卡号、客户号等个人信息如果被泄露出去，就会引发严重的数据安全风险。 在真实业务场景中，相关业务开发团队往往需要针对公司安全部门需求，自行实行并维护一套加解密系统，自行维护的加解密系统往往又面临着重构或修改风险。因此希望实现一个通用的敏感数据处理框架，如何在不修改业务逻辑、业务SQL的情况下，透明化、安全低风险地实现无缝进行数据加解密改造。

163 Technology lddgo Shared on 2022-09-14

本文将介绍脚手架需要的一些工具 commander、chalk、inquirer、ora等，以及package.json中的一些重要字段，最后通过实例demo来展示如何开发脚手架，希望可以为大家带来帮助！

130 Technology lddgo Shared on 2022-09-14

安全是产品的底座，是体验的基础，也是企业的一项核心竞争力。安全生产是一项系统性的工作，同时也是一件比较琐碎的事，需要做方方面面的考虑尽一切可能保障系统安全稳定运行。个人之前一直负责商品的稳定性工作，在这方面有比较多的经历和实践。

268 Design lddgo Shared on 2022-09-14

Part one of this tutorial will teach you how to build and run a custom source connector to be used with Table API and SQL, two high-level abstractions in Flink. The tutorial comes with a bundled docker-compose setup that lets you easily run the connector. You can then try it out with Flink’s SQL client.

93 Technology lddgo Shared on 2022-09-13

In part two of this blog post, we will give you insight into some core design considerations and implementation details of the sort-based blocking shuffle in Flink and list several ideas for future improvement.

230 Technology lddgo Shared on 2022-09-13

Part one of this blog post will explain the motivation behind introducing sort-based blocking shuffle, present benchmark results, and provide guidelines on how to use this new feature.

87 Technology lddgo Shared on 2022-09-13

Part one of this blog post briefly introduced the optimizations we’ve made to improve the performance of the scheduler; compared to Flink 1.12, the time cost and memory usage of scheduling large-scale jobs in Flink 1.14 is significantly reduced. In part two, we will elaborate on the details of these optimizations.

175 Technology lddgo Shared on 2022-09-13

When scheduling large-scale jobs in Flink 1.12, a lot of time is required to initialize jobs and deploy tasks. The scheduler also requires a large amount of heap memory in order to store the execution topology and host temporary deployment descriptors. For example, for a job with a topology that contains two vertices connected with an all-to-all edge and a parallelism of 10k (which means there are 10k source tasks and 10k sink tasks and every source task is connected to all sink tasks)

148 Technology lddgo Shared on 2022-09-13