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。

114 技术 lddgo 分享于 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。

113 技术 lddgo 分享于 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！

88 技术 lddgo 分享于 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。

235 设计 lddgo 分享于 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.

63 技术 lddgo 分享于 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.

192 技术 lddgo 分享于 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.

58 技术 lddgo 分享于 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.

82 技术 lddgo 分享于 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)

50 技术 lddgo 分享于 2022-09-13

Flink has become a well established data streaming engine and a mature project requires some shifting of priorities from thinking purely about new features towards improving stability and operational simplicity. In the last couple of releases, the Flink community has tried to address some known friction points, which includes improvements to the snapshotting process. Snapshotting takes a global, consistent image of the state of a Flink job and is integral to fault-tolerance and exacty-once proce

71 技术 lddgo 分享于 2022-09-13