知鸦日报2022-07-08

IBM just released an open-source office suite called IBM Lotus Symphony. Sounds like Yet Another StarOffice distribution. But I suspect they’re probably trying to wipe out the memory of the original Lotus Symphony, which had been hyped as the Second Coming and which fell totally flat. It was the software equivalent of Gigli.

When I was in college I took two intro economics courses: macroeconomics and microeconomics. Macro was full of theories like “low unemployment causes inflation” that never quite stood up to reality. But the micro stuff was both cool and useful. It was full of interesting concepts about the relationships between supply and demand that really did work. For example, if you have a competitor who lowers their prices, the demand for your product will go down unless you match them.

Version 5.0 of Microsoft’s flagship spreadsheet program Excel came out in 1993. It was positively huge: it required a whole 15 megabytes of hard drive space. In those days we could still remember our first 20MB PC hard drives (around 1985) and so 15MB sure seemed like a lot.

By the time Excel 2000 came out, it required a whopping 146MB … almost a tenfold increase! Dang those sloppy Microsoft programmers, right?

When you’re trying to get people to switch from a competitor to your product, you need to understand barriers to entry, and you need to understand them a lot better than you think, or people won’t switch and you’ll be waiting tables.

The idea of advertising is to lie without getting caught. Most companies, when they run an advertising campaign, simply take the most unfortunate truth about their company, turn it upside down (“lie”), and drill that lie home. Let’s call it “proof by repeated assertion.” For example, plane travel is cramped and uncomfortable and airline employees are rude and unpleasant, indeed the whole commercial air system is designed as a means of torture. So almost all airline ads are going to be about how comfortable and pleasant it is to fly and how pampered you will be every step of the way. When British airways showed an ad with a businessman in a plane seat dreaming that he was a baby in a basket, all sense of reasonableness was gone for good.

Building a company? You’ve got one very important decision to make, because it affects everything else you do. No matter what else you do, you absolutely must figure out which camp you’re in, and gear everything you do accordingly, or you’re going to have a disaster on your hands.

纵观全网Figma基本都是To B 、To C类的产品应用，很少人会往这个游戏这个方向研究了，因此我开启了一段Figma针对扁平类游戏UI设计的探索之旅，结合Figma Config 2022姗姗来迟的AutoLayout 4.0的使用，以英雄联盟鲜明的海克斯科技风格代表性更高。

一个好的专利不仅是获得授权，真正发挥到业务中才能体现最大价值。

除了每天上班画图，设计师如何赋能业务，持续地发现创新？作为一名设计师，个人通过集团申请已有60+项，今天给大家分享我在专利申请及设计创新中的一点思考。

Uber is a data-driven company that heavily relies on offline and online analytics for decision-making. As Uber’s data grows exponentially every year, it’s crucial to process this data very efficiently and with minimum cost. Over the years, Apache Spark™ has become the primary compute engine at Uber to satisfy such data needs. Spark empowers many business-critical use cases at Uber with its unique features, including Uber rides, Uber Eats, autonomous vehicles, ETAs, Maps, and many more. Spark is the primary engine for data warehousing, data science, and AI/ML. In the last few years, Uber’s Spark usage has grown exponentially year over year, running on more than 10,000 nodes in production. Spark jobs now account for more than 95% of analytics cluster compute resources which process hundreds of petabytes of data every day.

本文旨在探索与介绍如何通过“流量录制”、“流量回放”代码套件降低白盒测试成本，持续提升移动端代码可测性。

Create a rating component with svg stars that support fractional values.

企业微信在飞速发展，越来越多的企业在企微协同、连接。据 2022 年企微发布会公布，企微内有 1000 万真实企业/组织，服务 5 亿微信活跃用户，活跃用户数达到 1.8 亿。

消息是企微最核心的基础功能，过去几年消息量增长了很多倍。为了保证消息存储系统的高可用和高可靠，我们进行了多次重要升级改造。

有赞作为一家商家服务公司，OLAP对有赞非常重要，最近有赞门罗发布会上的有赞贾维斯、MA，都离不开OLAP，本文主要介绍Apache Doris在有赞OLAP的初步尝试。

通过观察者机制，可以实现目标类和观察者类的解耦，即目标对象无需知道需要通知哪些观察者，方便后续的扩展与维护。

关于C++异步，你需要了解哪些？

Masonry layout can be made with the CSS columns property, and with Tailwind, that's just a couple CSS classes. CSS Columns is about as old as flexbox, but it never seemed to be as popular.

• 随着携程酒店数据的膨胀以及个性化需求的增多，每个数据接口个性化的排期开发，因为没有标准化，从需求讨论，数据准备、接口封装、上线调试到接口api说明，期间需要花费大量的时间。一个接口的实现到生产上线至少需要2天甚至更多时间，这个时间成本不得不依赖排期开发；
• 随着历史接口的迭代，已对外提供的700多数据接口中，其中500多个还在使用，并且每年的增量在100多，开发和维护成本高，特别是在追溯上游离线数据逻辑的时候，过于依赖研发资源；
• 不同研发团队技术栈不一样，算法相关的研发更多偏向于python开发，对外输出的接口也是由python实现，但公司框架对java接口有更友好的支持，不同技术栈对外输出接口的稳定性存疑，特别是人员流动，团队职责变化后，同时也影响维护成本；
• 随着业务的发展，各个业务系统的数据需求越来越多，需求响应要求也越来越高；
• 通过历史接口的分析归类，80%以上的数据接口其实是针对离线数据或者实时数据加上需求方的检索条件返回数据，没有过多的加工逻辑或者过于复杂的业务逻辑在接口中实现；

为了能更快速支持业务个性化需求和降低研发成本，起到降本增效的效果，同时避免烟囱式数据接口开发，提高数据复用率，避免同样数据出现同样的多个接口，也避免不同的研发团队拿到同一份数据都在做自己场景的数据接口，减少数据孤岛情况。为此，我们设计了一套符合需求的数据服务平台。

携程酒店业务使用Flutter技术开发的时间快接近两年，这期间有列表页、详情页、相册页等页面使用了Flutter技术栈进行了跨平台整合，大大提高了研发效率。在开发过程中，也遇到了一些性能相关问题和用户反馈，比如长列表滚动卡顿、页面打开时间较长、页面打开后部分数据加载时间较长等问题。为解决这些问题，我们选用了多个性能指标监控业务运行状态，借助性能检测工具定位问题，并查阅源码、文档等资源解决问题，形成了这篇文章。

同时在不断的需求迭代和代码更新过程中，APP的性能稳定性持续受到挑战，为此我们建立了线上性能监控系统，通过量化，治理，监控三方面手段，持续改善APP性能和用户体验。目前页面的各种性能指标诸如FPS、TTI、内存等都达到了不错的效果，本文将介绍我们在优化过程中所遇到的问题和采取的主要优化方案。

In a thriving community, people are connected to their friends and local businesses. Nextdoor is the hyperlocal platform that mirrors these offline relationships. Every day, through active discussions on the platform, new relationships are formed and existing ones strengthened.

For example, a Nextdoor user can create a post like “I really like @XYZ cafe. @John is a hard working business owner and we should all support him by buying a cup of delicious latte!” Here, the post is created by at-mentioning (via the @ symbol) nearby businesses and users. From this post, users in the neighborhood can contribute by at-mentioning others to be part of the comment threads. As a result, John’s cafe thrives and acts as a neighborhood hub where new friends are made.

Every month, millions of these mentions are created in various discussions (including lost dogs!). In addition to posts and comments, a user can type into the search box and see, among other things, nearby users and businesses. All these features are powered by the same autocomplete service — a set of APIs to ingest data and handle typeahead search of different entity types (businesses, users, keywords etc) on Nextdoor.

This post focuses on how we built a proximity-based typeahead service to power typeahead use cases at Nextdoor.

练好基本功，能解决99%的事情。

对于很多中小型企业而言，人才走一个都算可惜。因为对于一个组织而言，人的高度决定了组织的高度。在不确定时代，更需要留住人才、激发他们的积极性。而作为一个HR，要如何去判断组织的关键人才是谁呢？关键人才的薪酬制度又该怎样制定呢？