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所在平台: Udemy |
课程主页: https://www.udemy.com/course/functional-streams-for-scala-with-fs2/
课程评论：没有评论
课程名称：Scala的功能流与FS2 课程概述：许多应用程序涉及处理大量数据流，例如在ETL作业中处理文件、从数据库读取结果或获取来自HTTP调用的大响应。处理大量数据通常意味着要么牺牲可读性，要么牺牲性能。而使用流（Streams），你可以兼得这两者的优点：即使数据量非常大，数据处理也仅使用固定量的内存；而且，处理过程是声明式的，仿佛你在处理常规的列表或序列，可以使用诸如map、filter和flatMap等高级方法。此外，FS2中的流是关注效果的，能够在效果单子（如IO）的上下文中工作，使其能够执行许多有用的操作，如并行处理元素、限制速率、失败重试等。 在本课程中，我们将深入探讨流的内部机制，并学习以下内容： - 创建和组合纯流（pure streams） - 为流添加效果并学习如何组合它们 - 安全地处理错误和资源 - 应用涉及时间的模式，如重试、限制速率和防抖动 - 使用Pulls和Pipes构建自己的流转换 - 使用多种不同模式处理并发 - 使用信号（Signals）、通道（Channels）、主题（Topics）和队列（Queues）等原语在流之间进行通信 加入我，让我们一起探索这一令人惊叹的工具，为你的函数式编程工具箱增添新内容！
Many applications involve dealing with large flows of data. Examples are processing files in ETL jobs, reading results from a database or getting a big response from http calls. Handling large amounts of data often means sacrificing either readability or performance. With streams, you can get the best of both worlds:- Data is processed using a constant amount of memory, even if the total amount of data is very large- The processing is built declaratively as if you were dealing with regular Lists or Sequences, with high level methods such as map, filter and flatMapFurthermore, streams in FS2 are effect-aware. They work in the context of an effect monad like IO, which enables them to do all sorts of useful stuff such as processing elements in parallel, throttling, retrying on failure and many more.In this course we will turn streams inside out and learn things like:- Create and combine pure streams - Add effects to our streams and learn how to compose them- Handle errors & resources safely- Apply patterns involving time, such as retries, throttling and debouncing.- Build our own stream transformations with Pulls and Pipes- Handle concurrency using many different patterns- Communicate between streams using primitives such as Signals, Channels, Topics and QueuesJoin me in this journey and add yet another amazing tool to your functional programming toolkit!
