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所在平台: Udemy |
课程主页: https://www.udemy.com/course/data-stream-development-via-spark-kafka-and-spring-boot/
课程评论：没有评论
课程名称: 数据流开发：使用Spark、Kafka和Spring Boot 课程概述: 在当今社会，组织在处理大规模数据集时面临着困难。为了获得洞察，数据处理和分析需要实时进行。这就是数据流的作用。随着大数据不再是小众话题，开发人员必须具备架构和开发稳健数据流管道的技能。此外，他们还需要考虑整个管道，包括每个层级的权衡。本课程首先解释了开发完全功能的数据流管道的蓝图架构以及所使用技术的安装。通过现场编码环节，您将亲手构建管道的每个层级，并处理处理流数据时遇到的具体问题。您将输入一个Meetup RSVP的实时数据流，并通过Google Maps进行分析和展示。到课程结束时，您将构建一个高效的数据流管道，并能够分析其各个层级，确保数据的持续流动。 关于讲师: Anghel Leonard现为Java首席架构师，拥有20年以上的经验，曾担任Java EE Guardians的成员。他的职业生涯主要集中在架构分布式系统上，同时也是多本书籍的作者、演讲者，并热衷于处理数据。
Today, organizations have a difficult time working with huge numbers of datasets. In addition, data processing and analyzing need to be done in real time to gain insights. This is where data streaming comes in. As big data is no longer a niche topic, having the skillset to architect and develop robust data streaming pipelines is a must for all developers. In addition, they also need to think of the entire pipeline, including the trade-offs for every tier.This course starts by explaining the blueprint architecture for developing a completely functional data streaming pipeline and installing the technologies used. With the help of live coding sessions, you will get hands-on with architecting every tier of the pipeline. You will also handle specific issues encountered working with streaming data. You will input a live data stream of Meetup RSVPs that will be analyzed and displayed via Google Maps.By the end of the course, you will have built an efficient data streaming pipeline and will be able to analyze its various tiers, ensuring a continuous flow of data.About the AuthorAnghel Leonard is currently a Java chief architect. He is a member of the Java EE Guardians with 20+ years' experience. He has spent most of his career architecting distributed systems. He is also the author of several books, a speaker, and a big fan of working with data.
