|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/learn-spark-and-hadoop-overnight-on-gcp/
课程评论：没有评论
课程名称：在 GCP 上一夜学会 Spark 和 Hadoop 课程概述：本课程是一个全面的实操课程，专注于大数据及其周边的开源解决方案。我们将使用这些工具来支持我们的电子商务项目 CORE（创建自己的推荐引擎）。这个项目旨在全方位学习技术。课程中，我们将探讨 Hadoop 这一重要的大数据解决方案，了解其背后的原因及运作方法，包括其生态系统、架构及基本运作原理，并且我们将在 Google Cloud 上用不到 2 分钟的时间启动第一个 Hadoop。 本课程将在 Project CORE 中使用，这是一个以实操技术为核心的综合项目。在这个项目中，你将学习如何构建自己的大数据系统，涉及 Spark、机器学习、SAPUI5、Angular4、D3JS 和 SAP® HANA®。通过本课程，你将对 Apache Spark™ 有一个初步了解，它是一个用于大规模数据处理的快速通用引擎。Spark 被用于 Project CORE 来管理使用 HDFS 文件系统存储的 150 万条书籍记录，并实施协同过滤算法。Spark 提供超过 80 个高级操作符，便于构建并行应用程序，并且可以通过 Scala、Python 和 R 交互使用。Spark 还支持 SQL 和 DataFrames、MLlib 机器学习库、GraphX 和 Spark Streaming 等多个库，能够在同一应用程序中无缝结合使用。Spark 可以在 Hadoop、Mesos、独立环境或云中运行。 这个课程将帮助你快速掌握相关技能，为未来的项目打下坚实的基础。
This is a comprehensive hands on course on Spark HadoopIn this course we focused on Big Data and open source solutions around that. We require these tools for our E-commerce end of Project CORE (Create your Own Recommendation Engine) is one of its kind of project to learn technology End-to-EndWe will explore Hadoop one of the prominent Big Data solutionWe will look Why part and How part of it and its ecosystem, its Architecture and basic inner working and will also spin our first Hadoop under 2 min in Google CloudThis particular course we are going to use in Project CORE which is comprehensive project on hands on technologies. In Project CORE you will learn more about Building you own system on Big Data, Spark, Machine Learning, SAPUI5, Angular4, D3JS, SAP® HANA®With this Course you will get a brief understanding on Apache Spark™, Which is a fast and general engine for large-scale data processing. Spark is used in Project CORE to manage Big data with HDFS file system, We are storing 1.5 million records of books in spark and implementing collaborative filtering algorithm. Spark offers over 80 high-level operators that make it easy to build parallel apps. And you can use it interactively from the Scala, Python and R shells. Spark powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming. You can combine these libraries seamlessly in the same application. Runs Everywhere - Spark runs on Hadoop, Mesos, standalone, or in the cloud.
