|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/working-with-hadoop-e/
课程评论:没有评论
**课程名称:** Working with Hadoop (2022年12月) **课程概述:** 本课程旨在帮助您掌握大数据处理的核心技能。Apache Hadoop是一个强大的框架,能够通过简单的编程模型,在计算机集群上实现大规模数据集的分布式处理。它具备从单台服务器扩展到数千台机器的能力,每台机器都提供本地计算和存储。Hadoop的关键优势在于,它能在应用层处理硬件故障,从而在可能发生故障的计算机集群上提供高可用服务。 **课程内容亮点:** * **Hadoop组件介绍:** 深入了解Hadoop的核心组成部分。 * **SQOOP的增量导入与导出:** 学习如何高效地使用SQOOP进行数据迁移。 * **Hive数据库操作:** 探索Hive数据库,掌握不同的数据转换技术。 * **Hive优化技术:** 学习Hive的分区、分桶和索引技术,提升查询性能。 * **Apache Pig入门:** 了解Apache Pig的特性、功能、用户自定义函数(UDF)、数据抽样和调试。 * **Oozie工作流管理:** 学习使用Oozie构建和管理工作流及子工作流,包括Shell Action、调度和监控Coordinator。 * **Flume介绍:** 了解Flume的特性及其构建模块。 * **Cloudera Manager API访问:** 学习通过API与Cloudera Manager进行交互。 * **Scala编程示例:** 通过实际例子学习Scala编程。 * **Spark生态系统:** 了解Spark生态系统及其各个组件。 * **Spark中的数据单元:** 理解Spark处理数据时的基本单元。 **谁适合学习:** 如果您希望构建并精通大数据处理技能,本课程是您的理想选择。 **立即加入,开启您的大数据之旅!**
If you are looking for building the skills and mastering in Big Data concepts, Then this is the course for you.The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than rely on hardware to deliver high-availability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly-available service on top of a cluster of computers, each of which may be prone to failures. In this course, you will learn about the Hadoop components, Incremental Import and export Using SQOOP, Explore on databases in Hive with different data transformations. Illustration of Hive partitioning, bucketing and indexing. You will get to know about Apache Pig with its features and functions, Pig UDF's, data sampling and debugging, working with Oozie workflow and sub-workflow, shell action, scheduling and monitoring coordinator, Flume with its features, building blocks of Flume, API access to Cloudera manager, Scala program with example, Spark Ecosystem and its Components, and Data units in spark.What are you waiting for?Hurry up!