Hadoop and Spark Fundamentals: Unit 3

Hadoop and Spark Fundamentals: Unit 3

本课程是 Hadoop and Spark Fundamentals 专项课程的一部分

位教师：Pearson

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8 小时完成

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深入了解一个主题并学习基础知识。

中级等级

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8 小时完成

灵活的计划

自行安排学习进度

您将学到什么

Master advanced data ingestion techniques into Hadoop HDFS, including Hive, Spark, Flume, and Sqoop.
Develop and run interactive Spark applications using the Apache Zeppelin web interface.
Install, monitor, and administer Hadoop clusters with Ambari and essential command-line tools.
Utilize advanced HDFS features such as snapshots and NFS mounts for enhanced data management.

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4 项作业

授课语言：英语（English）

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本课程是 Hadoop and Spark Fundamentals 专项课程专项课程的一部分

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该课程共有1个模块

This course is for those who want to become data engineers or analysts. It covers the key skills needed to manage, process, and analyze large datasets using common industry tools. You will learn how to import data into Hadoop HDFS, Hive tables, and use Spark for direct HDFS imports. The course also covers handling streaming data with Apache Flume and connecting relational databases to Hadoop with Apache Sqoop. You will use Apache Zeppelin for developing Spark applications and learn how to install, monitor, and manage Hadoop clusters with Ambari. The course also introduces advanced HDFS features for data management. By the end, you will be able to use Hadoop and Spark in practical settings.

This module introduces essential tools and techniques for working with Hadoop and Spark. It covers data ingestion into HDFS using Hive, Spark, Flume, and Sqoop, emphasizing methods that preserve data structure. The module also explores user-friendly interfaces, such as Apache Zeppelin for interactive Spark development and Ambari for Hadoop installation and administration. Practical examples and demonstrations guide learners through importing data, managing clusters, and utilizing both web-based and command-line tools, providing a comprehensive foundation for effective Hadoop and Spark operations.