Hadoop and Spark Fundamentals: Unit 3

Hadoop and Spark Fundamentals: Unit 3

This course is part of Hadoop and Spark Fundamentals Specialization

Instructors: Pearson

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1 module

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

8 hours to complete

Flexible schedule

Learn at your own pace

1 module

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

8 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

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.

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

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Assessments

4 assignments

Taught in English

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This course is part of the Hadoop and Spark Fundamentals Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There is 1 module in this course

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.