Hadoop and Spark Fundamentals: Unit 2
About this course
This course introduces the fundamentals of modern data processing for data engineers, analysts, and IT professionals. You will learn the basics of Hadoop MapReduce, including how it works, how to compile and run Java MapReduce programs, and how to debug and extend them using other languages. The course includes practical exercises such as word counts across multiple files, log file analysis, and large-scale text processing with datasets like Wikipedia. You will also cover advanced MapReduce features and use tools like Yarn and the Job Browser. The course then covers higher-level tools such as Apache Pig and Hive QL for managing data workflows and running SQL-like queries. Finally, you will work with Apache Spark and PySpark to gain experience with modern data analytics platforms. By the end of the course, you will have practical skills to work with big data in various environments.
Price shown by Coursera — confirm on their site.
Enroll on CourseraYou'll be redirected to Coursera to complete enrollment.
- Listed & compared by CourseAsk
- English · All Levels
More courses like this
Databricks Certified Data Analyst Associate - Guía Completa
Udemy · MOOC / Non-credit
Coursera
Enterprise Data Integration, Governance and Architecture
Coursera · MOOC / Non-credit
Coursera
How to Use Data
University of Pennsylvania · MOOC / Non-credit
Certified Fraud Examiner (CFE) Essentials || Masterclass ||
Udemy · Certificate
More courses from Coursera
Coursera
TCP/IP and Internet
Birla Institute of Technology & Science, Pilani · MOOC / Non-credit
Coursera
Agile Project Management
University of Colorado Boulder · Master's Degree
Coursera
Conservation and Sustainable Development
University of Michigan · MOOC / Non-credit
Coursera
Extra-Galactic Astronomy
University of Cambridge · MOOC / Non-credit