Course · Intermediate
Analyzing Large Datasets in Spark
As data grows beyond what single machines can handle, Apache Spark has become the industry standard for distributed data processing. In this course, you'll learn how to leverage Spark's in-memory computing to process massive datasets 10-100x faster than traditional tools. You'll master the three core Spark APIs - RDDs for fine-grained control, DataFrames for optimized operations, and Spark SQL for familiar query syntax - giving you the versatility to tackle any big data challenge.
- Intermediate friendly
- 3 hrs
- 4 lessons
- Premium
Course overview
Work with Apache Spark to process massive datasets using RDDs, DataFrames, and Spark SQL across distributed environments.
What's inside
4 lessons
- 01 120 minIntroduction to Spark
Learn the basics of Spark by analyzing guests on The Daily Show.
- 02 120 minWorking With RDDs in Spark
Learn how RDDs work under the hood using world population data. Explore key transformations like `map`, `filter`, and actions like `take`, `collect`, and `reduce`.
- 03 120 minSpark DataFrames
Learn the basics of Spark DataFrames by working with census data.
- 04 120 minSpark SQL
Learn Spark SQL fundamentals by querying, filtering, merging, and summarizing real-world census data across decades.
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