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Master scalable data processing with Apache Spark in this hands-on course. Learn to build efficient ETL pipelines, perform advanced analytics, and optimize distributed data transformations using Spark’s DataFrame API. Explore grouping, aggregation, joins, set operations, and window functions. Work with complex data types like arrays, maps, and structs while applying best practices for performance optimization.

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What You'll Learn

  • Developing Applications with Spark

Who Should Attend

  • N/A
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Prerequisites

  • Basic programming knowledge
  • Familiarity with Python
  • Basic understanding of SQL queries (SELECT, JOIN, GROUP BY)
  • Familiarity with data processing concepts
  • "Introduction to Apache Spark Course" or Previous Databricks experience required

Learning Journey

Coming Soon...

Developing Applications with Spark

  • DataFrame API Basics
  • Demo: (Optional) Basic ETL with the DataFrame API
  • Grouping and Aggregating Data
  • Demo: Grouping and Aggregating Data
  • Lab: Grouping and Aggregating E-Commerce Data
  • Relational Operations
  • Demo: Data Relational Operations in Apache Spark
  • Working with Complex Data
  • Demo: Working with Complex Data Types in Apache Spark
  • Lab: Working with Complex Data Types in E-Commerce Data

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Frequently Asked Questions (FAQs)

None

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Course Curriculum

Course Curriculum

Training Schedule

Training Schedule

Exam & Certification

Exam & Certification

FAQs

Frequently Asked Questions

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