Apache Spark Developer

DATB-ASP : Apache Spark Programming with Databricks

Course Duration

2 Days

Delivery

ILT/VILT

Overview

Overview Course Curriculum Training Schedule Exam & Certification FAQs

This course serves as an appropriate entry point to learn Apache Spark Programming with Databricks.

Below, we describe each of the four, four-hour modules included in this course.

Introduction to Apache Spark

This course offers essential knowledge of Apache Spark, with a focus on its distributed architecture and practical applications for large-scale data processing. Participants will explore programming frameworks, learn the Spark DataFrame API, and develop skills for reading, writing, and transforming data using Python-based Spark workflows.

Developing Applications with Apache Spark

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.

Stream Processing and Analysis with Apache Spark

Learn the essentials of stream processing and analysis with Apache Spark in this course. Gain a solid understanding of stream processing fundamentals and develop applications using the Spark Structured Streaming API. Explore advanced techniques such as stream aggregation and window analysis to process real-time data efficiently. This course equips you with the skills to create scalable and fault-tolerant streaming applications for dynamic data environments.

Monitoring and Optimizing Apache Spark Workloads on Databricks

This course explores the Lakehouse architecture and Medallion design for scalable data workflows, focusing on Unity Catalog for secure data governance, access control, and lineage tracking. The curriculum includes building reliable, ACID-compliant pipelines with Delta Lake. You'll examine Spark optimization techniques, such as partitioning, caching, and query tuning, and learn performance monitoring, troubleshooting, and best practices for efficient data engineering and analytics to address real-world challenges.

What You'll Learn

Introduction to Apache Spark
Developing Applications with Apache Spark
Stream Processing and Analysis with Apache Spark
Monitoring and Optimizing Apache Spark Workloads on Databricks

Who Should Attend

Prerequisites

Basic programming knowledge
Familiarity with Python
Basic understanding of SQL queries (SELECT, JOIN, GROUP BY)
Familiarity with data processing concepts
No prior Spark or Databricks experience required

Learning Journey

Coming Soon...

Introduction to Apache Spark

Spark Runtime Architecture

Exploring Apache Spark Architecture in Databbricks

Introduction to Spark DataFrames and SQL

Reading and Writing Data with DataFrames

Distributed System Programming Fundamentals

Basic ETL with the DataFrame API

Flight Data ETL with the DataFrame API

Analyzing Transaction Data with DataFrames

Developing Applications with Apache 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

Stream Processing and Analysis with Apache Spark

Introduction to Stream Processing

Spark Structured Streaming

Demo: Introduction to Spark Structured Streaming

Lab: Introduction to Spark Structured Streaming

Advanced Stream Processing and Analysis

Demo: Window Aggregation in Spark Structured Streaming

Lab: Window Aggregation in Spark Structured Streaming

Monitoring and Optimizing Apache Spark Workloads on Databricks

Apache Spark and Databricks

Using Apache Spark with Delta Lake

Demo: Introduction to Delta Lake

Lab: Introduction to Delta Lake

Optimizing Apache Spark

Demo: Optimizing Apache Spark

Lab: Optimizing Apache Spark

Frequently Asked Questions (FAQs)

None

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Course Curriculum

Training Schedule

Exam & Certification

FAQs

Frequently Asked Questions

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