Batch Data Pipeline with Spark

From Data Lake to Lakehouse you own this product

This project is part of the liveProject series End-to-End Batch Data Pipeline with Spark
prerequisites
beginner Python • basics of Jupyter Notebook • beginner SQL • beginner Apache Spark • basic data processing in Python (with pandas or similar libraries) • basic distributed computing
skills learned
leverage Delta Lake capabilities including schema enforcement and time travel • use Delta Lake commands • interact with multiple layers of the three-layer architecture • use Apache Spark for data processing and interacting with the Lakehouse
Mahdi Karabiben
1 week · 4-6 hours per week · BEGINNER
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liveProject This project is part of the liveProject series End-to-End Batch Data Pipeline with Spark liveProjects give you the opportunity to learn new skills by completing real-world challenges in your local development environment. Solve practical problems, write working code, and analyze real data—with liveProject, you learn by doing. These self-paced projects also come with full liveBook access to select books for 90 days plus permanent access to other select Manning products. $19.99 $29.99 you save $10 (33%)
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Turn an existing data lake into a Lakehouse, using Delta Lake, an open table format (and the cornerstone of Databricks’ Lakehouse design). For data processing and interacting with the Lakehouse, you’ll use Apache Spark. As you transform the existing tables into Delta tables, you’ll explore Delta Lake’s rich features, see firsthand how it handles potential problems, and appreciate the sophistication of the Lakehouse design.

This project is designed for learning purposes and is not a complete, production-ready application or solution.

book resources

When you start your liveProject, you get full access to the following books for 90 days.

project author

Mahdi Karabiben

Mahdi is a senior data engineer at Zendesk. With four years of experience in data engineering, he has worked on multiple large-scale projects within the AdTech and financial sectors. He's a Cloudera-certified Apache Spark developer and works with Big Data technologies on a daily basis, designing and building data pipelines, data lakes, and data services that rely on petabytes of data. Thanks to his degree in software engineering (with a minor in big data), he is comfortable with a wide range of technologies and concepts. He additionally writes for major Medium publications (Towards Data Science, The Startup) and technology websites (TheNextWeb, Software Engineering Daily, freeCodeCamp).

prerequisites

The liveProject is for software engineers and data professionals interested in onboarding big data processing skills including processing large amounts of data and building cloud-based data lakes. To begin these liveProjects you'll need to be familiar with the following:


TOOLS
  • Beginner Python
  • Basics of Jupyter Notebook
  • Beginner SQL
  • Beginner Apache Spark
TECHNIQUES
  • Basic data processing in Python (with pandas or similar libraries)
  • Basic distributed computing
  • Basic SQL
  • Basic understanding of distributed data lakes

you will learn

In this liveProject, you’ll learn to transform an existing data lake into a Lakehouse, onboarding the following important concepts and tools:


  • Leverage Delta Lake capabilities including schema enforcement and time travel
  • Use Delta Lake commands
  • Interact with multiple layers of the three-layer architecture
  • Use Apache Spark for data processing and interacting with the Lakehouse

features

Self-paced
You choose the schedule and decide how much time to invest as you build your project.
Project roadmap
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book resources
Get full access to select books for 90 days. Permanent access to excerpts from Manning products are also included, as well as references to other resources.
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