Introduction to Data Lake Architectures
Chapter 1: Architectural Foundations
Decoupling Compute and Storage
Object Storage Semantics
The Medallion Architecture
Lambda and Kappa Architectures
Chapter 2: File Formats and Optimization
Row-Oriented vs Columnar Storage
Apache Parquet Internals
Open Table Formats
Compression Algorithms
Partitioning Strategies
Hands-on Practical: Optimizing File Layouts
Chapter 3: Ingestion Pipelines
Batch Ingestion Workflows
Change Data Capture (CDC)
Handling Schema Evolution
The Small File Problem
Idempotency in Pipelines
Hands-on Practical: Building a CDC Pipeline
Chapter 4: Metadata and Cataloging
The Role of the Metastore
Partition Discovery
Technical Governance
Data Lineage Implementation
Hands-on Practical: Configuring a Catalog
Chapter 5: Querying and Performance
Distributed Query Engines
File Pruning and Skipping
Vectorized Query Execution
Caching Strategies
Hands-on Practical: Query Analysis
Hands-on Practical: Configuring a Catalog
Was this section helpful?
- What is AWS Glue Data Catalog?, Amazon Web Services, 2024 - Official documentation detailing the AWS Glue Data Catalog service, its features, and how to use Glue Crawlers to automatically discover and register data lake schema and partitions.
- Apache Parquet Format Documentation, Apache Software Foundation, 2025 (Apache Software Foundation) - Explains the columnar storage format, its specifications, and features like schema evolution and encoding, which are fundamental to understanding data storage in data lakes.
- Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems, Martin Kleppmann, 2017 (O'Reilly Media) - A comprehensive guide to the principles of data systems, covering topics such as data models, storage formats, schema evolution, and distributed systems, offering a strong theoretical foundation for data lake architectures.
© 2025 ApX Machine LearningEngineered with