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: Optimizing File Layouts
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- Apache Parquet, Apache Software Foundation, 2023 - Official documentation for Apache Parquet, covering its columnar storage format, data types, compression, and performance benefits crucial for analytical workloads in data lakes.
- Apache Iceberg: A Table Format for Analytic Datasets, Ryan Blue, Daniel Weeks, David Rolfe, 2020 Proceedings of the VLDB Endowment, Vol. 13 (VLDB Endowment) DOI: 10.14778/3415494.3415555 - A foundational paper introducing Apache Iceberg, explaining its architecture, metadata storage, snapshot isolation, and how it addresses challenges in large-scale data lake table management.
- Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems, Martin Kleppmann, 2017 (O'Reilly Media) - This authoritative book provides deep insights into the fundamental principles of data storage, retrieval, and partitioning, which underpin the optimization strategies for data lakes discussed in the section.
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