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
The Role of the Metastore
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- Hive Metastore Design, Apache Software Foundation, 2024 - Describes the architecture and components of the Apache Hive Metastore, which serves as a central metadata repository for data lakes.
- What is AWS Glue Data Catalog?, Amazon Web Services, 2024 (Amazon Web Services) - Official documentation explaining the role and functionalities of AWS Glue Data Catalog as a managed, serverless metadata repository compatible with the Hive Metastore interface.
- Data Lake Architecture: How to Build a Modern Data Platform for the AI Era, Bill Inmon, Daniel Linstedt, Ralph Hughes, 2020 (Technics Publications) - Provides a comprehensive overview of data lake concepts, including the decoupling of storage and compute, and the fundamental role of metadata management.
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