Building Scalable Data Warehouses
Chapter 1: MPP Architecture and Storage Internals
Massively Parallel Processing Fundamentals
Decoupling Compute and Storage
Columnar Storage Formats and Compression
Micro-partitioning and Metadata Management
Hands-on practice: Inspecting Storage Profiles
Chapter 2: Advanced Data Modeling at Scale
Dimensional Modeling Constraints in Big Data
Data Vault 2.0 Implementation Patterns
Handling Semi-Structured Data
Schema Evolution and Versioning
Hands-on practice: Designing a Data Vault
Chapter 3: High-Throughput Ingestion Pipelines
Change Data Capture Architectures
Idempotency in Data Pipelines
Micro-batch vs Streaming Ingestion
Handling Late Arriving Data
Hands-on practice: Building a CDC Pipeline
Chapter 4: Query Optimization and Performance Tuning
Analyzing Query Execution Plans
Partition Pruning and Clustering Keys
Join Strategies: Broadcast vs Shuffle
Materialized Views and Caching Layers
Hands-on practice: Tuning High-Latency Queries
Chapter 5: Governance, Security, and Observability
Role-Based Access Control Hierarchies
Dynamic Data Masking and Tokenization
Row-Level Security Implementation
Resource Monitoring and Cost Control
Hands-on practice: Configuring Security Policies
Join Strategies: Broadcast vs Shuffle
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- Database Management Systems, Raghu Ramakrishnan, Johannes Gehrke, 2003 (McGraw-Hill Education) - A standard textbook providing fundamental concepts of distributed databases and query processing, including join algorithms.
- Performance Tuning Guide - Join Strategy Hints, The Apache Software Foundation, 2024 (The Apache Software Foundation) - Official documentation explaining join strategies in Apache Spark SQL, including broadcast and shuffle joins, and how to influence them.
- Query Profile, Snowflake Inc., 2025 (Snowflake Inc.) - Snowflake's official documentation describing how to analyze query execution plans to understand join strategies and performance.
- Skew-Tolerant Join Methods for MapReduce, Bugra Okcan, Vadim Riabov, 2011 Proceedings of the VLDB Endowment, Vol. 4 (VLDB Endowment) DOI: 10.14778/340270.340277 - This paper discusses methods to handle data skew during distributed join operations in large-scale data processing systems.
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