Big Data Processing & Lakehouse Engineering Roadmap — Step-by-step Le…
Processing massive datasets with distributed systems: Spark, lakehouse table formats, and performance at petabyte scale
The Big Data Processing & Lakehouse Engineering roadmap
- Big Data and Distributed Processing Fundamentals — beginner
- Distributed Storage Fundamentals — beginner
- Distributed File Systems Fundamentals — beginner
- Cloud Object Storage for Big Data (S3, GCS, ADLS) — beginner
- Data Locality and Its Modern Relevance — beginner
- File Organization for Distributed Processing — beginner
- Storage Formats for Big Data (Parquet, ORC) — beginner
- Spark Core Concepts — beginner
- RDDs: Spark's Original Abstraction — beginner
- Transformations vs Actions — beginner
- The Spark Execution Model — beginner
- Spark's Cluster Manager Options — beginner
- Writing Your First Spark Job — beginner
- Spark SQL and DataFrames — beginner
- DataFrames and the Catalyst Optimizer — beginner
- Spark SQL Fundamentals — beginner
- User-Defined Functions (UDFs) in Spark — beginner
- Reading the Physical Query Plan — beginner
- Spark DataFrame vs Pandas: Key Differences — beginner
- Spark Architecture and Execution — beginner
- Driver, Executors and Cluster Architecture — beginner
- The Spark UI and Job Monitoring — beginner
- Stages, Tasks and Parallelism — beginner
- Wide vs Narrow Transformations — beginner
- Fault Tolerance in Spark — beginner
- Debugging a Slow Spark Job — beginner
- Partitioning and Data Layout — beginner
- Partitioning Fundamentals in Spark — beginner
- Choosing the Right Number of Partitions — beginner
- Partition Pruning — beginner
- Data Skew and Its Impact on Performance — beginner
- Repartitioning and Coalescing — beginner
- Joins and Shuffle Optimization — beginner
- Join Strategies in Spark — beginner
- Broadcast Joins — beginner
- Understanding Shuffle Operations — beginner
- Optimizing Joins on Skewed Data — beginner
- Join Order and Query Planning — beginner
- Caching and Memory Management — beginner
- Caching and Persistence in Spark — beginner
- Storage Levels Explained — beginner
- When Caching Hurts Performance — beginner
- Broadcast Variables and Accumulators — beginner
- Memory Management Internals — beginner
- Spark Performance Tuning — beginner
- A Systematic Approach to Spark Performance Tuning — beginner
- Tuning Spark Configuration Parameters — beginner
- Adaptive Query Execution — beginner
- File Size and Small File Problems — beginner
- Benchmarking Spark Jobs — beginner
- Case Study: Optimizing a Slow Production Spark Job — beginner
- Open Table Formats — beginner
- Why Open Table Formats Exist — beginner
- Delta Lake Fundamentals — beginner
- Apache Iceberg Fundamentals — beginner
- Apache Hudi Fundamentals — beginner
- Choosing Between Table Formats — beginner
- Lakehouse Architecture Patterns — beginner
- Lakehouse Architecture Fundamentals — beginner
- Medallion Architecture in a Lakehouse — beginner
- ACID Transactions on a Data Lake — beginner
- Time Travel and Data Versioning — beginner
- Lakehouse vs Traditional Warehouse — beginner
- Data Lake Management — beginner
- Data Lake Organization and Zoning — beginner
- Metadata Management for Data Lakes — beginner
- Compaction and File Maintenance — beginner
- Access Control for Data Lakes — beginner
- Data Lake Cost Management — beginner
- Structured Streaming with Spark — beginner
- Structured Streaming Fundamentals — beginner
- Micro-Batch vs Continuous Processing — beginner
- Windowing and Watermarks in Streaming — beginner
- Stateful Stream Processing — beginner
- Exactly-Once Semantics in Structured Streaming — beginner
- Combining Batch and Streaming (Lambda/Kappa Architecture) — beginner
- Cluster Management and Resource Allocation — beginner
- Cluster Sizing Fundamentals — beginner
- Autoscaling Spark Clusters — beginner
- Resource Allocation and Scheduling — beginner
- Multi-Tenant Cluster Management — beginner
- Cluster Monitoring and Health Checks — beginner
- Databricks and Managed Spark Platforms — beginner
- Databricks Platform Overview — beginner
- Databricks Notebooks and Workflows — beginner
- Unity Catalog and Governance on Databricks — beginner
- Databricks SQL and the Lakehouse for Analytics — beginner
- Comparing Managed Spark Platforms — beginner
- Cost Optimization for Big Data Workloads — beginner
- Understanding Big Data Workload Costs — beginner
- Right-Sizing Clusters for Cost — beginner
- Spot Instances for Big Data Workloads — beginner
- Storage Tiering and Lifecycle Policies — beginner
- Cost Monitoring and Chargeback — beginner
- Career and Capstone — advanced