Real-Time Data Pipelines with Apache Kafka and Flink
Chapter 1: Stream Processing Architectures and Semantics
Evolution of Distributed Logs
Lambda versus Kappa Architecture
Processing Guarantees and Semantics
Event Time versus Processing Time
Hands-on Practical: Designing a Kappa Pipeline
Chapter 2: Advanced Kafka Producer and Consumer Internals
Replication Protocols and ISRs
Idempotent Producers and Transactions
Custom Partitioning Strategies
Consumer Group Rebalancing protocols
Hands-on Practical: Implementing Transactional Writes
Chapter 3: Flink State Management and Checkpointing
State Backends: HashMap versus RocksDB
Asynchronous Barrier Snapshots
Incremental Checkpointing
State Schema Evolution
Hands-on Practical: State Migration with Savepoints
Chapter 4: Advanced Windowing and Time Attributes
Watermark Generation Strategies
Handling Late Data and Side Outputs
Custom Window Triggers and Evictors
Session Windows and Gap Analysis
Hands-on Practical: Building a Custom Trigger
Chapter 5: Low-Level Operations with ProcessFunctions
The ProcessFunction Hierarchy
Timer Services and Event Scheduling
Broadcast State Pattern
Async I/O for External Lookups
Hands-on Practical: Dynamic Rule Evaluation
Chapter 6: Production Deployment and Reliability
Serialization with Avro and Protobuf
Schema Registry Integration
Kafka Connect for Sink and Source
Failure Recovery Strategies
Hands-on Practical: Schema Evolution in Flight
Chapter 7: Performance Tuning and Monitoring
Identifying Backpressure
Memory Management and Slot Allocation
Tuning RocksDB Performance
Kafka Consumer Lag Analysis
Hands-on Practical: Resolving Skewed Data
Chapter 8: Real-Time AI and Feature Engineering
Online Feature Generation
Model Serving Patterns in Streams
Request-Response over Async Streams
Feature Store Integration
Hands-on Practical: Real-Time Inference Pipeline
Idempotent Producers and Transactions
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- Apache Kafka Documentation: Producers and Transactions, The Apache Software Foundation, 2023 - Provides comprehensive details on configuring and using Kafka's idempotent producers and transactional API, including operational implications.
- KIP-98: Exactly Once Semantics for Message Production, Jason Gustafson, Flavio Paiva Junqueira, Apurva Mehta, Sriram, Guozhang Wang, 2016 Kafka Improvement Proposals (Apache Software Foundation) - The original design document for Kafka's idempotent producer, explaining the Producer ID (PID), sequence number, and broker validation logic.
- KIP-305: Transactions for Kafka, Apurva Mehta, Jason Gustafson, Sriram Sundar, Sophie Blee-Goldman, 2017 Kafka Improvement Proposals (Apache Software Foundation) - The original design document for Kafka's transactional API, explaining the Transaction Coordinator, two-phase commit, and isolation levels.
- Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems, Martin Kleppmann, 2017 (O'Reilly Media) - Offers a foundational understanding of distributed systems concepts, consistency models, and transaction processing, giving broader context for Kafka's solutions.
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