Grokking streaming systems real-time event processing
Grokking Streaming Systems introduces real-time event streaming applications in clear, reader-friendly language. This engaging book illuminates core concepts like data parallelization, event windows, and backpressure without getting bogged down in framework-specific details. As you go, you'll b...
| Main Authors: | , |
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| Format: | eBook |
| Language: | English |
| Published: |
Shelter Island
Manning Publications
2022
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| Subjects: | |
| Online Access: | |
| Collection: | O'Reilly - Collection details see MPG.ReNa |
Table of Contents:
- Comparing grouping behaviors
- Summary
- Exercises
- 4 Stream graph
- A credit card fraud detection system
- More about the credit card fraud detection system
- The fraud detection business
- Streaming isn't always a straight line
- Zoom into the system
- The fraud detection job in detail
- New concepts
- Upstream and downstream components
- Stream fan-out and fan-in
- Graph, directed graph, and DAG
- DAG in stream processing systems
- All new concepts in one page
- Stream fan-out to the analyzers
- Look inside the engine
- There is a problem: Efficiency
- The Streamwork framework overview
- Zooming in on the Streamwork engine
- Core streaming concepts
- More details of the concepts
- The streaming job execution flow
- Your first streaming job
- Executing the job
- Inspecting the job execution
- Look inside the engine
- Keep events moving
- The life of a data element
- Reviewing streaming concepts
- Summary
- Exercises
- 3 Parallelization and data grouping
- The sensor is emitting more events
- Even in streaming, real time is hard
- New concepts: Parallelism is important
- New concepts: Data parallelism
- The advantages of multi-stage architecture
- The multi-stage architecture in batch and stream processing systems
- Compare the systems
- A model stream processing system
- Summary
- Exercise
- 2 Hello, streaming systems!
- The chief needs a fancy tollbooth
- It started as HTTP requests, and it failed
- AJ and Miranda take time to reflect
- AJ ponders about streaming systems
- Comparing backend service and streaming
- How a streaming system could fit
- Queues: A foundational concept
- Data transfer via queues
- Our streaming framework (the start of it)
- New concepts: Data execution independence
- New concepts: Task parallelism
- Data parallelism vs. task parallelism
- Parallelism and concurrency
- Parallelizing the job
- Parallelizing components
- Parallelizing sources
- Viewing job output
- Parallelizing operators
- Viewing job output
- Events and instances
- Event ordering
- Event grouping
- Shuffle grouping
- Shuffle grouping: Under the hood
- Fields grouping
- Fields grouping: Under the hood
- Event grouping execution
- Look inside the engine: Event dispatcher
- Applying fields grouping in your job
- Event ordering
- Intro
- inside front cover
- Grokking Streaming Systems
- Copyright
- brief contents
- contents
- front matter
- preface
- acknowledgments
- about this book
- about the authors
- Part 1. Getting started with streaming
- 1 Welcome to Grokking Streaming Systems
- What is stream processing?
- Streaming system examples
- Streaming systems and real time
- How a streaming system works
- Applications
- Backend services
- Inside a backend service
- Batch processing systems
- Inside a batch processing system
- Stream processing systems
- Inside a stream processing system