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Event Streams in Action：Unified Log Processing with Kafta and Kinesis

Event Streams in Action：Unified Log Processing with Kafta and Kinesis

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作者: Alexander Dean , Valentin Crettaz

出版社: Manning Publications

出版时间: 2019-05

ISBN: 9781617292347

装帧: 其他

页数: 344页

分类: 外文古旧书>英文书>文学

2人买过

About the Technology
Many high-profile applications, like LinkedIn and Netflix, deliver nimble, responsive performance by reacting to user and system events as they occur. In large-scale systems, this requires efficiently monitoring, managing, and reacting to multiple event streams. Tools like Kafka, along with innovative patterns like unified log processing, help create a coherent data processing architecture for event-based applications.
About the Book
Event Streams in Action teaches you techniques for aggregating, storing, and processing event streams using the unified log processing pattern. In this hands-on guide, you'll discover important application designs like the lambda architecture, stream aggregation, and event reprocessing. You'll also explore scaling, resiliency, advanced stream patterns, and much more! By the time you're finished, you'll be designing large-scale data-driven applications that are easier to build, deploy, and maintain.
What's inside
Validating and monitoring event streams
Event analytics
Methods for event modeling
Examples using Apache Kafka and Amazon Kinesis Alexander Dean is co-founder and technical lead of Snowplow Analytics, an open source event processing and analytics platform.
Valentin Crettaz is an independent IT consultant who's been working for the past 25 years on many different challenging projects across the globe. His expertise ranges from software engineering and architecture to data science and business intelligence. His daily job boils down to leveraging the latest and most cutting-edge web, data, and streaming technologies to implement IT solutions that will help reduce the cultural gap between IT and business people. PART 1 - EVENT STREAMS AND UNIFIED LOGS
Introducing event streams
The unified log 24
Event stream processing with Apache Kafka
Event stream processing with Amazon Kinesis
Stateful stream processing
PART 2- DATA ENGINEERING WITH STREAMS
Schemas
Archiving events
Railway-oriented processing
Commands
PART 3 - EVENT ANALYTICS
Analytics-on-read
Analytics-on-write
内容简介:
About the Technology
Many high-profile applications, like LinkedIn and Netflix, deliver nimble, responsive performance by reacting to user and system events as they occur. In large-scale systems, this requires efficiently monitoring, managing, and reacting to multiple event streams. Tools like Kafka, along with innovative patterns like unified log processing, help create a coherent data processing architecture for event-based applications.
About the Book
Event Streams in Action teaches you techniques for aggregating, storing, and processing event streams using the unified log processing pattern. In this hands-on guide, you'll discover important application designs like the lambda architecture, stream aggregation, and event reprocessing. You'll also explore scaling, resiliency, advanced stream patterns, and much more! By the time you're finished, you'll be designing large-scale data-driven applications that are easier to build, deploy, and maintain.
What's inside
Validating and monitoring event streams
Event analytics
Methods for event modeling
Examples using Apache Kafka and Amazon Kinesis
作者简介:
Alexander Dean is co-founder and technical lead of Snowplow Analytics, an open source event processing and analytics platform.
Valentin Crettaz is an independent IT consultant who's been working for the past 25 years on many different challenging projects across the globe. His expertise ranges from software engineering and architecture to data science and business intelligence. His daily job boils down to leveraging the latest and most cutting-edge web, data, and streaming technologies to implement IT solutions that will help reduce the cultural gap between IT and business people.
目录:
PART 1 - EVENT STREAMS AND UNIFIED LOGS
Introducing event streams
The unified log 24
Event stream processing with Apache Kafka
Event stream processing with Amazon Kinesis
Stateful stream processing
PART 2- DATA ENGINEERING WITH STREAMS
Schemas
Archiving events
Railway-oriented processing
Commands
PART 3 - EVENT ANALYTICS
Analytics-on-read
Analytics-on-write

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