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Real-Time Big Data Analytics
Sumit Gupta Shilpi
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Real-Time Big Data AnalyticsSumit Gupta Shilpi
If you are a Big Data architect, developer, or a programmer who wants to develop applications/frameworks to implement real-time analytics using open source technologies, then this book is for you.
If you are a Big Data architect, developer, or a programmer who wants to develop applications/frameworks to implement real-time analytics using open source technologies, then this book is for you.
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If you are a Big Data architect, developer, or a programmer who wants to develop applications/frameworks to implement real-time analytics using open source technologies, then this book is for you.
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出版社Packt Publishing
出版时间2016年2月
字数451,112
分类计算机-编程设计
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Real-Time Big Data Analytics
Sumit Gupta Shilpi
- 扉页
- 版权信息+书签
- Credits
- About the Authors
- About the Reviewer
- www.PacktPub.com
- Preface
- Chapter 1. Introducing the Big Data Technology Landscape and Analytics Platform
- Big Data – a phenomenon
- The Big Data dimensional paradigm
- The Big Data ecosystem
- The Big Data infrastructure
- Components of the Big Data ecosystem
- Distributed batch processing
- Distributed databases (NoSQL)
- Real-time processing
- Summary
- Chapter 2. Getting Acquainted with Storm
- An overview of Storm
- Storm architecture and its components
- How and when to use Storm
- Storm internals
- Summary
- Chapter 3. Processing Data with Storm
- Storm input sources
- Other sources for input to Storm
- Reliability of data processing
- Storm simple patterns
- Storm persistence
- Summary
- Chapter 4. Introduction to Trident and Optimizing Storm Performance
- Working with Trident
- Understanding LMAX
- Storm internode communication
- Understanding the Storm UI
- Optimizing Storm performance
- Summary
- Chapter 5. Getting Acquainted with Kinesis
- Architectural overview of Kinesis
- Creating a Kinesis streaming service
- Summary
- Chapter 6. Getting Acquainted with Spark
- An overview of Spark
- The architecture of Spark
- Resilient distributed datasets (RDD)
- Writing and executing our first Spark program
- Summary
- Chapter 7. Programming with RDDs
- Understanding Spark transformations and actions
- Programming Spark transformations and actions
- Handling persistence in Spark
- Summary
- Chapter 8. SQL Query Engine for Spark – Spark SQL
- The architecture of Spark SQL
- Coding our first Spark SQL job
- Converting RDDs to DataFrames
- Working with Parquet
- Working with Hive tables
- Performance tuning and best practices
- Summary
- Chapter 9. Analysis of Streaming Data Using Spark Streaming
- High-level architecture
- Coding our first Spark Streaming job
- Querying streaming data in real time
- Deployment and monitoring
- Summary
- Chapter 10. Introducing Lambda Architecture
- What is Lambda Architecture
- The technology matrix for Lambda Architecture
- Realization of Lambda Architecture
- Summary
- Index
Real-Time Big Data Analytics
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