Hadoop Application Architectures - Designing Real-World Big Data Applications由 O'Reilly 于2015年7月出版，共364页。

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目录

Chapter 1 Data Modeling in Hadoop
Chapter 2 Data Movement
Chapter 3 Processing Data in Hadoop
Chapter 4 Common Hadoop Processing Patterns
Chapter 5 Graph Processing on Hadoop
Chapter 6 Orchestration
Chapter 7 Near-Real-Time Processing with Hadoop
Chapter 8 Clickstream Analysis
Chapter 9 Fraud Detection
Chapter 10 Data Warehouse

通过本书可以学到以下知识

• Factors to consider when using Hadoop to store and model data
• Best practices for moving data in and out of the system
• Data processing frameworks, including MapReduce, Spark, and Hive
• Common Hadoop processing patterns, such as removing duplicate records and using windowing analytics
• Giraph, GraphX, and other tools for large graph processing on Hadoop
• Using workflow orchestration and scheduling tools such as Apache Oozie
• Near-real-time stream processing with Apache Storm, Apache Spark Streaming, and Apache Flume
• Architecture examples for clickstream analysis, fraud detection, and data warehousing

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