文件名称:
Hadoop.Application.Architectures.1491900083
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文件大小: 18mb
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上传时间: 2015-07-07
详细说明： Get expert guidance on architecting end-to-end data management solutions with Apache Hadoop. While many sources explain how to use various components in the Hadoop ecosystem, this practical book takes you through architectural considerations necessary to tie those components together into a complete tailored application, based on your particular use case. To reinforce those lessons, the book’s second section provides detailed examples of architectures used in some of the most commonly found Hadoop applications. Whether you’re de signing a new Hadoop application, or planning to integrate Hadoop into your existing data infrastructure, Hadoop Application Architectures will skillfully guide you through the process. This book covers: 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 Table of Contents Part I. Architectural Considerations For Hadoop Applications 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 Part II. Case Studies Chapter 8. Clickstream Analysis Chapter 9. Fraud Detection Chapter 10. Data Warehouse Appendix A. Joins In Impala ...展开收缩
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