Next-Generation Big Data: A Practical Guide to Apache Kudu, Impala, and Spark
暫譯: 下一代大數據:Apache Kudu、Impala 與 Spark 實用指南

Butch Quinto

  • 出版商: Apress
  • 出版日期: 2018-06-13
  • 售價: $2,050
  • 貴賓價: 9.5$1,948
  • 語言: 英文
  • 頁數: 584
  • 裝訂: Paperback
  • ISBN: 1484231465
  • ISBN-13: 9781484231463
  • 相關分類: Spark大數據 Big-data
  • 海外代購書籍(需單獨結帳)

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商品描述

Utilize this practical and easy-to-follow guide to modernize traditional enterprise data warehouse and business intelligence environments with next-generation big data technologies.

Next-Generation Big Data takes a holistic approach, covering the most important aspects of modern enterprise big data. The book covers not only the main technology stack but also the next-generation tools and applications used for big data warehousing, data warehouse optimization, real-time and batch data ingestion and processing, real-time data visualization, big data governance, data wrangling, big data cloud deployments, and distributed in-memory big data computing. Finally, the book has an extensive and detailed coverage of big data case studies from Navistar, Cerner, British Telecom, Shopzilla, Thomson Reuters, and Mastercard.

What You’ll Learn

  • Install Apache Kudu, Impala, and Spark to modernize enterprise data warehouse and business intelligence environments, complete with real-world, easy-to-follow examples, and practical advice
  • Integrate HBase, Solr, Oracle, SQL Server, MySQL, Flume, Kafka, HDFS, and Amazon S3 with Apache Kudu, Impala, and Spark
  • Use StreamSets, Talend, Pentaho, and CDAP for real-time and batch data ingestion and processing
  • Utilize Trifacta, Alteryx, and Datameer for data wrangling and interactive data processing
  • Turbocharge Spark with Alluxio, a distributed in-memory storage platform
  • Deploy big data in the cloud using Cloudera Director
  • Perform real-time data visualization and time series analysis using Zoomdata, Apache Kudu, Impala, and Spark
  • Understand enterprise big data topics such as big data governance, metadata management, data lineage, impact analysis, and policy enforcement, and how to use Cloudera Navigator to perform common data governance tasks
  • Implement big data use cases such as big data warehousing, data warehouse optimization, Internet of Things, real-time data ingestion and analytics, complex event processing, and scalable predictive modeling
  • Study real-world big data case studies from innovative companies, including Navistar, Cerner, British Telecom, Shopzilla, Thomson Reuters, and Mastercard
Who This Book Is For

BI and big data warehouse professionals interested in gaining practical and real-world insight into next-generation big data processing and analytics using Apache Kudu, Impala, and Spark; and those who want to learn more about other advanced enterprise topics

商品描述(中文翻譯)

利用這本實用且易於遵循的指南,使用下一代大數據技術現代化傳統企業資料倉儲和商業智慧環境。

《下一代大數據》採取整體性的方法,涵蓋現代企業大數據最重要的各個方面。這本書不僅涵蓋主要的技術堆疊,還包括用於大數據倉儲、資料倉儲優化、即時和批次資料攝取與處理、即時資料視覺化、大數據治理、資料整理、大數據雲端部署以及分散式內存大數據計算的下一代工具和應用程式。最後,本書詳細介紹了來自Navistar、Cerner、British Telecom、Shopzilla、Thomson Reuters和Mastercard的大數據案例研究。

您將學到的內容:

- 安裝Apache Kudu、Impala和Spark,以現代化企業資料倉儲和商業智慧環境,並提供真實世界的易於遵循的範例和實用建議
- 將HBase、Solr、Oracle、SQL Server、MySQL、Flume、Kafka、HDFS和Amazon S3與Apache Kudu、Impala和Spark整合
- 使用StreamSets、Talend、Pentaho和CDAP進行即時和批次資料攝取與處理
- 利用Trifacta、Alteryx和Datameer進行資料整理和互動式資料處理
- 使用Alluxio這個分散式內存儲存平台來加速Spark
- 使用Cloudera Director在雲端部署大數據
- 使用Zoomdata、Apache Kudu、Impala和Spark進行即時資料視覺化和時間序列分析
- 理解企業大數據主題,如大數據治理、元資料管理、資料血緣、影響分析和政策執行,以及如何使用Cloudera Navigator執行常見的資料治理任務
- 實施大數據使用案例,如大數據倉儲、資料倉儲優化、物聯網、即時資料攝取與分析、複雜事件處理和可擴展的預測建模
- 研究來自創新公司的真實世界大數據案例研究,包括Navistar、Cerner、British Telecom、Shopzilla、Thomson Reuters和Mastercard

本書適合對象:

對於希望獲得實用且真實世界見解的BI和大數據倉儲專業人士,特別是使用Apache Kudu、Impala和Spark進行下一代大數據處理和分析的人士;以及那些想要了解更多其他進階企業主題的人士。

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