| 000 | 02363nam a2200181 4500 | ||
|---|---|---|---|
| 020 | _a978-9352605026 | ||
| 082 | _a005 ANI | ||
| 100 | _aAnil Maheswari | ||
| 245 | _aBig data | ||
| 260 |
_aNew Delhi _bMcGraw Hill _c2017 |
||
| 300 |
_axv, 236p. _b24 cm ; Pbk |
||
| 500 | _aGratis Rs.399/- | ||
| 505 | _aChapter 1. Wholeness of Big Data Chapter 2. Big Data Sources and Applications Chapter 3. Big Data Architectures Chapter 4. Distributed Computing using Hadoop Chapter 5. Parallel Processing with MapReduce Chapter 6. NoSQL Databases Chapter 7. Stream Processing with Spark Chapter 8. Ingesting Data Chapter 9. Cloud Computing Chapter 10. Web Log Analyzer Application Case Study Chapter 11. Data Mining Primer Chapter 12 Big Data Programming Primer Appendix 1 – Installing Hadoop Using Cloudera on Virtual Box Appendix 2 – Installing Hadoop on Amazon Web Services , Elastic Computing Cluster Appendix 3 – Spark Installation & Tutorial | ||
| 520 | _aThis book is written to meet the needs for an introductoryBig Data course. It is meant for students, as well as executives, who wish totake advantage of emerging opportunities in Big Data. It provides an intuitionof the wholeness of the field in a simple language, free from jargon and code.All the essential Big Data technology tools and platforms such as Hadoop,MapReduce, Spark, and NoSql are discussed. Most of the relevant programming details have been moved to Appendicesto ensure readability. The short chapters make it easy to quickly understandthe key concepts. A complete case study of developing a Big Data application isincluded. 1. Provides fun and insightful case-lets from real-world stories at the beginning of every chapter. IMB Watson Case Study, Google Flu 2. Provides a running case study across the chapters as exercises e.g. Google Query Architecture, How Google Search Works. 3. Shows clear learning objectives, review questions, and objective type questions 4. Covers end-to-end data processing chain, from generation of data to the consumption of data 5. Covers important topics like Hive, NoSQL, Data Mining Primer. 6. Dedicated Chapters on Data Mining and Big Data Programming, Appendices on Installation of Hadoop, Spark and Amazon Web Services. | ||
| 650 |
_aData mining _aBig Data |
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| 856 | _uhttp://www.mheducation.co.in/9789352605026-india-big-data | ||
| 942 | _cBK | ||
| 999 |
_c103241 _d103241 |
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