| 000 | a | ||
|---|---|---|---|
| 999 |
_c33764 _d33764 |
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| 008 | 250305b xxu||||| |||| 00| 0 eng d | ||
| 020 | _a9781484219096 | ||
| 082 |
_a005.74 _bKOI |
||
| 100 | _aKoitzsch, Kerry | ||
| 245 | _aPro Hadoop data analytics : designing and building big data systems using the Hadoop ecosystem | ||
| 260 |
_bApress, _c2017 _aNew York : |
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| 300 |
_axxi, 298 p. ; _bill., (some col.), _c26 cm |
||
| 365 |
_b39.99 _c€ _d93.20 |
||
| 504 | _aIncludes bibliographical references at the end of each chapters and index. | ||
| 520 | _aLearn advanced analytical techniques and leverage existing toolkits to make your analytic applications more powerful, precise, and efficient. This book provides the right combination of architecture, design, and implementation information to create analytical systems which go beyond the basics of classification, clustering, and recommendation. In Pro Hadoop Data Analytics best practices are emphasized to ensure coherent, efficient development. A complete example system will be developed using standard third-party components which will consist of the toolkits, libraries, visualization and reporting code, as well as support glue to provide a working and extensible end-to-end system. The book emphasizes four important topics: The importance of end-to-end, flexible, configurable, high-performance data pipeline systems with analytical components as well as appropriate visualization results. Deep-dive topics will include Spark, H20, Vopal Wabbit (NLP), Stanford NLP, and other appropriate toolkits and plugins. Best practices and structured design principles. This will include strategic topics as well as the how to example portions. The importance of mix-and-match or hybrid systems, using different analytical components in one application to accomplish application goals. The hybrid approach will be prominent in the examples. Use of existing third-party libraries is key to effective development. Deep dive examples of the functionality of some of these toolkits will be showcased as you develop the example system. | ||
| 650 | _aApache Hadoop | ||
| 650 | _aCloud Computing | ||
| 650 | _aSoftware development | ||
| 650 | _aData mining | ||
| 650 | _aDatabase management | ||
| 650 | _aAnalytical engine | ||
| 650 | _aBig data analytics | ||
| 650 | _aData pipeline | ||
| 650 | _a Environment variable | ||
| 650 | _aHadoop ecosystem | ||
| 650 | _aSpring Framework | ||
| 942 |
_2ddc _cBK |
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