| 000 -LEADER |
|---|
| fixed length control field |
a |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
250305b xxu||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9781484219096 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
005.74 |
| Item number |
KOI |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Koitzsch, Kerry |
| 245 ## - TITLE STATEMENT |
|---|
| Title |
Pro Hadoop data analytics : designing and building big data systems using the Hadoop ecosystem |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
|---|
| Name of publisher, distributor, etc |
Apress, |
| Date of publication, distribution, etc |
2017 |
| Place of publication, distribution, etc |
New York : |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xxi, 298 p. ; |
| Other physical details |
ill., (some col.), |
| Dimensions |
26 cm |
| 365 ## - TRADE PRICE |
|---|
| Price amount |
39.99 |
| Price type code |
€ |
| Unit of pricing |
93.20 |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc |
Includes bibliographical references at the end of each chapters and index.
|
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc |
Learn 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 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Apache Hadoop |
|
|---|
| Topical term or geographic name as entry element |
Cloud Computing |
|
|---|
| Topical term or geographic name as entry element |
Software development |
|
|---|
| Topical term or geographic name as entry element |
Data mining |
|
|---|
| Topical term or geographic name as entry element |
Database management |
|
|---|
| Topical term or geographic name as entry element |
Analytical engine |
|
|---|
| Topical term or geographic name as entry element |
Big data analytics |
|
|---|
| Topical term or geographic name as entry element |
Data pipeline |
|
|---|
| Topical term or geographic name as entry element |
Environment variable |
|
|---|
| Topical term or geographic name as entry element |
Hadoop ecosystem |
|
|---|
| Topical term or geographic name as entry element |
Spring Framework |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
|
| Item type |
Books |