| 000 | 01510nam a22002658a 4500 | ||
|---|---|---|---|
| 001 | 680045 | ||
| 005 | 20210719165124.0 | ||
| 008 | 121213s2013 ctu f 000 0 eng|d | ||
| 020 |
_a9781617290343 (pbk.) : _cNo price |
||
| 035 | _a(StDuBDS)9781617290343 | ||
| 040 |
_aStDuBDS _cStDuBDS |
||
| 072 | 7 |
_aCOM _2eflch |
|
| 082 | 0 | 4 |
_a005.7'4 _223 |
| 100 | 1 | _aMarz, Nathan. | |
| 245 | 1 | 0 |
_aBig data : _bprinciples and best practices of scalable realtime data systems / _cNathan Marz, James Warren. |
| 260 |
_aGreenwich, Conn. : _bManning ; _aLondon : _bPearson Education [distributor], _c2013. |
||
| 300 |
_a425 p. ; _c24 cm. |
||
| 520 | 8 | _aServices like social networks, web analytics, and intelligent e-commerce often need to manage data at a scale too big for a traditional database. As scale and demand increase, so does complexity. Fortunately, scalability and simplicity are not mutually exclusive-rather than using some trendy technology, a different approach is needed. Big data systems use many machines working in parallel to store and process data, which introduces fundamental challenges unfamiliar to most developers. 'Big Data' shows how to build these systems using an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data. | |
| 521 | _aSpecialized. | ||
| 650 | 0 | _aDatabase management. | |
| 650 | 0 | _aReal-time data processing. | |
| 650 | 7 |
_aComputers and IT. _2eflch |
|
| 700 | 1 | _aWarren, James. | |
| 942 | _n0 | ||
| 999 |
_c37026 _d37026 |
||