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◾ Streaming Algorithms for Big Data Processing on Multicore Architecture
| Content Provider | Scilit |
|---|---|
| Author | Li, Kuan-Ching Jiang, Hai Yang, Laurence T. Cuzzocrea, Alfredo |
| Copyright Year | 2015 |
| Description | Is chapter brings together three topics: hash functions, Bloom lters, and the recently emerged streaming algorithms. Hashing is the oldest of the three and is backed by much literature. Bloom lters are based on hash functions and benet from hashing eciency directly. Streaming algorithms use both Bloom lters and hashing in various ways but impose strict requirements on performance. is chapter views the three topics from the viewpoint of eciency and speed. e two main performance metrics are per-unit processing time and the size of the memory footprint. All algorithms are presented as C/C++ pseudocode. Specic attention is paid to the feasibility of hardware implementation. Book Name: Big Data |
| Related Links | https://content.taylorfrancis.com/books/download?dac=C2013-0-27341-6&isbn=9780429174018&doi=10.1201/b18050-17&format=pdf |
| Ending Page | 277 |
| Page Count | 26 |
| Starting Page | 252 |
| DOI | 10.1201/b18050-17 |
| Language | English |
| Publisher | Informa UK Limited |
| Publisher Date | 2015-02-23 |
| Access Restriction | Open |
| Subject Keyword | Book Name: Big Data Computation Theory and Mathematics Hashing Hash Functions Streaming Algorithms Brings Strict Viewpoint Memory |
| Content Type | Text |
| Resource Type | Chapter |
