MapReduce with Deltas
- The MapReduce programming model is extended slightly in order to use deltas. Because many MapReduce jobs are being re-executed over slightly changing input, processing only those changes promises significant improvements. Reduced execution time allows for more frequent execution of tasks, yielding more up-to-date results in practical applications. In the context of compound MapReduce jobs, benefits even add up over the individual jobs, as each job gains from processing less input data. The individual steps necessary in working with deltas are being analyzed and examined for efficiency. Several use cases have been implemented and tested on top of Hadoop. The correctness of the extended programming model relies on a simple correctness criterion.
| Author: | David Saile |
|---|---|
| URN: | urn:nbn:de:kola-5479 |
| Advisor: | Ralf Lämmel |
| Document Type: | Diploma Thesis |
| Language: | English |
| Date of completion: | 2011/08/10 |
| Date of publication: | 2011/08/10 |
| Publishing institution: | Universität Koblenz-Landau, Campus Koblenz, Universitätsbibliothek |
| Granting institution: | Universität Koblenz, Fachbereich 4 |
| Release Date: | 2011/08/10 |
| Tag: | Delta; Incremental Algorithms; MapReduce |
| Institutes: | Fachbereich 4 / Fachbereich 4 |
| Dewey Decimal Classification: | 0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik |
| Licence (German): |  Es gilt das deutsche Urheberrecht: § 53 UrhG |
