Efficient Big Data Processing in Hadoop MapReduce
Summary: Tutorial on efficient Hadoop MapReduce performance, covering optimization techniques, data layouts, and indexes to boost big-data processing. Contrasts with parallel DBMS, frames unresolved research questions, and outlines a three-part structure to bridge the performance gap to well-tuned databases. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Jens Dittrich (Saarland University)
- 2. Jorge-Arnulfo Quiané-Ruiz (Saarland University)
BibTeX Citation
@article{dittrich_vldb12,
title = {{Efficient Big Data Processing in Hadoop MapReduce}},
author = {Dittrich, Jens and Quiané-Ruiz, Jorge-Arnulfo},
journal = {PVLDB},
series = {{VLDB} '12},
doi = {10.14778/2367502.2367562},
url = {https://doi.org/10.14778/2367502.2367562},
year = {2012}
}
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,344 | Towards General and Efficient Online Tuning for Spark | 2023 | VLDB | 5.9060457e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 13 of 13 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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| 10 | 9,263 | MapReduce Algorithms for Big Data Analysis | 2012 | VLDB |