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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)

Paper ID
10648
Venue
VLDB
Year
2012
Pagerank
5.2576928e-05
Overall Rank
9,510 | 34.76%
DOI
10.14778/2367502.2367562

Incoming Non-self Citations Over Time

Authors

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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