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Redoop Infrastructure for Recurring Big Data Queries

Summary: Redoop is the first full-fledged MapReduce framework with native support for recurring big data queries, extending Hadoop core. Window-aware partitioning, cache-aware scheduling, and inter-window caching yield order-of-magnitude speedups for recurring workloads on click-stream and sensor data. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10827
Venue
VLDB
Year
2014
Pagerank
4.3667196e-05
Overall Rank
9,266 | 35.54%
DOI
-

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
3,625 Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings 2020 SIGMOD 6.9055212e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 4 of 4 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
413 HaLoop: Efficient Iterative Data Processing on Large Clusters 2010 VLDB 0.00023904409
2,476 A Platform for Scalable One-Pass Analytics using MapReduce 2011 SIGMOD 8.6960139e-05
4,425 Nova: Continuous Pig/Hadoop Workflows 2011 SIGMOD 6.198382e-05
4,857 The "Big Data" Ecosystem at LinkedIn 2013 SIGMOD 5.8736144e-05
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