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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
10828
Venue
VLDB
Year
2014
Pagerank
4.362604e-05
Overall Rank
9,270 | 35.58%
DOI
-

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
3,623 Cost Models for Big Data Query Processing: Learning, Retrofitting, and Our Findings 2020 SIGMOD 6.9017341e-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
408 HaLoop: Efficient Iterative Data Processing on Large Clusters 2010 VLDB 0.00023939456
2,476 A Platform for Scalable One-Pass Analytics using MapReduce 2011 SIGMOD 8.6907971e-05
4,424 Nova: Continuous Pig/Hadoop Workflows 2011 SIGMOD 6.19243e-05
4,859 The "Big Data" Ecosystem at LinkedIn 2013 SIGMOD 5.8680444e-05
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