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Making Queries Tractable on Big Data with Preprocessing (through the eyes of complexity theory)

Summary: Formalizes offline preprocessing for big data with Pi-tractable queries (PiT0Q, PiTQ), enabling NC-time evaluation after PTIME preprocessing. PiT0Q ⊊ P unless P=NC; PiTQ = P via data/query refactorization and NC reductions, plus a PiTQ-complete class, advancing tractability in data management. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10732
Venue
VLDB
Year
2013
Pagerank
4.1905499e-05
Overall Rank
12,105 | 15.87%
DOI
-

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Incoming Citations (Sorted by Pagerank)

Showing 4 of 4 citing papers.

Rank Citing Paper Year Venue Pagerank
4,545 Bounded Conjunctive Queries 2014 VLDB 6.0917464e-05
7,061 Querying Big Data by Accessing Small Data 2015 PODS 4.8400281e-05
7,410 On Scale Independence for Querying Big Data 2014 PODS 4.7320027e-05
11,839 Logical Aspects of Massively Parallel and Distributed Systems 2016 PODS 4.1905499e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 6 of 6 cited papers.

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

Rank Cited Paper Year Venue Pagerank
8 Optimal Aggregation Algorithms for Middleware [Extended Abstract] 2001 PODS 0.0015436578
47 Data Integration: A Theoretical Perspective 2002 PODS 0.00069691761
387 Graph Summarization with Bounded Error 2008 SIGMOD 0.00024682268
1,114 Parallel Evaluation of Conjunctive Queries 2011 PODS 0.00013871948
1,572 Query Preserving Graph Compression 2012 SIGMOD 0.00011296109
1,806 Incremental Graph Pattern Matching 2011 SIGMOD 0.00010478244
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