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QUILTS: Multidimensional Partitioning Framework Based on Query-Aware and Skew-Tolerant Space-Filling Curves

Summary: QUILTS is a multidimensional partitioning framework using query-aware, skew-tolerant space-filling curves to minimize page accesses via data skipping. It offers a cost model and curve-design method tuned to query patterns and data skew, with experiments showing order-of-magnitude gains for DWH/GIS. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5300
Venue
SIGMOD
Year
2017
Pagerank
4.8909129e-05
Overall Rank
6,947 | 51.68%
DOI
10.1145/3035918.3035934

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

Rank Cited Paper Year Venue Pagerank
241 DB2 with BLU Acceleration: So Much More than Just a Column Store 2013 VLDB 0.00031420034
1,477 Fine-grained Partitioning for Aggressive Data Skipping 2014 SIGMOD 0.00011770865
2,485 Multiattribute Hashing Using Gray Codes. 1986 SIGMOD 8.6800526e-05
2,502 Integrating the UB-Tree into a Database System Kernel 2000 VLDB 8.6438339e-05
5,990 On the Optimality of Clustering Properties of Space Filling Curves 2012 PODS 5.2424347e-05
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