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» Join operations in temporal databases
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SIGMOD
2006
ACM
117views Database» more  SIGMOD 2006»
15 years 9 months ago
Database support for matching: limitations and opportunities
We define a match join of R and S with predicate to be a subset of the -join of R and S such that each tuple of R and S contributes to at most one result tuple. Match joins and t...
Ameet Kini, Srinath Shankar, Jeffrey F. Naughton, ...
AINA
2007
IEEE
15 years 1 months ago
Improving distributed join efficiency with extended bloom filter operations
Bloom filter based algorithms have proven successful as very efficient technique to reduce communication costs of database joins in a distributed setting. However, the full potent...
Loizos Michael, Wolfgang Nejdl, Odysseas Papapetro...
SIGMOD
1999
ACM
98views Database» more  SIGMOD 1999»
15 years 1 months ago
Integration of Spatial Join Algorithms for Processing Multiple Inputs
Several techniques that compute the join between two spatial datasets have been proposed during the last decade. Among these methods, some consider existing indices for the joined...
Nikos Mamoulis, Dimitris Papadias
VLDB
1995
ACM
121views Database» more  VLDB 1995»
15 years 1 months ago
Benchmarking Spatial Join Operations with Spatial Output
The spatial join operation is benchmarked using variants of well-known spatial data structures such as the R-tree, R-tree, R+-tree, and the PMR quadtree. The focus is on a spatia...
Erik G. Hoel, Hanan Samet
DANTE
1999
IEEE
149views Database» more  DANTE 1999»
15 years 1 months ago
Parallel R-Tree Spatial Join for a Shared-Nothing Architecture
The growing importance of spatial data has made it imperative that spatial operations be executed efficiently. The most expensive operation is the join for spatial databases. This...
Lawrence Mutenda, Masaru Kitsuregawa