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PVLDB
2008
182views more  PVLDB 2008»
13 years 7 months ago
SCOPE: easy and efficient parallel processing of massive data sets
Companies providing cloud-scale services have an increasing need to store and analyze massive data sets such as search logs and click streams. For cost and performance reasons, pr...
Ronnie Chaiken, Bob Jenkins, Per-Åke Larson,...
WWW
2011
ACM
13 years 2 months ago
Counting triangles and the curse of the last reducer
The clustering coefficient of a node in a social network is a fundamental measure that quantifies how tightly-knit the community is around the node. Its computation can be reduce...
Siddharth Suri, Sergei Vassilvitskii
BMCBI
2011
12 years 11 months ago
Faster Smith-Waterman database searches with inter-sequence SIMD parallelisation
Background: The Smith-Waterman algorithm for local sequence alignment is more sensitive than heuristic methods for database searching, but also more time-consuming. The fastest ap...
Torbjørn Rognes
PVLDB
2011
12 years 10 months ago
Merging What's Cracked, Cracking What's Merged: Adaptive Indexing in Main-Memory Column-Stores
Adaptive indexing is characterized by the partial creation and refinement of the index as side effects of query execution. Dynamic or shifting workloads may benefit from prelimi...
Stratos Idreos, Stefan Manegold, Harumi A. Kuno, G...
SIGMOD
2009
ACM
132views Database» more  SIGMOD 2009»
14 years 7 months ago
Core schema mappings
Research has investigated mappings among data sources under two perspectives. On one side, there are studies of practical tools for schema mapping generation; these focus on algor...
Giansalvatore Mecca, Paolo Papotti, Salvatore Raun...