Paper Info
Title
Efficient many-core query execution in main memory column-stores
Abstract
We use the full query set of the TPC-H Benchmark as a case study for the efficient implementation of decision support queries on main memory column-store databases. Instead of splitting a query into separate independent operators, we consider the query as a whole and translate the execution plan into a single function performing the query. This allows highly efficient CPU utilization, minimal materialization, and execution in a single pass over the data for most queries. The single pass is performed in parallel and scales near-linearly with the number of cores. The resulting query plans for most of the 22 queries are remarkably simple and are suited for automatic generation and fast compilation. Using a data-parallel, NUMA-aware many-core implementation with block summaries, inverted index data structures, and efficient aggregation algorithms, we achieve one to two orders of magnitude better performance than the current record holders of the TPC-H Benchmark.
Year
DOI
Venue
2013
10.1109/ICDE.2013.6544838
ICDE
Keywords
Field
DocType
efficient cpu utilization,single function,full query,main memory column-stores,numa-aware many-core implementation,decision support query,efficient implementation,efficient aggregation algorithm,single pass,tpc-h benchmark,query plan,efficient many-core query execution,indexes,data structures,decision support systems,bandwidth,cpu utilization,instruction sets,benchmark testing
Query optimization,Data mining,Query language,RDF query language,Query expansion,Computer science,Sargable,Parallel computing,Web query classification,Spatial query,Online aggregation,Database
Conference
ISSN
Citations 
PageRank 
1084-4627
12
0.66
References 
Authors
21
2
Name
Order
Citations
PageRank
Jonathan Dees11637.51
Peter Sanders21957120.14