Aggregate-join query processing in parallel database systems

Queries containing aggregate functions often combine multiple tables through join operations. We call these queries "aggregate-join" queries. In parallel processing of such queries, it must be decided which attribute to be used as a partitioning attribute, particularly join attribute or gr...

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Bibliographic Details
Main Authors: Taniar, D., Jiang, Y., Liu, K.H., Leung, C.H.C.
Format: Conference Proceeding
Language:English
Subjects:
Aggregates
Cities and towns
Computer science
Data warehouses
Database systems
Decision making
Informatics
Parallel processing
Performance gain
Query processing
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Summary:Queries containing aggregate functions often combine multiple tables through join operations. We call these queries "aggregate-join" queries. In parallel processing of such queries, it must be decided which attribute to be used as a partitioning attribute, particularly join attribute or group-by attribute. Based on the partitioning attribute, we discuss three parallel aggregate-join query processing methods, namely: Join Partition Method (JPM), Aggregate Partition Method (APM), and Hybrid Partition Method (HPM). The JPM and APM models use the join attribute, and the group-by attribute, respectively, as the partitioning attribute. The HPM model combines the other two methods using a logically hybrid architecture.
DOI:10.1109/HPC.2000.843554