Performance Improvement for Collection Operations Using Join Query Optimization

Programming languages with explicit support for queries over collections allow programmers to express operations on collections more abstractly than relying on their realization in loops or through provided libraries. Join optimization techniques from the field of database technology support efficie...

Full description

Saved in:
Bibliographic Details
Main Authors: Nerella, Venkata Krishna Suhas, Madria, Sanjay Kumar, Weigert, Thomas
Format: Conference Proceeding
Language:English
Subjects:
Benchmark testing
Buildings
collection operations
Frequency estimation
Histograms
joins
Optimization
query optimization
Query processing
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Programming languages with explicit support for queries over collections allow programmers to express operations on collections more abstractly than relying on their realization in loops or through provided libraries. Join optimization techniques from the field of database technology support efficient realizations of such language constructs. We describe an algorithm that performs run-time query optimization and is effective for single runs of a program. The proposed approach relies on histograms built from the data at run time to estimate the selectivity of joins and predicates in order to construct query plans. Information from earlier executions of the same query during run time can be leveraged during the construction of the query plans, even when the data has changed between these executions. Experimental results demonstrate improvement over earlier approaches, such as JQL.
ISSN:0730-3157
DOI:10.1109/COMPSAC.2011.93