JOURNAL ARTICLE

Dataflow query execution in a parallel main-memory environment

Abstract

The performance and characteristics of the execution of various join-trees on a parallel DBMS are studied. The results are a step in the direction of the design of a query optimization strategy that is fit for parallel execution of complex queries. Among others, synchronization issues are identified to limit the performance gain from parallelism. A new hash-join algorithm, called pipelining hash-join is introduced that has fewer synchronization constraints than the known hash-join algorithms. Also, the behavior of individual join operations in a join-tree is studied in a simulation experiment. The results show that the pipelining hash-join algorithm yields a better performance for multi-join queries. Also, the format of the optimal join-tree appears to depend on the size of the operands of the join. The results from the simulation study are confirmed with an analytic model for dataflow query execution

Keywords:
Join (topology) Dataflow Computer science Hash join Parallel computing Hash function Operand Parallelism (grammar) Synchronization (alternating current) Theoretical computer science Query optimization Tree (set theory) Programming language Database Mathematics

Metrics

76
Cited By
4.88
FWCI (Field Weighted Citation Impact)
19
Refs
0.96
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Database Systems and Queries
Physical Sciences →  Computer Science →  Computer Networks and Communications
Data Management and Algorithms
Physical Sciences →  Computer Science →  Signal Processing
Advanced Data Storage Technologies
Physical Sciences →  Computer Science →  Computer Networks and Communications

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