Quantitative system performance: computer system analysis using queueing network models
Quantitative system performance: computer system analysis using queueing network models
Join processing in database systems with large main memories
ACM Transactions on Database Systems (TODS)
ISCA '88 Proceedings of the 15th Annual International Symposium on Computer architecture
The effect of bucket size tuning in the dynamic hybrid GRACE hash join method
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An analytic model of multistage interconnection networks
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SIGMETRICS '91 Proceedings of the 1991 ACM SIGMETRICS conference on Measurement and modeling of computer systems
Parallel database systems: the future of high performance database systems
Communications of the ACM
Query evaluation techniques for large databases
ACM Computing Surveys (CSUR)
Mean-Value Analysis of Closed Multichain Queuing Networks
Journal of the ACM (JACM)
ACM Computing Surveys (CSUR)
Implementation techniques for main memory database systems
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
The Gamma Database Machine Project
IEEE Transactions on Knowledge and Data Engineering
Effectiveness of Parallel Joins
IEEE Transactions on Knowledge and Data Engineering
Hashing Methods and Relational Algebra Operations
VLDB '84 Proceedings of the 10th International Conference on Very Large Data Bases
VLDB '88 Proceedings of the 14th International Conference on Very Large Data Bases
Using Segmented Right-Deep Trees for the Execution of Pipelined Hash Joins
VLDB '92 Proceedings of the 18th International Conference on Very Large Data Bases
Managing Memory to Meet Multiclass Workload Response Time Goals
VLDB '93 Proceedings of the 19th International Conference on Very Large Data Bases
Dynamic Memory Allocation for Multiple-Query Workloads
VLDB '93 Proceedings of the 19th International Conference on Very Large Data Bases
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SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
AMVA techniques for high service time variability
Proceedings of the 2000 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
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VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Mean Value Analysis: a Personal Account
Performance Evaluation: Origins and Directions
The VLDB Journal — The International Journal on Very Large Data Bases
Sing the truth about ad hoc join costs
The VLDB Journal — The International Journal on Very Large Data Bases
Improving query I/O performance by permuting and refining block request sequences
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Identifying robust plans through plan diagram reduction
Proceedings of the VLDB Endowment
Exploiting pipeline interruptions for efficient memory allocation
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Performance improvement of join queries through algebraic signatures
International Journal of Intelligent Information and Database Systems
ONE: a predictable and scalable DW model
DaWaK'11 Proceedings of the 13th international conference on Data warehousing and knowledge discovery
A predictable storage model for scalable parallel DW
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ICA3PP'12 Proceedings of the 12th international conference on Algorithms and Architectures for Parallel Processing - Volume Part I
Providing timely results with an elastic parallel DW
ISMIS'12 Proceedings of the 20th international conference on Foundations of Intelligent Systems
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The join of two relations is an important operation in database systems. It occurs frequently in relational queries, and join performance is a significant factor in overall system performance. Cost models for join algorithms are used by query optimizers to choose efficient query execution strategies. This paper presents an efficient analytical model of an important join method, the hybrid hash join algorithm, that captures several key features of the algorithm's performance—including its intra-operator parallelism, interference between disk reads and writes, caching of disk pages, and placement of data on disk(s). Validation of the model against a detailed simulation of a database system shows that the response time estimates produced by the model are quite accurate.