Algorithms & data structures
Tradeoffs in processing complex join queries via hashing in multiprocessor database machines
Proceedings of the sixteenth international conference on Very large databases
Randomized algorithms for optimizing large join queries
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
Parallel database systems: the future of database processing or a passing fad?
ACM SIGMOD Record - Directions for future database research & development
Query optimization for parallel execution
SIGMOD '92 Proceedings of the 1992 ACM SIGMOD international conference on Management of data
Industrial-strength parallel query optimization: issues and lessons
Information Systems
The art of computer programming, volume 1 (3rd ed.): fundamental algorithms
The art of computer programming, volume 1 (3rd ed.): fundamental algorithms
Optimization of parallel query execution plans in XPRS
PDIS '91 Proceedings of the first international conference on Parallel and distributed information systems
Prototyping DBS3, a shared-memory parallel database system
PDIS '91 Proceedings of the first international conference on Parallel and distributed information systems
Access path selection in a relational database management system
SIGMOD '79 Proceedings of the 1979 ACM SIGMOD international conference on Management of data
Parallel query processing with zigzag trees
The VLDB Journal — The International Journal on Very Large Data Bases - Parallelism in database systems
Prototyping Bubba, A Highly Parallel Database System
IEEE Transactions on Knowledge and Data Engineering
The Gamma Database Machine Project
IEEE Transactions on Knowledge and Data Engineering
ESQL2: An Object-Oriented SQL with F-Logic Semantics
Proceedings of the Eighth International Conference on Data Engineering
Buffering Schemes for Permanent Data
Proceedings of the Second International Conference on Data Engineering
R* Optimizer Validation and Performance Evaluation for Distributed Queries
VLDB '86 Proceedings of the 12th International Conference on Very Large Data Bases
On the Effectiveness of Optimization Search Strategies for Parallel Execution Spaces
VLDB '93 Proceedings of the 19th International Conference on Very Large Data Bases
A latency and fault-tolerance optimizer for online parallel query plans
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
ModParOpt: a modular query optimizer for multi-query parallel databases
ADBIS'97 Proceedings of the First East-European conference on Advances in Databases and Information systems
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The authors designed and implemented the DBS3 optimizer along three dimensions: search space, search strategy, and cost model. (The DBS3, or Database System on Shared Store, is a shared-memory prototype implemented on an Encore Multimax multiprocessor as part of Esprit's EDS project.) The search space is the set of alternative execution plans that represent the input query. These plans are equivalent in the sense that they yield the same result, but they differ in execution order and implementation of operations. Their new equivalence criterion captures all aspects of parallelism and scheduling in an execution plan. By not including scheduling, the optimizer may lose the better plans.The search strategy explores the search space and selects the best plan. It defines which plans are examined and in which order. Because the search space is large enough to include four types of processing trees, the optimizer uses efficient, nonexhaustive search strategies to reduce the cost of a large search space.The cost model predicts the cost of an execution plan. To be accurate, it needs some knowledge of the parallel execution environment. The cost model abstracts the parallel execution system as operator cost functions and the database as physical schema information. In a parallel database system, the richness of the execution environment makes cost modeling difficult. In contrast to sequential execution, a parallel execution plan uses intraoperation and interoperation parallelism. Interoperation parallelism includes dataflow, or pipeline, execution, as well as independent execution. The cost model's necessary simplifications introduce the potential for errors. The authors designed a cost model easily adaptable to either the distributed- or shared-memory target architecture. Thus, the DBS3 optimizer is portable to either architecture.