Distributed databases principles and systems
Distributed databases principles and systems
ACM Computing Surveys (CSUR)
An adaptive hash join algorithm for multiuser environments
Proceedings of the sixteenth international conference on Very large databases
Principles of distributed database systems
Principles of distributed database systems
Parallel database systems: the future of high performance database systems
Communications of the ACM
Query optimization for parallel execution
SIGMOD '92 Proceedings of the 1992 ACM SIGMOD international conference on Management of data
Parallel database systems: open problems and new issues
Distributed and Parallel Databases - Special issue: Research topics in distributed and parallel databases
Scheduling problems in parallel query optimization
PODS '95 Proceedings of the fourteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Optimization of SQL queries for parallel machines
Optimization of SQL queries for parallel machines
PDIS '93 Proceedings of the second international conference on Parallel and distributed information systems
Optimizing multi-join queries in parallel relational databases
PDIS '93 Proceedings of the second international conference on Parallel and distributed information systems
Parallel query processing in DBS3
PDIS '93 Proceedings of the second international conference on Parallel and distributed information systems
Optimization of parallel query execution plans in XPRS
PDIS '91 Proceedings of the first international conference on Parallel and distributed information systems
Prototyping Bubba, A Highly Parallel Database System
IEEE Transactions on Knowledge and Data Engineering
GAMMA - A High Performance Dataflow Database Machine
VLDB '86 Proceedings of the 12th 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
Multi-Join Optimization for Symmetric Multiprocessors
VLDB '93 Proceedings of the 19th International Conference on Very Large Data Bases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Coloring Away Communication in Parallel Query Optimization
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Complex query processing in multiprocessor database machines
Complex query processing in multiprocessor database machines
Open issues in parallel query optimization
ACM SIGMOD Record
Performance Studies of Shared-Nothing Parallel Transaction Processing Systems
PaCT '999 Proceedings of the 5th International Conference on Parallel Computing Technologies
Coloring Away Communication in Parallel Query Optimization
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Pipelined operator tree scheduling in heterogeneous environments
Journal of Parallel and Distributed Computing
Survey of Architectures of Parallel Database Systems
Programming and Computing Software
Parallelizing query optimization
Proceedings of the VLDB Endowment
Dependency-aware reordering for parallelizing query optimization in multi-core CPUs
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
OSDI'08 Proceedings of the 8th USENIX conference on Operating systems design and implementation
| Hi-index | 0.00 |
We describe the use of parallel execution techniques and measure the price of parallel execution in NonStop SQL/MP, a commercial parallel database system from Tandem Computers. Non-Stop SQL uses intra-operator parallelism to parallelize joins, groupings and scans. Parallel execution consists of starting up several processes and communicating data between them. Our measurements show (a) Startup costs are negligible when processes are reused rather than created afresh (b) Communication costs are significant — they may exceed the costs of operators such as scan, grouping or join. We also show two counter-examples to the common intuition that parallel execution reduces response time at the expense of increased work — parallel execution may reduce work or may increase response time depending on communication costs.