Parallel database systems: the future of high performance database systems
Communications of the ACM
Data-movement-intensive problems: two folk theorems in parallel computation revisited
Theoretical Computer Science
Highly parallel computing
Scheduling problems in parallel query optimization
PODS '95 Proceedings of the fourteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Open issues in parallel query optimization
ACM SIGMOD Record
Models and issues in data stream systems
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Characterizing memory requirements for queries over continuous data streams
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Parallel Algorithms and Architectures
Parallel Algorithms and Architectures
Continuous queries over data streams
ACM SIGMOD Record
PRISMA/DB: A Parallel, Main Memory Relational DBMS
IEEE Transactions on Knowledge and Data Engineering
Volcano— An Extensible and Parallel Query Evaluation System
IEEE Transactions on Knowledge and Data Engineering
Issues in data stream management
ACM SIGMOD Record
Chain: operator scheduling for memory minimization in data stream systems
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Design and Evaluation of Alternative Selection Placement Strategies in Optimizing Continuous Queries
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Performability modeling with stochastic activity networks
Performability modeling with stochastic activity networks
Aurora: a new model and architecture for data stream management
The VLDB Journal — The International Journal on Very Large Data Bases
Dynamic plan migration for continuous queries over data streams
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Operator scheduling in data stream systems
The VLDB Journal — The International Journal on Very Large Data Bases
Dynamic Load Distribution in the Borealis Stream Processor
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Adaptive query processing in data stream management systems
Adaptive query processing in data stream management systems
Online clustering of parallel data streams
Data & Knowledge Engineering
Load shedding in a data stream manager
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Tuple routing strategies for distributed eddies
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Operator scheduling in a data stream manager
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Self-tuning query mesh for adaptive multi-route query processing
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
PDETool: A Multi-formalism Modeling Tool for Discrete-Event Systems Based on SDES Description
PETRI NETS '09 Proceedings of the 30th International Conference on Applications and Theory of Petri Nets
Query mesh: multi-route query processing technology
Proceedings of the VLDB Endowment
Scheduling strategies and their evaluation in a data stream management system
BNCOD'06 Proceedings of the 23rd British National Conference on Databases, conference on Flexible and Efficient Information Handling
Dynamic plan migration for snapshot-equivalent continuous queries in data stream systems
EDBT'06 Proceedings of the 2006 international conference on Current Trends in Database Technology
Xtream: a system for continuous querying over uncertain data streams
SUM'12 Proceedings of the 6th international conference on Scalable Uncertainty Management
| Hi-index | 0.00 |
In this paper, we propose parallel processing of continuous queries over data streams to handle the bottleneck of single processor DSMSs. Queries are executed in parallel over the logical machines in a multiprocessing environment. Scheduling parallel execution of operators is performed via finding the shortest path in a weighted graph called Query Mega Graph (QMG), which is a logical view of K machines. By lapse of time, number of tuples waiting in queues of different operators may be very different. When a queue becomes full, re-scheduling is done by updating weight of edges of QMG. In the new computed path, machines with more workload will be used less. The proposed system is formally presented and its correctness is proved. It is also modeled in PetriNets and its performance is evaluated and compared with serial query processing as well as the Min-Latency scheduling algorithm. The presented system is shown to outperform them w.r.t. tuple latency (response time), memory usage, throughput and also tuple loss- critical parameters in any data stream management systems.