Partially preemptible hash joins
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
ACM Computing Surveys (CSUR)
Efficient mid-query re-optimization of sub-optimal query execution plans
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Cost-based query scrambling for initial delays
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
The grid: blueprint for a new computing infrastructure
The grid: blueprint for a new computing infrastructure
Dynamic Query Operator Scheduling for Wide-Area Remote Access
Distributed and Parallel Databases
Cluster I/O with River: making the fast case common
Proceedings of the sixth workshop on I/O in parallel and distributed systems
Ripple joins for online aggregation
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
An adaptive query execution system for data integration
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Eddies: continuously adaptive query processing
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Scrambling query plans to cope with unexpected delays
DIS '96 Proceedings of the fourth international conference on on Parallel and distributed information systems
Optimizations Enabled by Relational Data Model View to Querying Data Streams
IPDPS '01 Proceedings of the 15th International Parallel & Distributed Processing Symposium
Dynamic Memory Adjustment for External Mergesort
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Dynamic Pipeline Scheduling for Improving Interactive Query Performance
Proceedings of the 27th International Conference on Very Large Data Bases
Memory-Adaptive External Sorting
VLDB '93 Proceedings of the 19th International Conference on Very Large Data Bases
The VLDB Journal — The International Journal on Very Large Data Bases
Invited Address: An Overview of Parallel Query Optimization in Relational Systems
DEXA '00 Proceedings of the 11th International Workshop on Database and Expert Systems Applications
dQUOB: Managing Large Data Flows Using Dynamic Embedded Queries
HPDC '00 Proceedings of the 9th IEEE International Symposium on High Performance Distributed Computing
SSDBM '99 Proceedings of the 11th International Conference on Scientific and Statistical Database Management
Dynamic Query Scheduling in Data Integration Systems
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
Continuous Query Optimization
Optimizing progressive query-by-example over pre-clustered large image databases
Proceedings of the 2nd international workshop on Computer vision meets databases
Active Integration of Databases in Grids for Scalable Distributed Query Processing
OTM '08 Proceedings of the OTM 2008 Confederated International Conferences, CoopIS, DOA, GADA, IS, and ODBASE 2008. Part I on On the Move to Meaningful Internet Systems:
Evolution of Query Optimization Methods: From Centralized Database Systems to Data Grid Systems
DEXA '09 Proceedings of the 20th International Conference on Database and Expert Systems Applications
Automation everywhere: autonomics and data management
BNCOD'07 Proceedings of the 24th British national conference on Databases
Dynamic query optimisation: towards decentralised methods
International Journal of Intelligent Information and Database Systems
Optimizing adaptive multi-route query processing via time-partitioned indices
Journal of Computer and System Sciences
Optimizing SPARQL query answering over OWL ontologies
Journal of Artificial Intelligence Research
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In wide-area database systems, which may be running on unpredictable and volatile environments (such as computational grids), it is difficult to produce efficient database query plans based on information available solely at compile time. A solution to this problem is to exploit information that becomes available at query runtime and adapt the query plan to changing conditions during execution. This paper presents a survey on adaptive query processing techniques, examining the opportunities they offer to modify a plan dynamically and classifying them into categories according to the problem they focus on, their objectives, the nature of feedback they collect from the environment, the frequency at which they can adapt, their implementation environment and which component is responsible for taking the adaptation decisions.