Adaptive selectivity estimation using query feedback
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
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
Wavelet-based histograms for selectivity estimation
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
PDIS '94 Proceedings of the third international conference on on Parallel and distributed information systems
Sampling Issues in Parallel Database Systems
EDBT '92 Proceedings of the 3rd International Conference on Extending Database Technology: Advances in Database Technology
Handling Data Skew in Multiprocessor Database Computers Using Partition Tuning
VLDB '91 Proceedings of the 17th International Conference on Very Large Data Bases
A Taxonomy and Performance Model of Data Skew Effects in Parallel Joins
VLDB '91 Proceedings of the 17th International Conference on Very Large Data Bases
Modeling Skewed Distribution Using Multifractals and the `80-20' Law
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Selectivity Estimation Without the Attribute Value Independence Assumption
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
On Disk Allocation of Intermediate Query Results in Parallel Database Systems
Euro-Par '99 Proceedings of the 5th International Euro-Par Conference on Parallel Processing
An Adaptive Hash Join Algorithm on a Network of Workstations
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
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Skew effects are a serious problem in parallel database systems, but the relationship between different skew types and load balancing methods is still not fully understood. We develop and compare two classifications of skew effects and load balancing strategies, respectively, to match their relevant properties. Our conclusions highlight the importance of highly dynamic scheduling to optimize both the complexity and the success of load balancing. We also suggest the tuning of database schemata as a new anti-skew measure.