An efficient algorithm for sequential random sampling
ACM Transactions on Mathematical Software (TOMS)
Query evaluation techniques for large databases
ACM Computing Surveys (CSUR)
On the estimation of join result sizes
EDBT '94 Proceedings of the 4th international conference on extending database technology: Advances in database technology
Reservoir-sampling algorithms of time complexity O(n(1 + log(N/n)))
ACM Transactions on Mathematical Software (TOMS)
Balancing histogram optimality and practicality for query result size estimation
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
On saying “Enough already!” in SQL
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Join synopses for approximate query answering
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Query Optimization in Database Systems
ACM Computing Surveys (CSUR)
Accurate estimation of the number of tuples satisfying a condition
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
Query languages for relational multidatabases
The VLDB Journal — The International Journal on Very Large Data Bases
Reducing the Braking Distance of an SQL Query Engine
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Aqua: A Fast Decision Support Systems Using Approximate Query Answers
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Simple Random Sampling from Relational Databases
VLDB '86 Proceedings of the 12th International Conference on Very Large Data Bases
SchemaSQL - A Language for Interoperability in Relational Multi-Database Systems
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
On Getting Some Answers Quickly, and Perhaps More Later
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
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Integrating, cleaning and analyzing data from heterogeneous sources is often complicated by the large amounts of data and its physical distribution which can result in poor query response time. One approach to speed up the processing is to reduce the cardinality of results - either by querying only the first tuples or by obtaining a sample for further processing. In this paper we address the processing of such queries in a multidatabase environment. We discuss implementations of the query operators, strategies for their placement in a query plan and particularly the usage of histograms for estimating attribute value distributions and result cardinalities in order to parameterize the operators.