Processing aggregate relational queries with hard time constraints
SIGMOD '89 Proceedings of the 1989 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
Congressional samples for approximate answering of group-by queries
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Real-Time Database Systems in the New Millenium
Real-Time Systems
Informix under CONTROL: Online Query Processing
Data Mining and Knowledge Discovery
Time-Constrained Query Processing in CASE-DB
IEEE Transactions on Knowledge and Data Engineering
Reducing the Braking Distance of an SQL Query Engine
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Evaluating Top-k Selection Queries
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Probabilistic Optimization of Top N Queries
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Large-Sample and Deterministic Confidence Intervals for Online Aggregation
SSDBM '97 Proceedings of the Ninth International Conference on Scientific and Statistical Database Management
Dynamic sample selection for approximate query processing
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Toward a progress indicator for database queries
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Estimating progress of execution for SQL queries
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Supporting top-k join queries in relational databases
The VLDB Journal — The International Journal on Very Large Data Bases
Real-Time Databases and Data Services
Real-Time Systems
Increasing the Accuracy and Coverage of SQL Progress Indicators
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
When can we trust progress estimators for SQL queries?
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
An efficient SQL-based RDF querying scheme
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Cost-based query transformation in Oracle
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Estimating aggregates in time-constrained approximate queries in Oracle
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Data warehouse technology by infobright
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
An experimental study of time-constrained aggregate queries
Proceedings of the 13th International Conference on Extending Database Technology
Towards approximate SQL: infobright's approach
RSCTC'10 Proceedings of the 7th international conference on Rough sets and current trends in computing
Randomized accuracy-aware program transformations for efficient approximate computations
POPL '12 Proceedings of the 39th annual ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Hi-index | 0.00 |
The growing nature of databases, and the flexibility inherent in the SQL query language that allows arbitrarily complex formulations, can result in queries that take inordinate amount of time to complete. To mitigate this problem, strategies that are optimized to return the 'first-few rows' or 'top-k rows' (in case of sorted results) are usually employed. However, both these strategies can lead to unpredictable query processing times. Thus, in this paper we propose supporting time-constrained SQL queries. Specifically, a user issues a SQL query as before but additionally provides nature of constraint (soft or hard), an upper bound for query processing time, and acceptable nature of results (partial or approximate). The DBMS takes the criteria (constraint type, time limit, quality of result) into account in generating the query execution plan, which is expected (guaranteed) to complete in the allocated time for soft (hard) time constraint. If partial results are acceptable then the technique of reducing result set cardinality (i.e. returning first few or top-k rows) is used, whereas if approximate results are acceptable then sampling is used, to compute query results within the specified time limit. For the latter case, we argue that trading off quality of results for predictable response time is quite useful. However, for this case, we provide additional aggregate functions to estimate the aggregate values and to compute the associated confidence interval. This paper presents the notion of time-constrained SQL queries, discusses the challenges in supporting such a construct, describes a framework for supporting such queries, and outlines its implementation in Oracle Database by exploiting Oracle's cost-based optimizer and extensibility capabilities.