Join processing in database systems with large main memories
ACM Transactions on Database Systems (TODS)
VLDB '89 Proceedings of the 15th international conference on Very large data bases
Selectivity and cost estimation for joins based on random sampling
Journal of Computer and System Sciences
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Approximate computation of multidimensional aggregates of sparse data using wavelets
SIGMOD '99 Proceedings of the 1999 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
Ripple joins for online aggregation
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
A scalable hash ripple join algorithm
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Processing Real-Time, Non-Aggregate Queries with Time-Constraints in CASE-DB
Proceedings of the Eighth International Conference on Data Engineering
Random Sampling from Pseudo-Ranked B+ Trees
VLDB '92 Proceedings of the 18th 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
On producing join results early
Proceedings of the twenty-second ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Histograms revisited: when are histograms the best approximation method for aggregates over joins?
Proceedings of the twenty-fourth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
A disk-based join with probabilistic guarantees
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Online estimation for subset-based SQL queries
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Scalable approximate query processing with the DBO engine
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Progressive merge join: a generic and non-blocking sort-based join algorithm
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Turbo-charging estimate convergence in DBO
Proceedings of the VLDB Endowment
PR-join: a non-blocking join achieving higher early result rate with statistical guarantees
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Approximate query answering and result refinement on XML data
SSDBM'10 Proceedings of the 22nd international conference on Scientific and statistical database management
Beyond simple aggregates: indexing for summary queries
Proceedings of the thirtieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Metadata for approximate query answering systems
Advances in Software Engineering
Driver input selection for main-memory multi-way joins
Proceedings of the 28th Annual ACM Symposium on Applied Computing
Indexing for summary queries: Theory and practice
ACM Transactions on Database Systems (TODS)
A sampling algebra for aggregate estimation
Proceedings of the VLDB Endowment
| Hi-index | 0.00 |
This article describes query processing in the DBO database system. Like other database systems designed for ad hoc analytic processing, DBO is able to compute the exact answers to queries over a large relational database in a scalable fashion. Unlike any other system designed for analytic processing, DBO can constantly maintain a guess as to the final answer to an aggregate query throughout execution, along with statistically meaningful bounds for the guess's accuracy. As DBO gathers more and more information, the guess gets more and more accurate, until it is 100% accurate as the query is completed. This allows users to stop the execution as soon as they are happy with the query accuracy, and thus encourages exploratory data analysis.