Incomplete Information in Relational Databases
Journal of the ACM (JACM)
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
Update semantics of relational views
ACM Transactions on Database Systems (TODS)
Tracing the lineage of view data in a warehousing environment
ACM Transactions on Database Systems (TODS)
On propagation of deletions and annotations through views
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
On the provenance of non-answers to queries over extracted data
Proceedings of the VLDB Endowment
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Provenance in Databases: Why, How, and Where
Foundations and Trends in Databases
Subsumption and complementation as data fusion operators
Proceedings of the 13th International Conference on Extending Database Technology
How to ConQueR why-not questions
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
SnipSuggest: context-aware autocompletion for SQL
Proceedings of the VLDB Endowment
The complexity of causality and responsibility for query answers and non-answers
Proceedings of the VLDB Endowment
Explaining missing answers to SPJUA queries
Proceedings of the VLDB Endowment
QueryViz: helping users understand SQL queries and their patterns
Proceedings of the 14th International Conference on Extending Database Technology
Answering Why-not Questions on Top-k Queries
ICDE '12 Proceedings of the 2012 IEEE 28th International Conference on Data Engineering
The nautilus analyzer: understanding and debugging data transformations
Proceedings of the 21st ACM international conference on Information and knowledge management
Observing SQL queries in their natural habitat
ACM Transactions on Database Systems (TODS)
| Hi-index | 0.00 |
In analyzing and debugging data transformations, or more specifically relational queries, a subproblem is to understand why some data are not part of the query result. This problem has recently been addressed from different perspectives for various fragments of relational queries. The different perspectives yield different, yet complementary explanations of such missing-answers. This paper first aims at unifying the different approaches by defining a new type of explanation, called hybrid explanation, that encompasses the variety of previously defined types of explanations. This solution goes beyond simply forming the union of explanations produced by different algorithms and is shown to be able to explain a larger set of missing-answers. Second, we present Conseil, an algorithm to generate hybrid explanations. Conseil is also the first algorithm to handle non-monotonic queries. Experiments on efficiency and explanation quality show that Conseil is comparable to and even outperforms previous algorithms.