Optimization of nested SQL queries revisited
SIGMOD '87 Proceedings of the 1987 ACM SIGMOD international conference on Management of data
On optimizing an SQL-like nested query
ACM Transactions on Database Systems (TODS)
A genetic approach for random testing of database systems
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Interactive plan hints for query optimization
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Observing SQL queries in their natural habitat
ACM Transactions on Database Systems (TODS)
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We demonstrate Habitat, a declarative observational debugger for SQL. Habitat facilitates true language-level (not: plan-level) debugging of, probably flawed, SQL queries that yield unexpected results. Users may mark arbitrary SQL subexpressions---ranging from literals, over fragments of predicates, to entire subquery blocks---to observe whether these evaluate as expected. From the marked SQL text, Habitat's algebraic compiler derives a new query whose result represents the values of the desired observations. These observations are generated by the target SQL database host itself. Prior data extraction or extra debugging middleware is not required. Habitat merges multiple observations into a single (nested) tabular display, letting a user explore the relationship of various observations. Filter predicates furthermore ease the interpretation of large results.