SnipSuggest: Context-Aware Autocompletion for SQL

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SnipSuggest: Context-Aware Autocompletion for SQL
In this paper, we present SnipSuggest, a system that provides onthe-go, context-aware assistance in the SQL composition process. SnipSuggest aims to help the increasing population of non-expert database users, who need to perform complex analysis on their large-scale datasets, but have difficulty writing SQL queries. As a user types a query, SnipSuggest recommends possible additions to various clauses in the query using relevant snippets collected from a log of past queries. SnipSuggest’s current capabilities include suggesting tables, views, and table-valued functions in the FROM clause, columns in the SELECT clause, predicates in the WHERE clause, columns in the GROUP BY clause, aggregates, and some support for sub-queries. SnipSuggest adjusts its recommendations according to the context: as the user writes more of the query, it is able to provide more accurate suggestions. We evaluate SnipSuggest over two query logs: one from an undergraduate database class and another from the ...
Nodira Khoussainova, YongChul Kwon, Magdalena Bala
Added 30 Jan 2011
Updated 30 Jan 2011
Type Journal
Year 2010
Authors Nodira Khoussainova, YongChul Kwon, Magdalena Balazinska, Dan Suciu
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