NEURON: An Interactive Natural Language Interface for Understanding Query Execution Plans in RDBMS

05/15/2018
by   Siyuan Liu, et al.
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Natural language interfaces for relational databases have been explored for several decades. Majority of the work have focused on translating natural language sentences to SQL queries or narrating SQL queries in natural language. Scant attention has been paid for natural language understanding of query execution plans (QEP) of SQL queries. In this demonstration, we present a novel generic system called NEURON that facilitates natural language interaction with QEPs. NEURON accepts a SQL query (which may include joins, aggregation, nesting, among other things) as input, executes it, and generates a natural language-based description (both in text and voice form) of the execution strategy deployed by the underlying RDBMS. Furthermore, it facilitates understanding of various features related to the QEP through a natural language-based question answering framework. NEURON can be potentially useful to database application developers in comprehending query execution strategies and to database instructors and students for pedagogical support.

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