Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
41 tokens/sec
GPT-4o
59 tokens/sec
Gemini 2.5 Pro Pro
41 tokens/sec
o3 Pro
7 tokens/sec
GPT-4.1 Pro
50 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Design of an intermediate representation for query languages (1607.04197v1)

Published 14 Jul 2016 in cs.PL

Abstract: Data oriented applications, usually written in a high-level, general-purpose programming language (such as Java) interact with database through a coarse interface. Informally, the text of a query is built on the application side (either via plain string concatenation or through an abstract notion of statement) and shipped to the database over the wire where it is executed. The results are then serialized and sent back to the "client-code" where they are translated in the language's native datatypes. This round trip is detrimental to performances but, worse, such a programming model prevents one from having richer queries, namely queries containing user-defined functions (that is functions defined by the programmer and used e.g. in the filter condition of a SQL query). While some databases also possess a "server-side" language (e.g. PL/SQL in Oracle database), its integration with the very-optimized query execution engine is still minimal and queries containing (PL/SQL) user-defined functions remain notoriously inefficient. In this setting, we reviewed existing language-integrated query frameworks, highlighting that existing database query languages (including SQL) share high-level querying primitives (e.g., filtering, joins, aggregation) that can be represented by operators, but differ widely regarding the semantics of their expression language. In order to represent queries in an application language- and database-agnostic manner, we designed a small calculus, dubbed "QIR" for Query Intermediate Representation. QIR contains expressions, corresponding to a small extension of the pure lambda-calculus, and operators to represent usual querying primitives. In the effort to send efficient queries to the database, we abstracted the idea of "good" query representations in a measure on QIR terms. Then, we designed an evaluation strategy rewriting QIR query representations into "better" ones.

User Edit Pencil Streamline Icon: https://streamlinehq.com
Authors (1)
  1. Romain Vernoux (2 papers)
Citations (2)