Features Of SQL Research Articles

A Formalization of SQL with Nulls

SQL is the world’s most popular declarative language, forming the basis of the multi-billion-dollar database industry. Although SQL has been standardized, the full standard is based on ambiguous natural language rather than formal specification. Commercial SQL implementations interpret the standard in different ways, so that, given the same input data, the same query can yield different results depending on the SQL system it is run on. Even for a particular system, mechanically checked formalization of all widely-used features of SQL remains an open problem. The lack of a well-understood formal semantics makes it very difficult to validate the soundness of database implementations. Although formal semantics for fragments of SQL were designed in the past, they usually did not support set and bag operations, lateral joins, nested subqueries, and, crucially, null values. Null values complicate SQL’s semantics in profound ways analogous to null pointers or side-effects in other programming languages. Since certain SQL queries are equivalent in the absence of null values, but produce different results when applied to tables containing incomplete data, semantics which ignore null values are able to prove query equivalences that are unsound in realistic databases. A formal semantics of SQL supporting all the aforementioned features was only proposed recently. In this paper, we report about our mechanization of SQL semantics covering set/bag operations, lateral joins, nested subqueries, and nulls, written in the Coq proof assistant, and describe the validation of key metatheoretic properties. Additionally, we are able to use the same framework to formalize the semantics of a flat relational calculus (with null values), and show a certified translation of its normal forms into SQL.

HoTTSQL: proving query rewrites with univalent SQL semantics

Every database system contains a query optimizer that performs query rewrites. Unfortunately, developing query optimizers remains a highly challenging task. Part of the challenges comes from the intricacies and rich features of query languages, which makes reasoning about rewrite rules difficult. In this paper, we propose a machine-checkable denotational semantics for SQL, the de facto language for relational database, for rigorously validating rewrite rules. Unlike previously proposed semantics that are either non-mechanized or only cover a small amount of SQL language features, our semantics covers all major features of SQL, including bags, correlated subqueries, aggregation, and indexes. Our mechanized semantics, called HoTT SQL, is based on K-Relations and homotopy type theory, where we denote relations as mathematical functions from tuples to univalent types. We have implemented HoTTSQL in Coq, which takes only fewer than 300 lines of code and have proved a wide range of SQL rewrite rules, including those from database research literature (e.g., magic set rewrites) and real-world query optimizers (e.g., subquery elimination). Several of these rewrite rules have never been previously proven correct. In addition, while query equivalence is generally undecidable, we have implemented an automated decision procedure using HoTTSQL for conjunctive queries: a well studied decidable fragment of SQL that encompasses many real-world queries.

What.s new in SQL:2011

SQL:2011 was published in December 2011, replacing the former version (SQL:2008) as the most recent update to the SQL standard for relational databases. This paper surveys the new non-temporal features of SQL:2011.

A practical guide to SQL white-box testing

SQL is a ubiquitous language used in a wide range of applications for accessing the data stored in relational databases. However, the usual software testing techniques are not designed to address some important features of SQL. We present a set of practical guidelines for designing white-box tests cases that reasonably exercise the way in which an SQL query processes the stored data. These guidelines are illustrated using an example.

A survey on usage of SQL

Relational database systems have been on market for more than a decade. SQL has been accepted as the standard query language of relational systems. To further understand the usage of relational systems and relational query language SQL, we conducted a survey recently that covers various aspects of the usage of SQL in industrial organizations. In this paper, we present those results that may interest DBMS researcher and developers, including the profiles of SQL users, the application areas where SQL is used, the usage of different features of SQL and difficulties encountered by SQL users.

Intelligent SQL

Intelligent SQL is an intelligent database engine interface language which incorporates object-oriented, inferencing, and multi-media constructs. It is intended to be a powerful extension of existing SQL dialects. It also provides querying capabilities for object-oriented databases. Intelligent SQL was prototyped at Ashton-Tate. This paper discusses the main features of Intelligent SQL.

OMEGA: A database management system for academic use

This paper describes an implementation of the relational database management system, OMEGA. OMEGA is designed to be "query language independent" in order to promote the investigation of experimental query languages by graduate students. OMEGA also supports the query language SQL and as such, is used in undergraduate database courses to demonstrate the features of SQL.

On optimizing an SQL-like nested query

SQL is a high-level nonprocedural data language which has received wide recognition in relational databases. One of the most interesting features of SQL is the nesting of query blocks to an arbitrary depth. An SQL-like query nested to an arbitrary depth is shown to be composed of five basic types of nesting. Four of them have not been well understood and more work needs to be done to improve their execution efficiency. Algorithms are developed that transform queries involving these basic types of nesting into semantically equivalent queries that are amenable to efficient processing by existing query-processing subsystems. These algorithms are then combined into a coherent strategy for processing a general nested query of arbitrary complexity.