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SQL Nulls and Two-Valued Logic

Authors: Libkin, Leonid; Peterfreund, Liat;

SQL Nulls and Two-Valued Logic

Abstract

The design of SQL is based on a three-valued logic (3VL), rather than the familiar two-valued Boolean logic (2VL). In addition to true and false, 3VL adds unknown to handle nulls. Viewed as indispensable for SQL expressiveness, it is often criticized for unintuitive behavior of queries and for being a source of programmer mistakes. We show that, contrary to the widely held view, SQL could have been designed based on 2VL, without any loss of expressiveness. Similarly to SQL’s WHERE clause, which only keeps true tuples, we conflate false and unknown for conditions involving nulls to obtain an equally expressive 2VL-based version of SQL. This applies to the core of the 1999 SQL Standard. Queries written under the 2VL semantics can be efficiently trans lated into the 3VL SQL and thus executed on any existing RDBMS. We show that 2VL enables additional optimizations. To gauge its applicability, we establish criteria under which 2VL and 3VL seman tics coincide, and analyze common benchmarks such as TPC-H and TPC-DS to show that most of their queries are such. For queries that behave differently under 2VL and 3VL, we undertake a user study to show a consistent preference for the 2VL semantics.

Keywords

SQL, User study, boolean logic, Boolean logic, user study, three-valued logic, nulls, query equivalence, Nulls, Three-valued logic, Query equivalence, [INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB], Query optimization, query optimization

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green