  Understanding the meaning of existing SQL queries is critical for code
maintenance and reuse. Yet SQL can be hard to read, even for expert users or
the original creator of a query. We conjecture that it is possible to capture
the logical intent of queries in \emph{automatically-generated visual diagrams}
that can help users understand the meaning of queries faster and more
accurately than SQL text alone. We present initial steps in that direction with
visual diagrams that are based on the first-order logic foundation of SQL and
can capture the meaning of deeply nested queries. Our diagrams build upon a
rich history of diagrammatic reasoning systems in logic and were designed using
a large body of human-computer interaction best practices: they are
\emph{minimal} in that no visual element is superfluous; they are
\emph{unambiguous} in that no two queries with different semantics map to the
same visualization; and they \emph{extend} previously existing visual
representations of relational schemata and conjunctive queries in a natural
way. An experimental evaluation involving 42 users on Amazon Mechanical Turk
shows that with only a 2--3 minute static tutorial, participants could
interpret queries meaningfully faster with our diagrams than when reading SQL
alone. Moreover, we have evidence that our visual diagrams result in
participants making fewer errors than with SQL. We believe that more regular
exposure to diagrammatic representations of SQL can give rise to a
\emph{pattern-based} and thus more intuitive use and re-use of SQL. All details
on the experimental study, the evaluation stimuli, raw data, and analyses, and
source code are available at https://osf.io/mycr2
