  A key learning goal of learners taking database systems course is to
understand how SQL queries are processed in an RDBMS in practice. To this end,
comprehension of the cost-based comparison of different plan choices to select
the query execution plan (QEP) of a query is paramount. Unfortunately,
off-the-shelf RDBMS typically only expose the selected QEP to users without
revealing information about representative alternative query plans considered
during QEP selection in a learner-friendly manner, hindering the learning
process. In this paper, we present a novel end-to-end and generic framework
called ARENA that facilitates exploration of informative alternative query
plans of a given SQL query to aid the comprehension of QEP selection. Under the
hood, ARENA addresses a novel problem called alternative plan selection problem
(TIPS) which aims to discover a set of k alternative plans from the underlying
plan space so that the plan interestingness of the set is maximized.
Specifically, we explore two variants of the problem, namely batch TIPS and
incremental TIPS, to cater to diverse set of learners. Due to the computational
hardness of the problem, we present a 2 approximation algorithm to address it
efficiently. Exhaustive experimental study with real-world learners
demonstrates the effectiveness of arena in enhancing learners' understanding of
the alternative plan choices considered during QEP selection.
