sqlquerypp is a library for preprocessing SQL queries. Main purpose
is writing highly optimized queries with a simplified syntax, allowing
for both maintainability and high performance.
Currently, only MySQL 8.4 syntax is supported.
SQL (Structed Query Language) follows a declarative paradigm, i.e. a query explains "what should be done" not "how should it be done". This stands in contrast to imperative programming, which expresses the "how should a certain task be fulfilled" aspect.
Database systems' internals are responsible for maintaining this aspect. But, however, for certain and large data structures, writing down "naive" queries sometimes result in poor performance.
Consider the following original query:
SELECT entity_b.*
FROM entity_b
INNER JOIN entity_a
ON entity_a.id = entity_b.entity_a_id
AND entity_a.criteria = 1337;
This is a very simplified example, but if you assume entity_b contains very
many items, even correct index conditions may exhaust any DBMS' join buffer.
An alternative approach might be doing a loop at application side (Python pseudocode), if network overhead is acceptable:
all_matches_in_entity_b = []
for entity_a_id in [rec.id
for rec in mysql_query("SELECT id FROM entity_a "
"WHERE criteria = 1337")]:
inner_result = mysql_query("SELECT * FROM entity_b "
f"WHERE entity_a_id = {entity_a_id}")
all_matches_in_entity_b += inner_result
The following statement, being no valid SQL, translates to a MySQL
native construct of Recursive Common Table Expression and UNION
fragments when being compiled by sqlquerypp. This allows for maximal
query performance, because the inner query with reduced complexity
is still taken into account. At the same time, it grants minimal I/O
overhead as only one query is executed on the database:
combined_result (SELECT id FROM entity_a WHERE criteria = 1337) AS $id {
SELECT * FROM entity_b WHERE entity_a_id = $id;
}