Example of a Non-Key Join:
In most practical scenarios, SQL joins aren’t limited to primary key–foreign key joins. Instead, data might be joined by comparisons, ranges, or some other business rule as determined by analysts or developers. For instance, let’s say we’re interested in finding employees whose hourly pay is higher than the spend-per-hour available for some projects. It then becomes easy to recognize where management’s investments in resources will be financially untenable from a high-level standpoint.
English Sentence:
“Retrieve the employees and the projects where the employee’s hourly wage is greater than the project’s budget-per-hour.”
SQL Query:
SELECT e.employee_id,
e.name,
e.hourly_wage,
p.project_id,
p.project_name,
p.budget_per_hour
FROM Employees e
JOIN Projects p
ON e.hourly_wage > p.budget_per_hour;
This query does not join on a key relationship but instead applies a business rule (hourly_wage > budget_per_hour). These joins come into consideration where comparing values between two things is more helpful than retrieving exact matches. More examples would include joining orders to ship dates where the order date is ahead of the ship window, or matching customers to campaign promotions by spend range rather than by unique identifier.
Opinion on SQL as a Language:
SQL is a very technical but highly adaptable language. It is a declarative language unlike procedural programming languages because instead of specifying step-by-step instructions where to retrieve data, the user tells SQL what data they desire. It then internally optimizes queries to be efficient and convenient for the user.
From a learning standpoint, SQL is easy to access because much of SQL’s syntax is English-like. Commands such as SELECT, FROM, and WHERE read almost as one would command with everyday language. SQL has depths to its complexity that come with higher-level operations such as subqueries, window functions, and recursive queries. Because of these reasons among others, SQL is easy to teach to beginners but substantial enough to handle high-level analysis of data.
Converting an English question into SQL is sometimes difficult, especially if the query is one that involves:
– Complex joins with several tables where relations are complex.
– Grouping with conditions, e.g., to collect departments with an average salary above a given value.
– Less intuitive initially are set operations such as EXISTS, NOT EXISTS, INTERSECT, or UNION.
– Nested subqueries or correlated subqueries where one has to retain more than one query scope simultaneously.
Despite these hurdles, SQL is fun to learn for me because results of queries immediately turn into something tangible. SQL queries can transform raw unstructured data into usable information if coded correctly. In a work environment, such capability is needed to support decisions, produce reports, and write application programming. SQL is both broad and deep. It is straightforward to glance at initially because English-like commands are present, but to be competent with it requires practice as well as critical thinking. Being able to translate business questions into SQL queries is something beyond syntax; it is a deep understanding of the data model as well as the data’s intrinsic relationships. It is a combination of depth with shallowness which renders SQL a