What’s missing? What matches in one table but not another? MySQL (and SQL in general) have a way to find out. More than likely, when working with a normalized database, you are faced with these types of questions. Querying multiple tables with JOIN‘s on matched values, only goes so far to answering this type of question. We will see how to leverage an OUTER JOIN, for these requests.
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JOINS
INNER JOIN in MySQL with examples.
To normalize data, we often store it in several tables within a given database. While querying those tables individually can provide answers to numerous questions around that data, more times than not, it leaves us ‘coming up short’ for the complete answer we need.
That poses the question of, how do you extract all this data from several tables that depend on one another to provide data-driven answers?
One tried and true method is to use a JOIN operation.
Fabulous fabrication asset tracking using JOINS in PostgreSQL
This post will demonstrate mock asset tracking with PostgreSQL for a pipe fabrication setting. The typical data one would track and record in this setting are bends, weld id’s, and joints of pipe. We will see powerful queries from multiple tables, return informative and useful data with the JOIN command.