Mysql - Selecting data from multiple tables all with same structure but different data

sql

database-engine

query-optimization

data-management

byAlex Kataev·Nov 15, 2024

To merge data from identically-structured tables, you can employ UNION ALL (if you wish to include duplicates) or simply UNION (if you prefer to weed out duplicates). For instance, using name from table1, table2, and table3 can be expressed as:

SELECT name FROM table1 -- Let's gather names, shall we?
UNION ALL            -- Feel the power of UNION ALL!
SELECT name FROM table2 
UNION ALL            -- ...And again!
SELECT name FROM table3;

This formulation pulls together all names. In contrast, UNION would only present a distinct array of names.

When combining identical structures, remember to:

Ensure column selection is explicit in broader queries, which may boost performance and minimizes transferred data.
Adopt table aliases to facilitate comprehension, particularly if JOINs are present or when the selection criteria are branched.

Add structure with refactoring

Work smarter, not harder! You can conveniently unite multiple tables bearing similar data into a single table by incorporating an additional categorical column, such as a language or country code. The result? A simplified query protocol and a single index.

For comprehensive datasets, building an index on the categorical column does wonders for performance. Take note of this sample code when selecting bespoke data:

SELECT title FROM movies_en WHERE genre = 'Sci-Fi' -- Extraterrestrials, anyone?
UNION ALL
SELECT title FROM movies_es WHERE genre = 'Ciencia Ficción'; -- More aliens, por favor.

Harnessing the power of partitioning

If you're dealing with massive datasets or need to optimise performance, MySQL's Merge database engine or UNION statements can part the Red Sea - I mean, simulate table partitioning. All the while, maintaining queries remains a walk in the park.

Path to optimal queries & potential potholes

Steer clear from unintentional JOINs which can drop performance like a hot potato. Clarification is key— ambiguous column referencing in WHERE or ORDER BY can trip up your code. Always pin down the table name or alias.

Here's a nifty example of a well-oiled query:

SELECT t1.name FROM table1 AS t1               -- Meet t1: our trusty alias!
WHERE t1.active = 1                            -- Active records only. No ghosts allowed!
UNION ALL
SELECT t2.name FROM table2 AS t2               -- Here comes t2, saving the day!
WHERE t2.active = 1                            -- Still no room for ghosts!
ORDER BY name;                                 -- Because we like to keep our ducks in a row.

Embrace advanced data management strategies

At the crossroads of handling a plethora of like-structured tables? Maybe it's time to trade up to a NoSQL database for versatility, or flirt with MySQL cluster technology for automated sharding and replication.

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