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Select rows with id having an even number

sql
sql-performance
sql-best-practices
sql-queries
Nikita BarsukovbyNikita Barsukov·Jan 21, 2025
TLDR

Unearth even-numbered IDs utilizing the SQL modulo operator (% 2 = 0):

SELECT * FROM table WHERE id % 2 = 0;

Concentrate on id % 2 = 0 for filtering even IDs seamlessly.

How modulo aids in even selection

Modulo operator % is your saviour if you need to sieve out even IDs. This magic operator yields the remainder of a division operation, like id % 2 computes the remainder of ID divided by 2. As even numbers yield a remainder of 0, the condition id % 2 = 0 does the perfect job.

-- SQL is like a wise old man, it knows how to split evenly SELECT * FROM table WHERE id % 2 = 0;

Use "%" over "MOD()"

You might recall using MOD() from Oracle or MySQL, yet remember, MOD() isn't a universal SQL celebrity. For environments like SQL Server, % is the preferred choice, saving you from error nightmares.

Syntax etiquette is key

Tailoring your SQL syntax to your working environment is paramount. If you stumble upon errors using MOD(), it's a cue you might be navigating in SQL Server or another MOD()-unfriendly zone. Savvy SQL citizens always adapt their queries to resonate with the SQL dialect in use.

Efficiency champion: "%"

The % operator aids in crafting efficient and clean queries. When confronted with distinguishing even or odd numbers, % rises to the occasion like a champ.

Exploring important considerations

It's crucial to recognize that not all SQL environments speak the same language. For instance, in Oracle/PLSQL, the MOD() function would be your buddy. Always consult your SQL system's documentation when in a quandary.

Handling SQL edge-cases

Wondering what happens if your id column shelters null values or non-integer data? Be proactive and craft your query to judiciously handle any peculiarities lurking in your dataset.

Consideration for performance

The % operator is often efficient, but when handling large tables, ensure you appoint the right indexes. This will keep your queries snappy and save you from undesired full table scans, particularly in large datasets.