Find records from one table which don't exist in another

Strategies for performance: NOT EXISTS, NOT IN, LEFT JOIN

Size matters, especially when talking about database tables. Optimal performance requires tailored strategies. Let's check them:

• Small tables? - use NOT IN

SELECT t1.*
FROM table1 t1
WHERE t1.id NOT IN (SELECT id FROM table2);
-- If the table was any smaller, we'd need a microscope! 


The NOT IN clause can be a nice fit for small tables.

• Large datasets? - NOT EXISTS is your friend

The NOT EXISTS tends to outperform NOT IN with larger data. The SQL engine executes queries differently based on these operations.

• Need more info? - LEFT JOIN is here to help

Fetch all columns from table1 for which a reference does not exist in table2.

SELECT t1.*
FROM table1 t1
LEFT JOIN table2 t2
ON t1.id = t2.id
WHERE t2.id IS NULL;
--LEFT or RIGHT, JOINs always bring us together!


A case for choosing specific columns

Chuck SELECT * out the window. Swapping it with necessary columns is the ticket to Efficiency Ville, reducing the transaction burden on your database.

SELECT t1.id, t1.name 
FROM table1 t1
WHERE NOT EXISTS (
    SELECT 1
    FROM table2 t2
    WHERE t1.id = t2.id
);
--Less is more? Definitely, when reducing DB transaction burden!


Dancing with the query optimizer

Different SQL engines have different dance moves (read: query optimizers). Find the rhythm that best suits your engine for spectacular performance!

Navigating through duplicates

Don't like doubles? Root them out using DISTINCT when joining tables to ensure unique records, specifically when table2 boasts about having multiple similar entries.

SELECT DISTINCT t1.*
FROM table1 t1
LEFT JOIN table2 t2
ON t1.id = t2.id
WHERE t2.id IS NULL;
-- The DISTINCT keyword reminds me of my childhood: "Mom, no more twins!"


Easy-reading code for the future

Using direct column comparisons and dodging subqueries when possible can earn you the trophy of code simplicity. It makes your code come across as a favorite novel that's easy to read and maintain.

SELECT t1.*
FROM table1 t1
LEFT JOIN table2 t2
ON t1.id = t2.id
WHERE t2.id IS NULL;
-- SQL poetry: simple, easy to read, and heartening. Also, gets the job done!


Test your queries—no surprises

Want to throw unwanted surprises out the window? Regularly test and validate your queries using sample data. This also shields you from unexpected performances.

Stay relevant amid schema changes

A schema can change faster than fashion trends! By sticking to specific columns instead of SELECT *, you can ensure your code's relevancy over time.

Boost efficiency with placeholders 'x'

In a NOT EXISTS subquery, placeholders 'x' or 1 serve as boosters for efficiency. These placeholders signal that we're checking for existence, not the data.

SELECT t1.*
FROM table1 t1
WHERE NOT EXISTS (
    SELECT 'x'
    FROM table2 t2
    WHERE t1.id = t2.id
);
-- Placeholder 'x', here to save the day!


Stay relevant: adaptation is key

As data grows and the database structure changes over time, it's essential to revisit and test your strategies regularly.

Unleash database-specific features

Every database has its own superpower—distinct syntax or functions such as EXCEPT in PostgreSQL. Swing these for optimal performance!

In conclusion, the best approach to find records from one table missing in another should align with your data and requirements. Whether you pick NOT EXISTS, NOT IN or LEFT JOIN, remember the mantra—performance matter.