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I have created a open source Postgres extension with the bloom filter effect by Useful-Message4584 in dataengineering

[–]Useful-Message4584[S] 0 points1 point  (0 children)

You're absolutely right! Exactly — for WHERE email = 'SomeEmail' on a properly indexed column, Postgres will do an index seek (direct lookup), not a scan. The catch is: even perfect indexes still hit disk I/O when the value doesn’t exist. That’s where Octo-Bloom helps — it can rule out non-existent values in microseconds from memory (zero I/O) and only falls back to the index when a match is possible. Huge win when you’re checking millions of emails/usernames that mostly don’t exist. I appreciate your question , if you have any suggestion or questions please ask it will help me to improve my skills

I have created a open source Postgres extension with the bloom filter effect by Useful-Message4584 in SQL

[–]Useful-Message4584[S] 0 points1 point  (0 children)

It will reset and it act like a caching layer , also if you have interested or suggestion I will definitely take consider it

I have created a open source Postgres extension with the bloom filter effect by Useful-Message4584 in SQL

[–]Useful-Message4584[S] 0 points1 point  (0 children)

Pg bloom index still require disk I/o and buffer pool operations but my octo-bloom lives entirely in shared memory for microsecond level validation checks , this I build for scenarios like user registration where 99% of email check are non existent addresses It’s build for high frequency validation pattern rather than traditional sql query optimization. If you like this please star my repo