Optimizing JSON Query Performance in PostgreSQL for Integration Work - Best Practices Needed
I've tried everything I can think of but I've encountered a strange issue with Currently developing a data integration layer using PostgreSQL that heavily interacts with JSON data... The JSON blobs contain various nested objects, and efficient querying is crucial for performance since we expect high transaction volumes. For example, I'm working with a table structured as follows: ```sql CREATE TABLE user_data ( id SERIAL PRIMARY KEY, info JSONB NOT NULL ); ``` I've been using the `jsonb` type for better indexing and querying capabilities. My queries often look like this: ```sql SELECT id, info->>'name' AS name FROM user_data WHERE info->>'status' = 'active'; ``` Despite this, performance is lagging when filtering by multiple keys. I tried creating indexes like so: ```sql CREATE INDEX idx_status ON user_data USING gin (info jsonb_path_ops); ``` However, I still notice slow execution times, especially when the `info` JSON object becomes quite large. I've also experimented with `jsonb_each` and `jsonb_array_elements` but found them to be slower in my use cases. Is there a more effective way to structure my queries or optimize how I'm storing the JSON data? I've read about using `jsonb` in combination with functional indexes, but I'm uncertain how to implement this effectively without increasing complexity. Any best practices or tips on improving performance would be greatly appreciated, especially in a high-load environment. I'd be grateful for any help. Could someone point me to the right documentation?