Basic Row-Level Security with Views and PostgreSQL Session Variables
Implement simple row-level security in PostgreSQL by filtering data in views based on a session-specific user ID, restricting access to sensitive information.
Curated list of production-ready SQL scripts and coding solutions.
Implement simple row-level security in PostgreSQL by filtering data in views based on a session-specific user ID, restricting access to sensitive information.
Enhance the readability and maintainability of complex SQL queries by breaking them down into logical, reusable steps using non-recursive Common Table Expressions (CTEs).
Learn to create flexible summary reports in SQL by aggregating data based on conditions, simulating pivot table behavior without a dedicated PIVOT function.
Discover how to efficiently query for parent records that do not have any corresponding child records using a LEFT JOIN and WHERE clause for data integrity checks.
Master using the LAG window function to determine the duration between an event and its preceding event, crucial for temporal analysis and time-series data.
Implement a robust search feature across multiple text columns using LIKE or ILIKE for case-insensitive matching and wildcard characters, enhancing user search experience.
Learn to group and summarize data by various time granularities like hourly, daily, or monthly, essential for trend analysis and dashboard reporting.
Learn to use SQL window functions like ROW_NUMBER(), RANK(), and DENSE_RANK() to assign ranks to records within specified groups, perfect for leaderboards or top N queries.
Master the SQL `INSERT ... ON CONFLICT DO UPDATE` statement in PostgreSQL for atomic upsert operations, efficiently inserting new rows or updating existing ones based on unique constraints.
Learn to implement robust data pagination in SQL using `LIMIT` and `OFFSET` clauses, essential for displaying large datasets in web applications without performance bottlenecks.
Learn to navigate and query tree-like or hierarchical data structures in SQL using powerful recursive Common Table Expressions (CTEs), ideal for categories, comments, or organizational charts.
Efficiently remove duplicate rows from a SQL table, preserving a single unique entry based on a chosen primary key or unique identifier, for robust data cleanup.