What are the most important standards for writing high-quality queries?

=> Using upper case to represent the reserved key words, and following naming conventions and commenting your code is easily overlooked but absolutely necessary. => Try to write a SQL query in as many different ways as possible. Understand and analyze your query to check if that can be optimized in any way. For example, you could leverage the sub-queries when there is a scope to avoid a join. Always remember that joins are costly operations and would consume a lot of resources if performed on huge tables. Understand the difference between various kinds of joins. => Work on real-world datasets. => Use efficient Indexing strategies. => Use EXPLAIN command to understand the semantics of your query and perform necessary optimizations.

In my experience - Use Indexes Wisely - Optimize Where clause - Use Joins effectively - Avoid cursors in Stored Procedures - Parametrised Query These are some high level standards would definitely help.

Use the appropriate type of JOIN (INNER JOIN, LEFT JOIN, etc.) based on your data requirements. Ensure ON or WHERE conditions are correctly specified to avoid Cartesian products. Minimize the use of subqueries when possible. Use the WHERE clause to filter rows early in the query to improve performance. Utilize indexing where applicable to speed up the filtering process. Know the indexes on your tables and leverage them for performance improvements. Avoid over-indexing, as it can lead to increased storage and maintenance overhead. Instead of using SELECT *, explicitly list the columns you need. Format your SQL queries for readability. Use indentation, line breaks, and consistent spacing to enhance clarity.

Use consistent formatting. Follow naming conventions. Use comments and documentation. Optimize your query performance. Test and validate your queries. Here's what else to consider.

It is also possible to use a query-tool (such as DataGrip) to format a query. That usually cleans it up quite well.

Choose meaningful and descriptive names for tables, columns, and aliases. This improves code readability and makes it easier for others to understand your queries.

I’ve found it helpful to add single line “—“ comments at the end of query lines that might be confusing or unclear in purpose. Also, don’t forget to include comments that contain sample parameters, so the user has something to reference when testing the query.

Code reusability is not always going to come with better performance. Under certain circumstances we might prefer to duplicate code to achieve better performance.

Cache Aggressively: Benefit: Caching reference data and handling joins in the application layer can vastly improve performance in systems with heavy read operations. Key Consideration: Implement a robust invalidation strategy for cached entities to ensure data consistency and freshness.

One thing that gets overlooked all the time is implicit versus explicit conversion. SQL Server like many Microsoft products attempts to make it easy on the end user at the cost of performance. I’ll give you an example if you want the date for tomorrow you could say give me today’s date +1. What happens to make this convenient for you is called “implicit conversion” aka “I know what you mean I’ll do it for you anyway even if one is a daytime and the other is int.” Code should be written, only using explicit conversion. There is an I/O difference between 1.0+2.0 (both floats/real) and 1.0 + 2 (float/real and int datatypes)

It is very important to test functionality with real data in all aspects (table size, data distribution to name a couple) to better assess performance and expectations. Code review is very important to be performed by someone with enough knowledge that can both review the code as well as its output.

- Write integration tests that cover your queries, supported by a mock database. This provides holistic coverage and verifies everything in context, ensuring that queries perform as expected when interacting with other parts of the system. - Conduct code reviews or peer reviews for additional feedback and suggestions.

Here are some standards to follow: Use Indexing: Properly index columns used in WHERE clauses, JOIN conditions, and ORDER BY clauses. This can significantly improve query performance. Optimize JOIN Operations: Minimize the use of unnecessary joins, and use appropriate join types (INNER JOIN, LEFT JOIN, etc.). Be mindful of the impact on query execution time. Limit Result Sets: Retrieve only the necessary columns instead of selecting all. This reduces the amount of data transferred and enhances performance. *Avoid SELECT : Explicitly list the columns you need rather than using SELECT * to ensure that unnecessary data isn't retrieved.