"SELECT product_name, SUM(monthly_sales) AS total_monthly_sales, RANK() OVER (PARTITION BY category ORDER BY SUM(monthly_sales) DESC) AS sales_rank FROM `sales_data` WHERE EXTRACT(YEAR FROM sale_date) = 2023 GROUP BY product_name, category, EXTRACT(MONTH FROM sale_date) But it's still a far cry from being able to turn something like "/* give me a list of products by category, ranked by monthly sales in 2023 */" into a working query that does what the user wants."
"Robert Kramer, principal analyst at Moor Insights and Strategy, said those working with data tend to think in terms of questions and outcomes, not syntax. "Translating intent into accurate and efficient SQL still takes time, especially with joins, time logic, and repetitive patterns. By allowing natural language expressions inside SQL comments, Google is trying to speed up that translation while keeping SQL as the execution layer," he said."
Google enables natural language expressions inside SQL comments to help convert user intent into executable SQL while retaining SQL as the execution layer. Current SQL construction often requires manual handling of joins, time logic, and repetitive patterns, which slows query creation and iteration. Translating intent into accurate, efficient SQL remains time-consuming. Allowing natural language in comments aims to reduce time spent writing and rewriting queries, minimize team handoffs, and enable more automated analytics processes. The feature is intended to let teams focus more on interpreting results and building downstream analytics rather than on query setup and syntax details.
Read at InfoWorld
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