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databricks-dbsql

Generate Databricks SQL for advanced DBSQL scenarios including AI functions.

Updated May 20, 2026
Search Tags:#geospatial#materialized views#dbsql#databricks sql#sql scripting#ai functions#collations
One-click install
npx skills add https://github.com/ice-droid-99/BI-Dashboard-Generation-Agent-in-Databricks- --skill databricks-dbsql-ice-droid-99
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: databricks-dbsql
Source: https://github.com/ice-droid-99/BI-Dashboard-Generation-Agent-in-Databricks-/tree/main/.gemini/skills/databricks-dbsql
Command: npx skills add https://github.com/ice-droid-99/BI-Dashboard-Generation-Agent-in-Databricks- --skill databricks-dbsql-ice-droid-99

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps you correctly use advanced Databricks SQL features when building robust, production-ready analytics and BI queries, avoiding common syntax and capability pitfalls.

Core Features & Use Cases

  • Databricks SQL advanced features coverage: guidance for SQL scripting, stored procedures, recursive CTEs, transactions, materialized views, temp tables/views, pipe syntax, and federated querying via SQL functions.
  • AI-enabled SQL patterns: practical use of DBSQL AI functions (ai_query, ai_classify, ai_extract, and related helpers) including structured outputs and safe batch development with cost controls.
  • Performance- and correctness-oriented DBSQL guidance: design patterns for geospatial (H3 and ST_*) functions, collations for case/locale correctness, and best practices for modeling and query execution on Databricks SQL warehouses.

Quick Start

Use this skill to generate a Databricks SQL script that creates a scheduled materialized view with proper clustering and then validates it using a DBSQL query that includes an AI function for structured enrichment.

Frequently Asked Questions about databricks-dbsql

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I write recursive CTEs and stored procedures in Databricks SQL?▼

Databricks SQL supports recursive CTEs and stored procedures through SQL scripting. You can generate production-ready scripts that implement procedural logic, enabling complex transformations and federated reads within DBSQL.

Can I use AI functions like ai_query and ai_classify in Databricks SQL?▼

Databricks SQL provides AI functions such as ai_query and ai_classify for structured enrichment. They require a serverless SQL warehouse and should be developed in safe batches with cost controls to manage execution expenses.

What is the best way to handle geospatial operations in Databricks SQL?▼

Databricks SQL handles geospatial operations using H3 and ST_ functions. Applying these design patterns allows you to perform spatial indexing and geometry calculations correctly within production BI workloads.

Does Databricks SQL support materialized views and pipe syntax?▼

Databricks SQL supports materialized views with clustering and pipe syntax for query execution. You can schedule materialized views to optimize BI workloads and use pipe syntax to structure complex queries.

How do collations work for string filtering in Databricks SQL?▼

Collations in Databricks SQL enable case- and locale-aware string filtering. Applying collation-aware design patterns ensures string comparisons and filtering operations return correct results across different locales.

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