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TRRaveendra
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mssql-to-databricks-migration

Convert T-SQL stored procedures and scripts into Databricks PySpark and Spark SQL notebooks.

1|2|Updated Aug 10, 2026
Search Tags:#migration#pyspark#databricks#mssql#spark sql#delta lake#t-sql
One-click install
npx skills add https://github.com/TRRaveendra/AI-Agents-Databricks --skill mssql-to-databricks-migration-trraveendra
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: mssql-to-databricks-migration
Source: https://github.com/TRRaveendra/AI-Agents-Databricks/tree/main/mssql-to-pyspark-ai-agent/skills_mssql_to_sparksql
Command: npx skills add https://github.com/TRRaveendra/AI-Agents-Databricks --skill mssql-to-databricks-migration-trraveendra

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? Migrating Microsoft SQL Server workloads to Databricks requires translating T-SQL constructs like stored procedures, cursors, temp tables, and dynamic SQL into Spark equivalents, which is error-prone and time-consuming when done manually. ## Core Features & Use Cases - T-SQL to Spark Translation: Maps DDL, DML, DQL, control flow, functions, and data types from SQL Server to Spark SQL and PySpark using nine detailed reference guides. - Security-First Conversion: Enforces SQL injection prevention rules, safe parameter handling with dbutils.widgets, and Spark-native date functions instead of Python datetime objects. - Pattern-Based Migration: Provides idiomatic rewrites for cursors, SCD Type 2 dimensions, MERGE upserts, SSIS components, and medallion architecture workflows. - Use Case: Given a legacy stored procedure using cursors and temp tables, produce a Databricks notebook with widget parameters, temp views, set-based MERGE operations, and audit logging. ## Quick Start Migrate this T-SQL stored procedure to a Databricks notebook using Spark SQL for data operations and PySpark for control flow.

Frequently Asked Questions about mssql-to-databricks-migration

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

FAQPage Schema
How do I migrate SQL Server stored procedures to Databricks?▼

Analyze the procedure's parameters, variables, temp tables, and control flow, then map each construct using the reference guides. Use Spark SQL for set-based operations like MERGE and PySpark for orchestration, widgets, and error handling.

How to convert T-SQL cursors to PySpark?▼

Rewrite cursors as set-based operations such as a single UPDATE or MERGE statement, since row-by-row processing is an anti-pattern in Spark. Use functions like GREATEST to replace conditional per-row updates.

Does Spark SQL support T-SQL MERGE statements?▼

Yes, Delta Lake supports MERGE with WHEN MATCHED, WHEN NOT MATCHED, and WHEN NOT MATCHED BY SOURCE clauses, making it a near-direct port from T-SQL. T-SQL UPDATE...FROM joins should also be rewritten as MERGE statements.

What is the Spark SQL equivalent of T-SQL temp tables?▼

Local temp tables (#Temp) map to createOrReplaceTempView for session-scoped views, while global temp tables map to Delta tables in a staging schema. Table variables become temp views or Python collections.

Why is f-string SQL interpolation dangerous in Databricks notebooks?▼

Interpolating widget values directly into spark.sql strings creates SQL injection vulnerabilities. Use the DataFrame API with col() comparisons, typed DataFrames with temp views, or whitelist-validated identifiers instead.

What T-SQL features cannot be migrated to Databricks directly?▼

Linked servers, CLR procedures, SQL Mail, Service Broker, full-text search, and SQL Agent jobs have no direct equivalent. They require redesign using JDBC connections, PySpark rewrites, workflow notifications, or streaming patterns.

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