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Add SQL-to-Kotlin DataFrame transition guide for backend developers #1377
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Includes a comprehensive guide to help SQL and ORM users adapt to Kotlin DataFrame. Covers key concepts, equivalents for SQL/ORM operations, and practical examples. Updated TOC to include the new guide.
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Pull Request Overview
This PR adds a comprehensive guide for backend developers with SQL experience to transition to Kotlin DataFrame. The guide provides SQL-to-DataFrame mappings and explains key conceptual differences between SQL databases, ORMs, and Kotlin DataFrame.
- Introduces Kotlin DataFrame concepts through familiar SQL terminology
- Provides side-by-side comparisons of SQL commands and DataFrame operations
- Explains the differences between DataFrame, SQL databases, and ORMs
Reviewed Changes
Copilot reviewed 2 out of 2 changed files in this pull request and generated 1 comment.
File | Description |
---|---|
Guide-for-backend-SQL-developers.md | New comprehensive guide document with SQL-to-DataFrame mappings and conceptual explanations |
d.tree | Adds the new guide to the documentation navigation structure |
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Please add an information about supported SQL DBs (and how to integrate unsupported !) with references to https://kotlin.github.io/dataframe/sql.html.
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Can be interesting that columns store any values, not just primitives or predefined set of types. List, File, Map, user objects - DataFrame offers fully generic storage. |
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Added details on setting up Kotlin DataFrame in Gradle projects, clarified DDL/DML equivalents, and enhanced examples. Updated TOC with a new Hibernate Interop reference and improved formatting consistency across sections.
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