mirror of
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Jack Ye
8f37234a86
Feature engineering is now the overview plus one page per operation: add a computed column, refresh a column, refresh a materialized view. Computed columns covered declaring and filling on one page, which are separate decisions with separate failure modes. Functions move to Management, where the other catalog objects are, and absorb the environment-mismatch guidance from the Enterprise page -- a symptom table worth having beside the parameters that cause it. The Enterprise feature-engineering page is merged into the overview. Two of its claims were stale: create_materialized_view is implemented for db:// connections in remote/db.py, so views are not local-only, and the tier is Enterprise rather than 'Cloud and Enterprise'. The REST reference leaves the sidebar. Mintlify only generates per-endpoint pages from a navigation group -- hidden, dropdowns, global anchors and a top-level openapi key were all tried -- so removing the group removes those pages. The overview survives as an unlisted page, linked from SDKs & SQL, and the spec still ships for anything that wants to read it directly.
23 lines
1.7 KiB
Plaintext
23 lines
1.7 KiB
Plaintext
---
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title: "Feature Engineering"
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sidebarTitle: "Feature Engineering"
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description: "Learn how to build features for your data in LanceDB."
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layout: wide
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---
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| Example | Description |
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|--------|:------------|
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| **Feature Engineering 101** <br /> <a href="https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/tutorials/feature-engineering/feature-engineering-101.ipynb" rel="noreferer, ,noopener" target="_blank"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab" /></a> [View on GitHub](https://github.com/lancedb/vectordb-recipes/tree/main/tutorials/feature-engineering/feature-engineering-101.ipynb) | This example demonstrates how to use LanceDB's feature engineering platform to add new derived features.
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| **Materialized Views** <br /> <a href="https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/tutorials/feature-engineering/materialized-views.ipynb" rel="noreferer, ,noopener" target="_blank"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab" /></a> [View on GitHub](https://github.com/lancedb/vectordb-recipes/tree/main/tutorials/feature-engineering/materialized-views.ipynb) | This example shows how to create materialized views: query results persisted as physical tables.
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## Read the docs {#read-the-docs}
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The relevant section of the documentation are listed below.
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| Feature | Description |
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|:--------|:------------|
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| [Feature engineering](/feature-engineering) | The three ways to derive columns and tables. |
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| [Materialized views](/feature-engineering/materialized-views) | Derive a table from a query and refresh it incrementally. |
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| [Computed columns](/feature-engineering/add-computed-column) | Declare a column from an expression and fill it. |
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