feat: add UDTF documentation and reorganize Geneva docs (#187)

Add two new doc pages for the UDTF features introduced in Geneva 0.11.0:
- Scalar UDTFs (1:N row expansion) for chunking, splitting, tiling
- Batch UDTFs (N:M transformations) for deduplication, clustering, aggregation

Also updates the UDF index page with a UDFs vs UDTFs overview section
and adds both pages to the docs.json navigation.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* feat: add UDFs and UDTFs overview page with visual comparisons

- Add geneva/overview/udfs-and-udtfs.mdx with table-based illustrations
  of 1:1, 1:N, and N:M transformations
- Move comparison table out of scalar-udtfs into the overview page
- Remove UDFs vs UDTFs blurb from UDF index (now in overview)
- Use @udtf instead of @geneva.udtf throughout
- Update scalar UDTF inherited columns example to exclude duration
- Reorder sections: choosing the right type and at-a-glance first

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>

Author: jmhsieh

docs/docs.json

@@ -159,49 +159,47 @@
               "geneva/index",
               "geneva/overview/index",
               {
-                "group": "User Defined Functions (UDFs)",
+                "group": "Transforms",
                 "pages": [
                   "geneva/udfs/index",
-                  {
-                    "group": "Built-in Providers",
-                    "pages": [
-                      "geneva/udfs/providers/index",
-                      "geneva/udfs/providers/openai",
-                      "geneva/udfs/providers/gemini",
-                      "geneva/udfs/providers/sentence-transformers"
-                    ]
-                  },
-                  "geneva/udfs/blobs",
+                  "geneva/udfs/udfs",
+                  "geneva/udfs/scalar-udtfs",
+                  "geneva/udfs/batch-udtfs",
                   "geneva/udfs/error_handling",
-                  "geneva/udfs/advanced-configuration"
+                  "geneva/udfs/blobs"
                 ]
               },
               {
-                "group": "Jobs",
+                "group": "Built-in Transforms",
                 "pages": [
-                  "geneva/jobs/lifecycle",
-                  "geneva/jobs/backfilling",
-                  "geneva/jobs/conflicts",
-                  "geneva/jobs/materialized-views",
-                  "geneva/jobs/performance",
-                  "geneva/jobs/job_metrics",
-                  "geneva/jobs/troubleshooting"
+                  "geneva/udfs/providers/index",
+                  "geneva/udfs/providers/openai",
+                  "geneva/udfs/providers/gemini",
+                  "geneva/udfs/providers/sentence-transformers"
                 ]
               },
               {
-                "group": "Operations",
+                "group": "Running Jobs",
                 "pages": [
                   "geneva/jobs/contexts",
-                  "geneva/deployment/dependency-verification",
-                  "geneva/jobs/startup",
-                  "geneva/jobs/console"
+                  "geneva/jobs/backfilling",
+                  "geneva/jobs/materialized-views",
+                  "geneva/jobs/lifecycle",
+                  "geneva/jobs/conflicts",
+                  "geneva/jobs/performance",
+                  "geneva/jobs/job_metrics",
+                  "geneva/jobs/console",
+                  "geneva/jobs/troubleshooting"
                 ]
               },
               {
                 "group": "Deployment",
                 "pages": [
                   "geneva/deployment/index",
                   "geneva/deployment/helm",
+                  "geneva/jobs/startup",
+                  "geneva/deployment/dependency-verification",
+                  "geneva/udfs/advanced-configuration",
                   "geneva/deployment/troubleshooting"
                 ]
               },

docs/geneva/index.mdx

@@ -23,15 +23,15 @@ Feature Engineering and the `geneva` Python package are currently only available
 in scaling up your feature engineering workloads for your AI and multimodal use cases.
 </Card>
 
-The `geneva` package uses Python [User Defined Functions (UDFs)](/geneva/udfs/) to define features
+The `geneva` package uses Python [User Defined Functions (UDFs)](/geneva/udfs/udfs) to define features
 as columns in a Lance dataset. Adding a feature is straightforward:
 
 <Steps>
   <Step>
   Prototype your Python function in your favorite environment.
   </Step>
   <Step>
-  Wrap the function with a small UDF decorator (see [UDFs](/geneva/udfs/)).
+  Wrap the function with a small UDF decorator (see [UDFs](/geneva/udfs/udfs)).
   </Step>
   <Step>
   Register the UDF as a virtual column using `Table.add_columns()`.
@@ -50,6 +50,6 @@ You can build your Python feature generator function in an IDE or a notebook usi
 Visit the following pages to learn more about featuring engineering in LanceDB Enterprise:
 
 - **Overview**: [What is Feature Engineering?](/geneva/overview/)
-- **UDFs**: [Using UDFs](/geneva/udfs/) · [Blob helpers](/geneva/udfs/blobs/) · [Error handling](/geneva/udfs/error_handling) · [Advanced configuration](/geneva/udfs/advanced-configuration) 
+- **UDFs**: [Using UDFs](/geneva/udfs/udfs) · [Blob helpers](/geneva/udfs/blobs/) · [Error handling](/geneva/udfs/error_handling) · [Advanced configuration](/geneva/udfs/advanced-configuration) 
 - **Jobs**: [Backfilling](/geneva/jobs/backfilling/) · [Startup optimizations](/geneva/jobs/startup/) · [Materialized views](/geneva/jobs/materialized-views/) · [Execution contexts](/geneva/jobs/contexts/) · [Geneva console](/geneva/jobs/console) · [Performance](/geneva/jobs/performance/)
 - **Deployment**: [Deployment overview](/geneva/deployment/) · [Helm deployment](/geneva/deployment/helm/) · [Troubleshooting](/geneva/deployment/troubleshooting/)