srielau opened a new pull request, #58224:
URL: https://github.com/apache/spark/pull/58224
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### What changes were proposed in this pull request?
Document `CHAR` / `VARCHAR` / `STRING` as a character string type family for
[SPARK-58942](https://issues.apache.org/jira/browse/SPARK-58942), matching
the
behavior behind `spark.sql.charVarchar.standardSemantics.enabled`.
- Add [Character String Types](docs/sql-ref-character-string-types.md): type
definitions, enablement, CAST vs assignment, least common type
(`CHAR(n) -> VARCHAR(n) -> STRING`, analogous to integral types),
expression
result typing, comparisons and RTRIM collations, schema surfaces, and
format/client metadata.
- Rewrite the Data Types page so CHAR and VARCHAR are not described as
special
variants of STRING, and are not limited to table schemas.
- Extend ANSI type precedence / least common type, link CAST and store
assignment to the new page, and add a Spark 4.4 migration note.
- Point SHOW COLLATIONS at the family page and update the generated
configuration description.
Parent: [SPARK-58794](https://issues.apache.org/jira/browse/SPARK-58794).
### Why are the changes needed?
Existing docs still describe CHAR/VARCHAR as annotated STRING used only in
table schemas. That is the Spark 3.1 story and no longer matches the
first-class
type family implemented under `standardSemantics`. Users need Spark-centric
SQL reference for length, padding, CAST vs assignment, LCT, and
STRING-returning
transforms.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Documentation only. Local Markdown links and SQL menu YAML were checked. The
Jekyll site was built with `SKIP_API=1 SKIP_ERRORDOC=1 bundle exec jekyll
build`.
### Was this patch authored or co-authored using generative AI tooling?
Generated-by: Cursor Grok 4.6
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