dongjoon-hyun opened a new pull request, #469:
URL: https://github.com/apache/spark-connect-swift/pull/469
### What changes were proposed in this pull request?
This PR aims to support `GEOMETRY` and `GEOGRAPHY` types (added in Apache
Spark 4.1) in
`DataType.simpleString` so that `DataFrame.dtypes` works on geospatial
columns.
Following Apache Spark's `GeometryType`/`GeographyType.typeName` convention,
the mapping uses
`geometry(<srid>)`/`geography(<srid>)` for fixed-SRID types and
`geometry(any)`/`geography(any)`
for the mixed-SRID case (`srid == -1`).
### Why are the changes needed?
`Spark_Connect_DataType`'s `geometry` and `geography` kinds fell through to
the `default:` branch
of `DataType.simpleString` and threw `SparkConnectError.InvalidType`. As a
result,
`DataFrame.dtypes` failed entirely on any DataFrame containing a geospatial
column.
```swift
let df = try await spark.sql("SELECT
st_geomfromwkb(X'0101000000000000000000F03F0000000000000040')")
try await df.dtypes // Before: throws SparkConnectError.InvalidType
// After: [("st_geomfromwkb(...)", "geometry(0)")]
```
### Does this PR introduce _any_ user-facing change?
Yes, `DataFrame.dtypes` no longer throws on geospatial columns and returns
Spark-style type
strings instead. This is a bug fix from the unreleased perspective.
### How was this patch tested?
Pass the CIs with a newly added test case, `dtypesGeospatial`, which
verifies `geometry(0)`,
`geometry(4326)`, and `geography(4326)` against Apache Spark 4.2.0 (guarded
for `4.2+` servers).
Manually verified against a local `apache/spark:4.2.0` Spark Connect server.
### Was this patch authored or co-authored using generative AI tooling?
Generated-by: Claude Fable 5
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