dongjoon-hyun opened a new pull request, #456:
URL: https://github.com/apache/spark-connect-swift/pull/456
### What changes were proposed in this pull request?
This PR aims to support Swift literal operands in `Column` operators so that
literals can be mixed with `Column` expressions directly without wrapping them
in `lit`.
- A new public protocol `SparkLiteral` with a `toLiteralColumn` requirement,
conformed by all nine types supported by `lit`: `Bool`, `Int8`, `Int16`,
`Int32`, `Int64`, `Int`, `Float`, `Double`, and `String`.
- Generic overloads for all thirteen binary operators (`==`, `!=`, `<`,
`<=`, `>`, `>=`, `&&`, `||`, `+`, `-`, `*`, `/`, `%`) accepting `some
SparkLiteral` on either the left-hand or right-hand side.
```swift
df.filter(col("age") > 21 && col("name") == "Alice")
df.select((col("id") * 2).alias("doubled"))
df.filter(21 < col("age"))
```
Each conformance reuses the existing `lit` functions, so the
literal-to-proto mapping is defined in one place. Existing Swift operations
such as `Int == Int` are not affected because every overload requires a
`Column` on one side.
### Why are the changes needed?
This allows users to write expressions in the idiomatic PySpark/Scala style
(`col("age") > 21`) instead of `col("age") > lit(21)`, without an overload
explosion per literal type.
### Does this PR introduce _any_ user-facing change?
No. This is a new feature addition to the unreleased `Column` API.
### How was this patch tested?
Pass the CIs with the newly added unit tests.
### Was this patch authored or co-authored using generative AI tooling?
Generated-by: Claude Fable 5
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