dongjoon-hyun opened a new pull request, #455:
URL: https://github.com/apache/spark-connect-swift/pull/455
### What changes were proposed in this pull request?
This PR aims to support comparison, logical, and arithmetic operators in
`Column`.
- Comparison: `==`, `!=`, `<`, `<=`, `>`, `>=`
- Logical: `&&`, `||`, prefix `!`
- Arithmetic: `+`, `-`, `*`, `/`, `%`, prefix `-` (negation)
The operators build `Expression.UnresolvedFunction` with the same function
names as the Scala client (`Column.scala`): `==` → `"="`, `!=` → `"!"` of
`"="`, `&&` → `"and"`, `||` → `"or"`, prefix `-` → `"negative"`, and the same
symbols for the rest.
In addition, `DataFrame.filter(_: Column)` and `DataFrame.where(_: Column)`
overloads are added to make the operators usable.
```swift
let adults = df.filter(col("age") > lit(21) && col("name") == lit("Alice"))
let doubled = df.select((col("id") * lit(2)).alias("doubled"))
```
Note that unlike Scala, Swift allows overloading `==` with a `Column` return
type without conflicts because `Column` does not conform to `Equatable`, so the
Scala-style `===`/`=!=` operators are not needed. Misuse such as `if col("a")
== col("b")` is rejected at compile time (`cannot convert value of type
'Column' to expected condition type 'Bool'`).
### Why are the changes needed?
To allow users to write filter and projection expressions in the idiomatic
PySpark/Scala style instead of SQL strings.
### 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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