dongjoon-hyun opened a new pull request, #441:
URL: https://github.com/apache/spark-connect-swift/pull/441
### What changes were proposed in this pull request?
This PR adds a `Column` expression type and a minimal set of `functions` to
`SparkConnect`
module, like Apache Spark's `org.apache.spark.sql.Column` and
`org.apache.spark.sql.functions`.
- `Column`: a `Sendable` struct wrapping `Spark_Connect_Expression`,
providing
`alias`, `asc`, `desc`, and `cast`.
- Functions: `col`, `column`, `lit`, `asc`, `desc`, `count`, `sum`, `avg`,
`mean`, `min`, `max`.
- New overloads accepting `Column` expressions: `DataFrame.select` and
`GroupedData.agg`.
```swift
let df2 = df.select(col("name"), col("age").cast("long").alias("age_long"))
let df3 = await df.groupBy("department")
.agg(count(col("*")).alias("employee_count"), avg(col("salary")))
```
In addition, the unused `Column` struct in `Catalog.swift` is renamed to
`CatalogColumn`
to free the name, and the `groupBy` documentation example is fixed.
### Why are the changes needed?
To provide a type-safe column expression DSL consistent with the other Spark
Connect
clients, instead of relying only on SQL string expressions.
### Does this PR introduce _any_ user-facing change?
Yes, the unused `Column` struct is renamed to `CatalogColumn`. The existing
APIs
behave identically, and the rest are API additions.
### How was this patch tested?
Pass the CIs including the new `FunctionsTests` suite.
### Was this patch authored or co-authored using generative AI tooling?
Generated-by: Claude Fable 5
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