dongjoon-hyun opened a new pull request, #449:
URL: https://github.com/apache/spark-connect-swift/pull/449
### What changes were proposed in this pull request?
This PR aims to support `DataFrame.observe` API which defines named metrics
to observe on a `DataFrame` by building a `CollectMetrics` relation.
```swift
let observedDf = df.observe("my_metrics", sum(col("id")), max(col("id")))
```
- `DataFrame.observe(_ name: String, _ expr: Column, _ exprs: Column...)`
returns an *observed* `DataFrame` that returns the same result as the input. At
least one metric column is required at compile time, like Scala's
`Dataset.observe(name:expr:exprs:)`.
- `SparkConnectClient.getCollectMetrics` assembles the `CollectMetrics`
relation following the existing static `get*` helper pattern.
Retrieving the observed metric values from
`ExecutePlanResponse.observed_metrics` will be handled in a follow-up.
### Why are the changes needed?
To provide a way to attach observable metrics (literals or aggregate
expressions) to a `DataFrame` like Apache Spark's Scala/PySpark clients. This
leverages the recently added `Column` type and aggregate functions
([SPARK-58336]).
### Does this PR introduce _any_ user-facing change?
No. This is a new API addition.
### How was this patch tested?
Pass the CIs with a newly added test case, `DataFrameTests.observe`, which
verifies that actions (`columns`, `count`, `collect`) on an observed
`DataFrame` return the same result as the input against a live Spark Connect
server (`apache/spark:4.2.0`).
### Was this patch authored or co-authored using generative AI tooling?
Generated-by: Claude Fable 5
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