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Posted to commits@spark.apache.org by do...@apache.org on 2025/05/16 12:51:17 UTC
(spark-connect-swift) branch main updated: [SPARK-52182] Support `withWatermark` for `DataFrame`
This is an automated email from the ASF dual-hosted git repository.
dongjoon pushed a commit to branch main
in repository https://gitbox.apache.org/repos/asf/spark-connect-swift.git
The following commit(s) were added to refs/heads/main by this push:
new e346c9e [SPARK-52182] Support `withWatermark` for `DataFrame`
e346c9e is described below
commit e346c9ee99132592872821bdb88c7f86fcb2fb8b
Author: Dongjoon Hyun <do...@apache.org>
AuthorDate: Fri May 16 05:51:08 2025 -0700
[SPARK-52182] Support `withWatermark` for `DataFrame`
### What changes were proposed in this pull request?
This PR aims to ad `withWatermark` for `DataFrame`.
### Why are the changes needed?
For feature parity.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Pass the CIs.
### Was this patch authored or co-authored using generative AI tooling?
No.
Closes #158 from dongjoon-hyun/SPARK-52182.
Authored-by: Dongjoon Hyun <do...@apache.org>
Signed-off-by: Dongjoon Hyun <do...@apache.org>
---
Sources/SparkConnect/DataFrame.swift | 14 ++++++++++++++
Sources/SparkConnect/SparkConnectClient.swift | 17 +++++++++++++++++
Tests/SparkConnectTests/DataFrameTests.swift | 16 ++++++++++++++++
3 files changed, 47 insertions(+)
diff --git a/Sources/SparkConnect/DataFrame.swift b/Sources/SparkConnect/DataFrame.swift
index 75f555f..945651e 100644
--- a/Sources/SparkConnect/DataFrame.swift
+++ b/Sources/SparkConnect/DataFrame.swift
@@ -117,6 +117,7 @@ import Synchronization
/// - ``transpose()``
/// - ``transpose(_:)``
/// - ``hint(_:_:)``
+/// - ``withWatermark(_:_:)``
///
/// ### Join Operations
/// - ``join(_:)``
@@ -1444,6 +1445,19 @@ public actor DataFrame: Sendable {
try await checkpoint(eager, false, storageLevel)
}
+ /// Defines an event time watermark for this ``DataFrame``. A watermark tracks a point in time
+ /// before which we assume no more late data is going to arrive.
+ /// - Parameters:
+ /// - eventTime: the name of the column that contains the event time of the row.
+ /// - delayThreshold: the minimum delay to wait to data to arrive late, relative to
+ /// the latest record that has been processed in the form of an interval (e.g. "1 minute" or "5 hours").
+ /// NOTE: This should not be negative.
+ /// - Returns: A ``DataFrame`` instance.
+ public func withWatermark(_ eventTime: String, _ delayThreshold: String) -> DataFrame {
+ let plan = SparkConnectClient.getWithWatermark(self.plan.root, eventTime, delayThreshold)
+ return DataFrame(spark: self.spark, plan: plan)
+ }
+
/// Returns a ``DataFrameWriter`` that can be used to write non-streaming data.
public var write: DataFrameWriter {
get {
diff --git a/Sources/SparkConnect/SparkConnectClient.swift b/Sources/SparkConnect/SparkConnectClient.swift
index c69888f..a5306dc 100644
--- a/Sources/SparkConnect/SparkConnectClient.swift
+++ b/Sources/SparkConnect/SparkConnectClient.swift
@@ -1022,6 +1022,23 @@ public actor SparkConnectClient {
return plan
}
+ static func getWithWatermark(
+ _ child: Relation,
+ _ eventTime: String,
+ _ delayThreshold: String
+ ) -> Plan {
+ var withWatermark = Spark_Connect_WithWatermark()
+ withWatermark.input = child
+ withWatermark.eventTime = eventTime
+ withWatermark.delayThreshold = delayThreshold
+
+ var relation = Relation()
+ relation.withWatermark = withWatermark
+ var plan = Plan()
+ plan.opType = .root(relation)
+ return plan
+ }
+
func createTempView(
_ child: Relation, _ viewName: String, replace: Bool, isGlobal: Bool
) async throws {
diff --git a/Tests/SparkConnectTests/DataFrameTests.swift b/Tests/SparkConnectTests/DataFrameTests.swift
index fd15496..09aab96 100644
--- a/Tests/SparkConnectTests/DataFrameTests.swift
+++ b/Tests/SparkConnectTests/DataFrameTests.swift
@@ -744,6 +744,22 @@ struct DataFrameTests {
await spark.stop()
}
+ @Test
+ func withWatermark() async throws {
+ let spark = try await SparkSession.builder.getOrCreate()
+ let df = try await spark
+ .sql("""
+ SELECT * FROM VALUES
+ (1, now()),
+ (1, now() - INTERVAL 1 HOUR),
+ (1, now() - INTERVAL 2 HOUR)
+ T(data, eventTime)
+ """)
+ .withWatermark("eventTime", "1 minute") // This tests only API for now
+ #expect(try await df.dropDuplicatesWithinWatermark("data").count() == 1)
+ await spark.stop()
+ }
+
@Test
func describe() async throws {
let spark = try await SparkSession.builder.getOrCreate()
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