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new 605aa0c299c
[SPARK-45687][CORE][SQL][ML][MLLIB][KUBERNETES][EXAMPLES][CONNECT][STRUCTURED
STREAMING] Fix `Passing an explicit array value to a Scala varargs method is
deprecated`
605aa0c299c is described below
commit 605aa0c299c1d88f8a31ba888ac8e6b6203be6c5
Author: Tengfei Huang <[email protected]>
AuthorDate: Fri Nov 10 08:10:20 2023 -0600
[SPARK-45687][CORE][SQL][ML][MLLIB][KUBERNETES][EXAMPLES][CONNECT][STRUCTURED
STREAMING] Fix `Passing an explicit array value to a Scala varargs method is
deprecated`
### What changes were proposed in this pull request?
Fix the deprecated behavior below:
`Passing an explicit array value to a Scala varargs method is deprecated
(since 2.13.0) and will result in a defensive copy; Use the more efficient
non-copying ArraySeq.unsafeWrapArray or an explicit toIndexedSeq call`
For all the use cases, we don't need to make a copy of the array.
Explicitly use `ArraySeq.unsafeWrapArray` to do the conversion.
### Why are the changes needed?
Eliminate compile warnings and no longer use deprecated scala APIs.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
Pass GA.
Fixed all the warning with build: `mvn clean package -DskipTests
-Pspark-ganglia-lgpl -Pkinesis-asl -Pdocker-integration-tests -Pyarn
-Pkubernetes -Pkubernetes-integration-tests -Phive-thriftserver -Phadoop-cloud`
### Was this patch authored or co-authored using generative AI tooling?
No.
Closes #43642 from ivoson/SPARK-45687.
Authored-by: Tengfei Huang <[email protected]>
Signed-off-by: Sean Owen <[email protected]>
---
.../scala/org/apache/spark/sql/KeyValueGroupedDataset.scala | 9 ++++++---
.../test/scala/org/apache/spark/sql/ColumnTestSuite.scala | 3 ++-
.../apache/spark/sql/UserDefinedFunctionE2ETestSuite.scala | 5 ++++-
.../spark/sql/connect/planner/SparkConnectPlanner.scala | 3 ++-
.../main/scala/org/apache/spark/api/python/PythonRDD.scala | 3 ++-
core/src/main/scala/org/apache/spark/executor/Executor.scala | 3 ++-
core/src/main/scala/org/apache/spark/rdd/RDD.scala | 3 ++-
.../scala/org/apache/spark/examples/graphx/Analytics.scala | 4 ++--
.../scala/org/apache/spark/ml/classification/OneVsRest.scala | 3 ++-
.../scala/org/apache/spark/ml/feature/FeatureHasher.scala | 4 +++-
.../src/main/scala/org/apache/spark/ml/feature/Imputer.scala | 8 +++++---
.../main/scala/org/apache/spark/ml/feature/Interaction.scala | 4 +++-
.../main/scala/org/apache/spark/ml/feature/RFormula.scala | 6 ++++--
.../scala/org/apache/spark/ml/feature/VectorAssembler.scala | 5 +++--
mllib/src/main/scala/org/apache/spark/ml/fpm/FPGrowth.scala | 3 ++-
.../src/main/scala/org/apache/spark/ml/fpm/PrefixSpan.scala | 3 ++-
.../src/main/scala/org/apache/spark/ml/r/KSTestWrapper.scala | 3 ++-
.../apache/spark/ml/regression/DecisionTreeRegressor.scala | 3 ++-
.../src/main/scala/org/apache/spark/ml/tree/treeModels.scala | 3 ++-
.../src/main/scala/org/apache/spark/mllib/util/MLUtils.scala | 12 ++++++++----
.../scala/org/apache/spark/ml/feature/ImputerSuite.scala | 12 ++++++++----
.../apache/spark/ml/source/image/ImageFileFormatSuite.scala | 3 ++-
.../apache/spark/ml/stat/KolmogorovSmirnovTestSuite.scala | 3 ++-
mllib/src/test/scala/org/apache/spark/ml/util/MLTest.scala | 6 ++++--
.../deploy/k8s/features/DriverCommandFeatureStepSuite.scala | 2 +-
.../apache/spark/sql/catalyst/expressions/generators.scala | 8 ++++++--
.../sql/catalyst/expressions/UnsafeRowConverterSuite.scala | 4 +++-
.../scala/org/apache/spark/sql/DataFrameStatFunctions.scala | 3 ++-
.../scala/org/apache/spark/sql/KeyValueGroupedDataset.scala | 8 ++++++--
.../spark/sql/execution/datasources/jdbc/JDBCRDD.scala | 2 +-
.../org/apache/spark/sql/execution/stat/StatFunctions.scala | 3 ++-
.../apache/spark/sql/execution/streaming/OffsetSeqLog.scala | 3 ++-
.../streaming/continuous/ContinuousRateStreamSource.scala | 3 ++-
.../src/test/scala/org/apache/spark/sql/DataFrameSuite.scala | 3 ++-
.../src/test/scala/org/apache/spark/sql/DatasetSuite.scala | 6 ++++--
.../src/test/scala/org/apache/spark/sql/GenTPCDSData.scala | 3 ++-
.../test/scala/org/apache/spark/sql/ParametersSuite.scala | 9 +++++----
.../spark/sql/connector/SimpleWritableDataSource.scala | 4 +++-
.../sql/execution/datasources/FileMetadataStructSuite.scala | 3 ++-
.../spark/sql/execution/datasources/csv/CSVBenchmark.scala | 7 ++++---
.../scala/org/apache/spark/sql/streaming/StreamSuite.scala | 2 +-
.../org/apache/spark/sql/streaming/StreamingQuerySuite.scala | 3 ++-
.../org/apache/spark/sql/hive/thriftserver/CliSuite.scala | 3 ++-
.../spark/sql/hive/execution/AggregationQuerySuite.scala | 4 +++-
.../spark/sql/hive/execution/ObjectHashAggregateSuite.scala | 8 +++++---
45 files changed, 136 insertions(+), 69 deletions(-)
diff --git
a/connector/connect/client/jvm/src/main/scala/org/apache/spark/sql/KeyValueGroupedDataset.scala
b/connector/connect/client/jvm/src/main/scala/org/apache/spark/sql/KeyValueGroupedDataset.scala
index dac89bf3eb5..2e6117abbf3 100644
---
a/connector/connect/client/jvm/src/main/scala/org/apache/spark/sql/KeyValueGroupedDataset.scala
+++
b/connector/connect/client/jvm/src/main/scala/org/apache/spark/sql/KeyValueGroupedDataset.scala
@@ -194,7 +194,9 @@ class KeyValueGroupedDataset[K, V] private[sql] () extends
Serializable {
SortExprs: Array[Column],
f: FlatMapGroupsFunction[K, V, U],
encoder: Encoder[U]): Dataset[U] = {
- flatMapSortedGroups(SortExprs:
_*)(UdfUtils.flatMapGroupsFuncToScalaFunc(f))(encoder)
+ import org.apache.spark.util.ArrayImplicits._
+ flatMapSortedGroups(SortExprs.toImmutableArraySeq: _*)(
+ UdfUtils.flatMapGroupsFuncToScalaFunc(f))(encoder)
}
/**
@@ -458,8 +460,9 @@ class KeyValueGroupedDataset[K, V] private[sql] () extends
Serializable {
otherSortExprs: Array[Column],
f: CoGroupFunction[K, V, U, R],
encoder: Encoder[R]): Dataset[R] = {
- cogroupSorted(other)(thisSortExprs: _*)(otherSortExprs: _*)(
- UdfUtils.coGroupFunctionToScalaFunc(f))(encoder)
+ import org.apache.spark.util.ArrayImplicits._
+ cogroupSorted(other)(thisSortExprs.toImmutableArraySeq: _*)(
+ otherSortExprs.toImmutableArraySeq:
_*)(UdfUtils.coGroupFunctionToScalaFunc(f))(encoder)
}
protected[sql] def flatMapGroupsWithStateHelper[S: Encoder, U: Encoder](
diff --git
a/connector/connect/client/jvm/src/test/scala/org/apache/spark/sql/ColumnTestSuite.scala
b/connector/connect/client/jvm/src/test/scala/org/apache/spark/sql/ColumnTestSuite.scala
index c1e4399ccb0..0fb6894e457 100644
---
a/connector/connect/client/jvm/src/test/scala/org/apache/spark/sql/ColumnTestSuite.scala
+++
b/connector/connect/client/jvm/src/test/scala/org/apache/spark/sql/ColumnTestSuite.scala
@@ -207,5 +207,6 @@ class ColumnTestSuite extends ConnectFunSuite {
private val structType1 = new StructType().add("a", "int").add("b", "string")
private val structType2 = structType1.add("c", "binary")
testColName(structType1, _.struct(structType1))
- testColName(structType2, _.struct(structType2.fields: _*))
+ import org.apache.spark.util.ArrayImplicits._
+ testColName(structType2, _.struct(structType2.fields.toImmutableArraySeq:
_*))
}
diff --git
a/connector/connect/client/jvm/src/test/scala/org/apache/spark/sql/UserDefinedFunctionE2ETestSuite.scala
b/connector/connect/client/jvm/src/test/scala/org/apache/spark/sql/UserDefinedFunctionE2ETestSuite.scala
index baf65e7bb33..f7ffe7aa127 100644
---
a/connector/connect/client/jvm/src/test/scala/org/apache/spark/sql/UserDefinedFunctionE2ETestSuite.scala
+++
b/connector/connect/client/jvm/src/test/scala/org/apache/spark/sql/UserDefinedFunctionE2ETestSuite.scala
@@ -286,7 +286,10 @@ class UserDefinedFunctionE2ETestSuite extends QueryTest {
import session.implicits._
val df = Seq((1, 2, 3)).toDF("a", "b", "c")
val f = udf((row: Row) => row.schema.fieldNames)
- checkDataset(df.select(f(struct(df.columns map col: _*))), Row(Seq("a",
"b", "c")))
+ import org.apache.spark.util.ArrayImplicits._
+ checkDataset(
+ df.select(f(struct((df.columns map col).toImmutableArraySeq: _*))),
+ Row(Seq("a", "b", "c")))
}
test("Filter with row input encoder") {
diff --git
a/connector/connect/server/src/main/scala/org/apache/spark/sql/connect/planner/SparkConnectPlanner.scala
b/connector/connect/server/src/main/scala/org/apache/spark/sql/connect/planner/SparkConnectPlanner.scala
index 8b852babb54..4925bc0a5dc 100644
---
a/connector/connect/server/src/main/scala/org/apache/spark/sql/connect/planner/SparkConnectPlanner.scala
+++
b/connector/connect/server/src/main/scala/org/apache/spark/sql/connect/planner/SparkConnectPlanner.scala
@@ -1178,11 +1178,12 @@ class SparkConnectPlanner(
val normalized = normalize(schema).asInstanceOf[StructType]
+ import org.apache.spark.util.ArrayImplicits._
val project = Dataset
.ofRows(
session,
logicalPlan =
logical.LocalRelation(normalize(structType).asInstanceOf[StructType]))
- .toDF(normalized.names: _*)
+ .toDF(normalized.names.toImmutableArraySeq: _*)
.to(normalized)
.logicalPlan
.asInstanceOf[Project]
diff --git a/core/src/main/scala/org/apache/spark/api/python/PythonRDD.scala
b/core/src/main/scala/org/apache/spark/api/python/PythonRDD.scala
index 3eea0ebcdb2..e98259562c9 100644
--- a/core/src/main/scala/org/apache/spark/api/python/PythonRDD.scala
+++ b/core/src/main/scala/org/apache/spark/api/python/PythonRDD.scala
@@ -43,6 +43,7 @@ import org.apache.spark.rdd.RDD
import org.apache.spark.security.{SocketAuthHelper, SocketAuthServer,
SocketFuncServer}
import org.apache.spark.storage.{BroadcastBlockId, StorageLevel}
import org.apache.spark.util._
+import org.apache.spark.util.ArrayImplicits._
private[spark] class PythonRDD(
@@ -179,7 +180,7 @@ private[spark] object PythonRDD extends Logging {
type UnrolledPartition = Array[ByteArray]
val allPartitions: Array[UnrolledPartition] =
sc.runJob(rdd, (x: Iterator[ByteArray]) => x.toArray,
partitions.asScala.toSeq)
- val flattenedPartition: UnrolledPartition = Array.concat(allPartitions: _*)
+ val flattenedPartition: UnrolledPartition =
Array.concat(allPartitions.toImmutableArraySeq: _*)
serveIterator(flattenedPartition.iterator,
s"serve RDD ${rdd.id} with partitions
${partitions.asScala.mkString(",")}")
}
diff --git a/core/src/main/scala/org/apache/spark/executor/Executor.scala
b/core/src/main/scala/org/apache/spark/executor/Executor.scala
index b12b5e21312..e340667173b 100644
--- a/core/src/main/scala/org/apache/spark/executor/Executor.scala
+++ b/core/src/main/scala/org/apache/spark/executor/Executor.scala
@@ -324,7 +324,8 @@ private[spark] class Executor(
private val Seq(initialUserJars, initialUserFiles, initialUserArchives) =
Seq("jar", "file", "archive").map { key =>
conf.getOption(s"spark.app.initial.$key.urls").map { urls =>
- immutable.Map(urls.split(",").map(url => (url, appStartTime)): _*)
+ import org.apache.spark.util.ArrayImplicits._
+ immutable.Map(urls.split(",").map(url => (url,
appStartTime)).toImmutableArraySeq: _*)
}.getOrElse(immutable.Map.empty)
}
updateDependencies(initialUserFiles, initialUserJars, initialUserArchives,
defaultSessionState)
diff --git a/core/src/main/scala/org/apache/spark/rdd/RDD.scala
b/core/src/main/scala/org/apache/spark/rdd/RDD.scala
index 5dc666c62d1..610b48ea2ba 100644
--- a/core/src/main/scala/org/apache/spark/rdd/RDD.scala
+++ b/core/src/main/scala/org/apache/spark/rdd/RDD.scala
@@ -1044,7 +1044,8 @@ abstract class RDD[T: ClassTag](
*/
def collect(): Array[T] = withScope {
val results = sc.runJob(this, (iter: Iterator[T]) => iter.toArray)
- Array.concat(results: _*)
+ import org.apache.spark.util.ArrayImplicits._
+ Array.concat(results.toImmutableArraySeq: _*)
}
/**
diff --git
a/examples/src/main/scala/org/apache/spark/examples/graphx/Analytics.scala
b/examples/src/main/scala/org/apache/spark/examples/graphx/Analytics.scala
index a8f9b32b0f3..5529da74970 100644
--- a/examples/src/main/scala/org/apache/spark/examples/graphx/Analytics.scala
+++ b/examples/src/main/scala/org/apache/spark/examples/graphx/Analytics.scala
@@ -18,7 +18,7 @@
// scalastyle:off println
package org.apache.spark.examples.graphx
-import scala.collection.mutable
+import scala.collection.{immutable, mutable}
import org.apache.spark._
import org.apache.spark.graphx._
@@ -51,7 +51,7 @@ object Analytics {
case _ => throw new IllegalArgumentException(s"Invalid argument: $arg")
}
}
- val options = mutable.Map(optionsList: _*)
+ val options = mutable.Map(immutable.ArraySeq.unsafeWrapArray(optionsList):
_*)
val conf = new SparkConf()
GraphXUtils.registerKryoClasses(conf)
diff --git
a/mllib/src/main/scala/org/apache/spark/ml/classification/OneVsRest.scala
b/mllib/src/main/scala/org/apache/spark/ml/classification/OneVsRest.scala
index 52106f4010f..b70f3ddd4c1 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/classification/OneVsRest.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/classification/OneVsRest.scala
@@ -213,9 +213,10 @@ final class OneVsRestModel private[ml] (
tmpModel.asInstanceOf[ProbabilisticClassificationModel[_,
_]].setProbabilityCol("")
}
+ import org.apache.spark.util.ArrayImplicits._
tmpModel.transform(df)
.withColumn(accColName, updateUDF(col(accColName),
col(tmpRawPredName)))
- .select(columns: _*)
+ .select(columns.toImmutableArraySeq: _*)
}
if (handlePersistence) {
diff --git
a/mllib/src/main/scala/org/apache/spark/ml/feature/FeatureHasher.scala
b/mllib/src/main/scala/org/apache/spark/ml/feature/FeatureHasher.scala
index f1268bdf6bd..866bf9e5bf3 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/FeatureHasher.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/FeatureHasher.scala
@@ -187,7 +187,9 @@ class FeatureHasher(@Since("2.3.0") override val uid:
String) extends Transforme
}
val metadata = outputSchema($(outputCol)).metadata
- dataset.withColumn($(outputCol),
hashFeatures(struct($(inputCols).map(col): _*)), metadata)
+ import org.apache.spark.util.ArrayImplicits._
+ dataset.withColumn($(outputCol),
+ hashFeatures(struct($(inputCols).map(col).toImmutableArraySeq: _*)),
metadata)
}
@Since("2.3.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/Imputer.scala
b/mllib/src/main/scala/org/apache/spark/ml/feature/Imputer.scala
index 5998887923f..4d38c127d41 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/Imputer.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/Imputer.scala
@@ -163,24 +163,26 @@ class Imputer @Since("2.2.0") (@Since("2.2.0") override
val uid: String)
}
val numCols = cols.length
+ import org.apache.spark.util.ArrayImplicits._
val results = $(strategy) match {
case Imputer.mean =>
// Function avg will ignore null automatically.
// For a column only containing null, avg will return null.
- val row = dataset.select(cols.map(avg): _*).head()
+ val row = dataset.select(cols.map(avg).toImmutableArraySeq: _*).head()
Array.tabulate(numCols)(i => if (row.isNullAt(i)) Double.NaN else
row.getDouble(i))
case Imputer.median =>
// Function approxQuantile will ignore null automatically.
// For a column only containing null, approxQuantile will return an
empty array.
- dataset.select(cols: _*).stat.approxQuantile(inputColumns, Array(0.5),
$(relativeError))
+ dataset.select(cols.toImmutableArraySeq: _*)
+ .stat.approxQuantile(inputColumns, Array(0.5), $(relativeError))
.map(_.headOption.getOrElse(Double.NaN))
case Imputer.mode =>
import spark.implicits._
// If there is more than one mode, choose the smallest one to keep in
line
// with sklearn.impute.SimpleImputer (using scipy.stats.mode).
- val modes = dataset.select(cols: _*).flatMap { row =>
+ val modes = dataset.select(cols.toImmutableArraySeq: _*).flatMap { row
=>
// Ignore null.
Iterator.range(0, numCols)
.flatMap(i => if (row.isNullAt(i)) None else Some((i,
row.getDouble(i))))
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/Interaction.scala
b/mllib/src/main/scala/org/apache/spark/ml/feature/Interaction.scala
index 9a4f1d97c90..a81c55a1715 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/Interaction.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/Interaction.scala
@@ -108,9 +108,11 @@ class Interaction @Since("1.6.0") (@Since("1.6.0")
override val uid: String) ext
case _: NumericType | BooleanType => dataset(f.name).cast(DoubleType)
}
}
+ import org.apache.spark.util.ArrayImplicits._
dataset.select(
col("*"),
- interactFunc(struct(featureCols: _*)).as($(outputCol),
featureAttrs.toMetadata()))
+ interactFunc(struct(featureCols.toImmutableArraySeq: _*))
+ .as($(outputCol), featureAttrs.toMetadata()))
}
/**
diff --git a/mllib/src/main/scala/org/apache/spark/ml/feature/RFormula.scala
b/mllib/src/main/scala/org/apache/spark/ml/feature/RFormula.scala
index 9387ab3daeb..f3f85b40986 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/RFormula.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/RFormula.scala
@@ -476,7 +476,8 @@ private class ColumnPruner(override val uid: String, val
columnsToPrune: Set[Str
override def transform(dataset: Dataset[_]): DataFrame = {
val columnsToKeep = dataset.columns.filter(!columnsToPrune.contains(_))
- dataset.select(columnsToKeep.map(dataset.col): _*)
+ import org.apache.spark.util.ArrayImplicits._
+ dataset.select(columnsToKeep.map(dataset.col).toImmutableArraySeq: _*)
}
override def transformSchema(schema: StructType): StructType = {
@@ -564,7 +565,8 @@ private class VectorAttributeRewriter(
}
val otherCols = dataset.columns.filter(_ != vectorCol).map(dataset.col)
val rewrittenCol = dataset.col(vectorCol).as(vectorCol, metadata)
- dataset.select(otherCols :+ rewrittenCol : _*)
+ import org.apache.spark.util.ArrayImplicits._
+ dataset.select((otherCols :+ rewrittenCol).toImmutableArraySeq : _*)
}
override def transformSchema(schema: StructType): StructType = {
diff --git
a/mllib/src/main/scala/org/apache/spark/ml/feature/VectorAssembler.scala
b/mllib/src/main/scala/org/apache/spark/ml/feature/VectorAssembler.scala
index cf5b5ecb201..47c0ca22f96 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/feature/VectorAssembler.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/feature/VectorAssembler.scala
@@ -149,8 +149,9 @@ class VectorAssembler @Since("1.4.0") (@Since("1.4.0")
override val uid: String)
case _: NumericType | BooleanType =>
dataset(c).cast(DoubleType).as(s"${c}_double_$uid")
}
}
-
- filteredDataset.select(col("*"), assembleFunc(struct(args:
_*)).as($(outputCol), metadata))
+ import org.apache.spark.util.ArrayImplicits._
+ filteredDataset.select(col("*"),
+ assembleFunc(struct(args.toImmutableArraySeq: _*)).as($(outputCol),
metadata))
}
@Since("1.4.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/fpm/FPGrowth.scala
b/mllib/src/main/scala/org/apache/spark/ml/fpm/FPGrowth.scala
index 7fe9aa414f2..081a40bfbe8 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/fpm/FPGrowth.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/fpm/FPGrowth.scala
@@ -164,7 +164,8 @@ class FPGrowth @Since("2.2.0") (
instr.logPipelineStage(this)
instr.logDataset(dataset)
- instr.logParams(this, params: _*)
+ import org.apache.spark.util.ArrayImplicits._
+ instr.logParams(this, params.toImmutableArraySeq: _*)
val data = dataset.select($(itemsCol))
val items = data.where(col($(itemsCol)).isNotNull).rdd.map(r =>
r.getSeq[Any](0).toArray)
val mllibFP = new MLlibFPGrowth().setMinSupport($(minSupport))
diff --git a/mllib/src/main/scala/org/apache/spark/ml/fpm/PrefixSpan.scala
b/mllib/src/main/scala/org/apache/spark/ml/fpm/PrefixSpan.scala
index 5c98ffa394f..3ea76658d1a 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/fpm/PrefixSpan.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/fpm/PrefixSpan.scala
@@ -135,7 +135,8 @@ final class PrefixSpan(@Since("2.4.0") override val uid:
String) extends Params
@Since("2.4.0")
def findFrequentSequentialPatterns(dataset: Dataset[_]): DataFrame =
instrumented { instr =>
instr.logDataset(dataset)
- instr.logParams(this, params: _*)
+ import org.apache.spark.util.ArrayImplicits._
+ instr.logParams(this, params.toImmutableArraySeq: _*)
val sequenceColParam = $(sequenceCol)
val inputType = dataset.schema(sequenceColParam).dataType
diff --git a/mllib/src/main/scala/org/apache/spark/ml/r/KSTestWrapper.scala
b/mllib/src/main/scala/org/apache/spark/ml/r/KSTestWrapper.scala
index 21531eb057a..234b8bbf6f0 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/r/KSTestWrapper.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/r/KSTestWrapper.scala
@@ -49,7 +49,8 @@ private[r] object KSTestWrapper {
case Row(feature: Double) => feature
}
- val ksTestResult = kolmogorovSmirnovTest(rddData, distName, distParams :
_*)
+ import org.apache.spark.util.ArrayImplicits._
+ val ksTestResult = kolmogorovSmirnovTest(rddData, distName,
distParams.toImmutableArraySeq : _*)
new KSTestWrapper(ksTestResult, distName, distParams)
}
diff --git
a/mllib/src/main/scala/org/apache/spark/ml/regression/DecisionTreeRegressor.scala
b/mllib/src/main/scala/org/apache/spark/ml/regression/DecisionTreeRegressor.scala
index d9942f1c4f3..6c0089b6894 100644
---
a/mllib/src/main/scala/org/apache/spark/ml/regression/DecisionTreeRegressor.scala
+++
b/mllib/src/main/scala/org/apache/spark/ml/regression/DecisionTreeRegressor.scala
@@ -129,7 +129,8 @@ class DecisionTreeRegressor @Since("1.4.0")
(@Since("1.4.0") override val uid: S
instr.logPipelineStage(this)
instr.logDataset(instances)
- instr.logParams(this, params: _*)
+ import org.apache.spark.util.ArrayImplicits._
+ instr.logParams(this, params.toImmutableArraySeq: _*)
val trees = RandomForest.run(instances, strategy, numTrees = 1,
featureSubsetStrategy = "all",
seed = $(seed), instr = Some(instr), parentUID = Some(uid))
diff --git a/mllib/src/main/scala/org/apache/spark/ml/tree/treeModels.scala
b/mllib/src/main/scala/org/apache/spark/ml/tree/treeModels.scala
index cc917db98b3..47fb8bc9229 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/tree/treeModels.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/tree/treeModels.scala
@@ -535,7 +535,8 @@ private[ml] object EnsembleModelReadWrite {
val newNodeDataCol = df.schema("nodeData").dataType match {
case StructType(fields) =>
val cols = fields.map(f => col(s"nodeData.${f.name}")) :+
lit(-1L).as("rawCount")
- struct(cols: _*)
+ import org.apache.spark.util.ArrayImplicits._
+ struct(cols.toImmutableArraySeq: _*)
}
df = df.withColumn("nodeData", newNodeDataCol)
}
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/util/MLUtils.scala
b/mllib/src/main/scala/org/apache/spark/mllib/util/MLUtils.scala
index 7bce38cc38a..378f1381e4c 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/util/MLUtils.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/util/MLUtils.scala
@@ -359,7 +359,8 @@ object MLUtils extends Logging {
col(c)
}
}
- dataset.select(exprs: _*)
+ import org.apache.spark.util.ArrayImplicits._
+ dataset.select(exprs.toImmutableArraySeq: _*)
}
/**
@@ -411,7 +412,8 @@ object MLUtils extends Logging {
col(c)
}
}
- dataset.select(exprs: _*)
+ import org.apache.spark.util.ArrayImplicits._
+ dataset.select(exprs.toImmutableArraySeq: _*)
}
/**
@@ -461,7 +463,8 @@ object MLUtils extends Logging {
col(c)
}
}
- dataset.select(exprs: _*)
+ import org.apache.spark.util.ArrayImplicits._
+ dataset.select(exprs.toImmutableArraySeq: _*)
}
/**
@@ -511,7 +514,8 @@ object MLUtils extends Logging {
col(c)
}
}
- dataset.select(exprs: _*)
+ import org.apache.spark.util.ArrayImplicits._
+ dataset.select(exprs.toImmutableArraySeq: _*)
}
diff --git
a/mllib/src/test/scala/org/apache/spark/ml/feature/ImputerSuite.scala
b/mllib/src/test/scala/org/apache/spark/ml/feature/ImputerSuite.scala
index 5ef22a282c3..4873dacfc0f 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/feature/ImputerSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/feature/ImputerSuite.scala
@@ -339,9 +339,10 @@ class ImputerSuite extends MLTest with
DefaultReadWriteTest {
.setOutputCols(Array("out1"))
val types = Seq(IntegerType, LongType)
+ import org.apache.spark.util.ArrayImplicits._
for (mType <- types) {
// cast all columns to desired data type for testing
- val df2 = df.select(df.columns.map(c => col(c).cast(mType)): _*)
+ val df2 = df.select(df.columns.map(c =>
col(c).cast(mType)).toImmutableArraySeq: _*)
ImputerSuite.iterateStrategyTest(true, imputer, df2)
}
}
@@ -360,9 +361,10 @@ class ImputerSuite extends MLTest with
DefaultReadWriteTest {
.setOutputCol("out")
val types = Seq(IntegerType, LongType)
+ import org.apache.spark.util.ArrayImplicits._
for (mType <- types) {
// cast all columns to desired data type for testing
- val df2 = df.select(df.columns.map(c => col(c).cast(mType)): _*)
+ val df2 = df.select(df.columns.map(c =>
col(c).cast(mType)).toImmutableArraySeq: _*)
ImputerSuite.iterateStrategyTest(false, imputer, df2)
}
}
@@ -382,9 +384,10 @@ class ImputerSuite extends MLTest with
DefaultReadWriteTest {
.setMissingValue(-1.0)
val types = Seq(IntegerType, LongType)
+ import org.apache.spark.util.ArrayImplicits._
for (mType <- types) {
// cast all columns to desired data type for testing
- val df2 = df.select(df.columns.map(c => col(c).cast(mType)): _*)
+ val df2 = df.select(df.columns.map(c =>
col(c).cast(mType)).toImmutableArraySeq: _*)
ImputerSuite.iterateStrategyTest(true, imputer, df2)
}
}
@@ -404,9 +407,10 @@ class ImputerSuite extends MLTest with
DefaultReadWriteTest {
.setMissingValue(-1.0)
val types = Seq(IntegerType, LongType)
+ import org.apache.spark.util.ArrayImplicits._
for (mType <- types) {
// cast all columns to desired data type for testing
- val df2 = df.select(df.columns.map(c => col(c).cast(mType)): _*)
+ val df2 = df.select(df.columns.map(c =>
col(c).cast(mType)).toImmutableArraySeq: _*)
ImputerSuite.iterateStrategyTest(false, imputer, df2)
}
}
diff --git
a/mllib/src/test/scala/org/apache/spark/ml/source/image/ImageFileFormatSuite.scala
b/mllib/src/test/scala/org/apache/spark/ml/source/image/ImageFileFormatSuite.scala
index 411e056bffb..32c50625447 100644
---
a/mllib/src/test/scala/org/apache/spark/ml/source/image/ImageFileFormatSuite.scala
+++
b/mllib/src/test/scala/org/apache/spark/ml/source/image/ImageFileFormatSuite.scala
@@ -95,7 +95,8 @@ class ImageFileFormatSuite extends SparkFunSuite with
MLlibTestSparkContext {
.select(substring_index(col("image.origin"), "/", -1).as("origin"),
col("cls"), col("date"))
.collect()
- assert(Set(result: _*) === Set(
+ import org.apache.spark.util.ArrayImplicits._
+ assert(Set(result.toImmutableArraySeq: _*) === Set(
Row("29.5.a_b_EGDP022204.jpg", "kittens", "2018-01"),
Row("54893.jpg", "kittens", "2018-02"),
Row("DP153539.jpg", "kittens", "2018-02"),
diff --git
a/mllib/src/test/scala/org/apache/spark/ml/stat/KolmogorovSmirnovTestSuite.scala
b/mllib/src/test/scala/org/apache/spark/ml/stat/KolmogorovSmirnovTestSuite.scala
index 1312de3a1b5..2ae21401538 100644
---
a/mllib/src/test/scala/org/apache/spark/ml/stat/KolmogorovSmirnovTestSuite.scala
+++
b/mllib/src/test/scala/org/apache/spark/ml/stat/KolmogorovSmirnovTestSuite.scala
@@ -60,9 +60,10 @@ class KolmogorovSmirnovTestSuite
val cdf = (x: Double) => theoreticalDist.cumulativeProbability(x)
KolmogorovSmirnovTest.test(sampledDF, "sample", cdf).head()
} else {
+ import org.apache.spark.util.ArrayImplicits._
KolmogorovSmirnovTest.test(sampledDF, "sample",
theoreticalDistByName._1,
- theoreticalDistByName._2: _*
+ theoreticalDistByName._2.toImmutableArraySeq: _*
).head()
}
val theoreticalDistMath3 = if (theoreticalDist == null) {
diff --git a/mllib/src/test/scala/org/apache/spark/ml/util/MLTest.scala
b/mllib/src/test/scala/org/apache/spark/ml/util/MLTest.scala
index b847c905e5f..def04b50118 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/util/MLTest.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/util/MLTest.scala
@@ -112,13 +112,15 @@ trait MLTest extends StreamTest with TempDirectory {
self: Suite =>
val columnsWithMetadata = dataframe.schema.map { structField =>
col(structField.name).as(structField.name, structField.metadata)
}
- val streamDF = stream.toDS().toDF(columnNames:
_*).select(columnsWithMetadata: _*)
+ import org.apache.spark.util.ArrayImplicits._
+ val streamDF = stream.toDS()
+ .toDF(columnNames.toImmutableArraySeq: _*).select(columnsWithMetadata:
_*)
val data = dataframe.as[A].collect()
val streamOutput = transformer.transform(streamDF)
.select(firstResultCol, otherResultCols: _*)
testStream(streamOutput) (
- AddData(stream, data: _*),
+ AddData(stream, data.toImmutableArraySeq: _*),
CheckAnswer(globalCheckFunction)
)
}
diff --git
a/resource-managers/kubernetes/core/src/test/scala/org/apache/spark/deploy/k8s/features/DriverCommandFeatureStepSuite.scala
b/resource-managers/kubernetes/core/src/test/scala/org/apache/spark/deploy/k8s/features/DriverCommandFeatureStepSuite.scala
index 4c38989955b..b12508573b7 100644
---
a/resource-managers/kubernetes/core/src/test/scala/org/apache/spark/deploy/k8s/features/DriverCommandFeatureStepSuite.scala
+++
b/resource-managers/kubernetes/core/src/test/scala/org/apache/spark/deploy/k8s/features/DriverCommandFeatureStepSuite.scala
@@ -79,7 +79,7 @@ class DriverCommandFeatureStepSuite extends SparkFunSuite {
(
envPy.map(v => ENV_PYSPARK_PYTHON -> v :: Nil) ++
envDriverPy.map(v => ENV_PYSPARK_DRIVER_PYTHON -> v :: Nil)
- ).flatten.toArray: _*)
+ ).flatten.toSeq: _*)
val spec = applyFeatureStep(
PythonMainAppResource(mainResource),
diff --git
a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/generators.scala
b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/generators.scala
index 49cf01d472e..b4be09f333d 100644
---
a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/generators.scala
+++
b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/generators.scala
@@ -234,13 +234,15 @@ case class Stack(children: Seq[Expression]) extends
Generator {
override def eval(input: InternalRow): IterableOnce[InternalRow] = {
val values = children.tail.map(_.eval(input)).toArray
+
+ import org.apache.spark.util.ArrayImplicits._
for (row <- 0 until numRows) yield {
val fields = new Array[Any](numFields)
for (col <- 0 until numFields) {
val index = row * numFields + col
fields.update(col, if (index < values.length) values(index) else null)
}
- InternalRow(fields: _*)
+ InternalRow(fields.toImmutableArraySeq: _*)
}
}
@@ -293,12 +295,14 @@ case class ReplicateRows(children: Seq[Expression])
extends Generator with Codeg
override def eval(input: InternalRow): IterableOnce[InternalRow] = {
val numRows = children.head.eval(input).asInstanceOf[Long]
val values = children.tail.map(_.eval(input)).toArray
+
+ import org.apache.spark.util.ArrayImplicits._
Range.Long(0, numRows, 1).map { _ =>
val fields = new Array[Any](numColumns)
for (col <- 0 until numColumns) {
fields.update(col, values(col))
}
- InternalRow(fields: _*)
+ InternalRow(fields.toImmutableArraySeq: _*)
}
}
diff --git
a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/UnsafeRowConverterSuite.scala
b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/UnsafeRowConverterSuite.scala
index cbab8894cb5..44264a84663 100644
---
a/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/UnsafeRowConverterSuite.scala
+++
b/sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/expressions/UnsafeRowConverterSuite.scala
@@ -314,7 +314,9 @@ class UnsafeRowConverterSuite extends SparkFunSuite with
Matchers with PlanTestB
val row = new SpecificInternalRow(fieldTypes)
val values = Array(new CalendarInterval(0, 7, 0L), null)
- row.update(0, createArray(values: _*))
+
+ import org.apache.spark.util.ArrayImplicits._
+ row.update(0, createArray(values.toImmutableArraySeq: _*))
val unsafeRow: UnsafeRow = converter.apply(row)
testArrayInterval(unsafeRow.getArray(0), values)
}
diff --git
a/sql/core/src/main/scala/org/apache/spark/sql/DataFrameStatFunctions.scala
b/sql/core/src/main/scala/org/apache/spark/sql/DataFrameStatFunctions.scala
index a8c4d4f8d2b..2f285776052 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/DataFrameStatFunctions.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/DataFrameStatFunctions.scala
@@ -98,8 +98,9 @@ final class DataFrameStatFunctions private[sql](df:
DataFrame) {
cols: Array[String],
probabilities: Array[Double],
relativeError: Double): Array[Array[Double]] = withOrigin {
+ import org.apache.spark.util.ArrayImplicits._
StatFunctions.multipleApproxQuantiles(
- df.select(cols.map(col): _*),
+ df.select(cols.map(col).toImmutableArraySeq: _*),
cols,
probabilities,
relativeError).map(_.toArray).toArray
diff --git
a/sql/core/src/main/scala/org/apache/spark/sql/KeyValueGroupedDataset.scala
b/sql/core/src/main/scala/org/apache/spark/sql/KeyValueGroupedDataset.scala
index ef0a3e0266c..22dfed3ea4c 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/KeyValueGroupedDataset.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/KeyValueGroupedDataset.scala
@@ -241,7 +241,9 @@ class KeyValueGroupedDataset[K, V] private[sql](
SortExprs: Array[Column],
f: FlatMapGroupsFunction[K, V, U],
encoder: Encoder[U]): Dataset[U] = {
- flatMapSortedGroups(SortExprs: _*)((key, data) => f.call(key,
data.asJava).asScala)(encoder)
+ import org.apache.spark.util.ArrayImplicits._
+ flatMapSortedGroups(
+ SortExprs.toImmutableArraySeq: _*)((key, data) => f.call(key,
data.asJava).asScala)(encoder)
}
/**
@@ -901,7 +903,9 @@ class KeyValueGroupedDataset[K, V] private[sql](
otherSortExprs: Array[Column],
f: CoGroupFunction[K, V, U, R],
encoder: Encoder[R]): Dataset[R] = {
- cogroupSorted(other)(thisSortExprs: _*)(otherSortExprs: _*)(
+ import org.apache.spark.util.ArrayImplicits._
+ cogroupSorted(other)(
+ thisSortExprs.toImmutableArraySeq:
_*)(otherSortExprs.toImmutableArraySeq: _*)(
(key, left, right) => f.call(key, left.asJava,
right.asJava).asScala)(encoder)
}
diff --git
a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JDBCRDD.scala
b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JDBCRDD.scala
index 53b09179cc3..934ed9ac2a1 100644
---
a/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JDBCRDD.scala
+++
b/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/jdbc/JDBCRDD.scala
@@ -89,7 +89,7 @@ object JDBCRDD extends Logging {
* @return A Catalyst schema corresponding to columns in the given order.
*/
private def pruneSchema(schema: StructType, columns: Array[String]):
StructType = {
- val fieldMap = Map(schema.fields.map(x => x.name -> x): _*)
+ val fieldMap = schema.fields.map(x => x.name -> x).toMap
new StructType(columns.map(name => fieldMap(name)))
}
diff --git
a/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/StatFunctions.scala
b/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/StatFunctions.scala
index e7f1affbde4..db26f8c7758 100644
---
a/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/StatFunctions.scala
+++
b/sql/core/src/main/scala/org/apache/spark/sql/execution/stat/StatFunctions.scala
@@ -253,9 +253,10 @@ object StatFunctions extends Logging {
val valueColumns = columnNames.map { columnName =>
new Column(ElementAt(col(columnName).expr,
col("summary").expr)).as(columnName)
}
+ import org.apache.spark.util.ArrayImplicits._
ds.select(mapColumns: _*)
.withColumn("summary", explode(lit(selectedStatistics)))
- .select(Array(col("summary")) ++ valueColumns: _*)
+ .select((Array(col("summary")) ++ valueColumns).toImmutableArraySeq:
_*)
}
}
}
diff --git
a/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/OffsetSeqLog.scala
b/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/OffsetSeqLog.scala
index 5646f61440e..7e490ef4cd5 100644
---
a/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/OffsetSeqLog.scala
+++
b/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/OffsetSeqLog.scala
@@ -64,7 +64,8 @@ class OffsetSeqLog(sparkSession: SparkSession, path: String)
case "" => None
case md => Some(md)
}
- OffsetSeq.fill(metadata, lines.map(parseOffset).toArray: _*)
+ import org.apache.spark.util.ArrayImplicits._
+ OffsetSeq.fill(metadata,
lines.map(parseOffset).toArray.toImmutableArraySeq: _*)
}
override protected def serialize(offsetSeq: OffsetSeq, out: OutputStream):
Unit = {
diff --git
a/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/continuous/ContinuousRateStreamSource.scala
b/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/continuous/ContinuousRateStreamSource.scala
index 08840496b05..132d9a9d61e 100644
---
a/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/continuous/ContinuousRateStreamSource.scala
+++
b/sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/continuous/ContinuousRateStreamSource.scala
@@ -42,7 +42,8 @@ class RateStreamContinuousStream(rowsPerSecond: Long,
numPartitions: Int) extend
case RateStreamPartitionOffset(i, currVal, nextRead) =>
(i, ValueRunTimeMsPair(currVal, nextRead))
}
- RateStreamOffset(Map(tuples: _*))
+ import org.apache.spark.util.ArrayImplicits._
+ RateStreamOffset(Map(tuples.toImmutableArraySeq: _*))
}
override def deserializeOffset(json: String): Offset = {
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala
b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala
index d3271283baa..b28a23f13f8 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/DataFrameSuite.scala
@@ -1182,8 +1182,9 @@ class DataFrameSuite extends QueryTest
}
test("summary advanced") {
+ import org.apache.spark.util.ArrayImplicits._
val stats = Array("count", "50.01%", "max", "mean", "min", "25%")
- val orderMatters = person2.summary(stats: _*)
+ val orderMatters = person2.summary(stats.toImmutableArraySeq: _*)
assert(orderMatters.collect().map(_.getString(0)) === stats)
val onlyPercentiles = person2.summary("0.1%", "99.9%")
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/DatasetSuite.scala
b/sql/core/src/test/scala/org/apache/spark/sql/DatasetSuite.scala
index dcbd8948120..9285c31d702 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/DatasetSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/DatasetSuite.scala
@@ -2058,13 +2058,14 @@ class DatasetSuite extends QueryTest
}
test("SPARK-24569: Option of primitive types are mistakenly mapped to struct
type") {
+ import org.apache.spark.util.ArrayImplicits._
withSQLConf(SQLConf.CROSS_JOINS_ENABLED.key -> "true") {
val a = Seq(Some(1)).toDS()
val b = Seq(Some(1.2)).toDS()
val expected = Seq((Some(1), Some(1.2))).toDS()
val joined = a.joinWith(b, lit(true))
assert(joined.schema == expected.schema)
- checkDataset(joined, expected.collect(): _*)
+ checkDataset(joined, expected.collect().toImmutableArraySeq: _*)
}
}
@@ -2078,7 +2079,8 @@ class DatasetSuite extends QueryTest
val ds1 = spark.createDataset(rdd)
val ds2 = spark.createDataset(rdd)(encoder)
assert(ds1.schema == ds2.schema)
- checkDataset(ds1.select("_2._2"), ds2.select("_2._2").collect(): _*)
+ import org.apache.spark.util.ArrayImplicits._
+ checkDataset(ds1.select("_2._2"),
ds2.select("_2._2").collect().toImmutableArraySeq: _*)
}
test("SPARK-23862: Spark ExpressionEncoder should support Java Enum type
from Scala") {
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/GenTPCDSData.scala
b/sql/core/src/test/scala/org/apache/spark/sql/GenTPCDSData.scala
index 6768c5fd07b..5f95ba4f385 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/GenTPCDSData.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/GenTPCDSData.scala
@@ -169,7 +169,8 @@ class TPCDSTables(spark: SparkSession, dsdgenDir: String,
scaleFactor: Int)
}
c.as(f.name)
}
- stringData.select(columns: _*)
+ import org.apache.spark.util.ArrayImplicits._
+ stringData.select(columns.toImmutableArraySeq: _*)
}
convertedData
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/ParametersSuite.scala
b/sql/core/src/test/scala/org/apache/spark/sql/ParametersSuite.scala
index afbe9cdac63..974def7f3b8 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/ParametersSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/ParametersSuite.scala
@@ -532,6 +532,7 @@ class ParametersSuite extends QueryTest with
SharedSparkSession {
}
test("SPARK-45033: maps as parameters") {
+ import org.apache.spark.util.ArrayImplicits._
def fromArr(keys: Array[_], values: Array[_]): Column = {
map_from_arrays(Column(Literal(keys)), Column(Literal(values)))
}
@@ -540,21 +541,21 @@ class ParametersSuite extends QueryTest with
SharedSparkSession {
}
def createMap(keys: Array[_], values: Array[_]): Column = {
val zipped = keys.map(k => Column(Literal(k))).zip(values.map(v =>
Column(Literal(v))))
- map(zipped.map { case (k, v) => Seq(k, v) }.flatten: _*)
+ map(zipped.flatMap { case (k, v) => Seq(k, v) }.toImmutableArraySeq: _*)
}
def callMap(keys: Array[_], values: Array[_]): Column = {
val zipped = keys.map(k => Column(Literal(k))).zip(values.map(v =>
Column(Literal(v))))
- call_function("map", zipped.map { case (k, v) => Seq(k, v) }.flatten: _*)
+ call_function("map", zipped.flatMap { case (k, v) => Seq(k, v)
}.toImmutableArraySeq: _*)
}
def fromEntries(keys: Array[_], values: Array[_]): Column = {
val structures = keys.zip(values)
.map { case (k, v) => struct(Column(Literal(k)), Column(Literal(v)))}
- map_from_entries(array(structures: _*))
+ map_from_entries(array(structures.toImmutableArraySeq: _*))
}
def callFromEntries(keys: Array[_], values: Array[_]): Column = {
val structures = keys.zip(values)
.map { case (k, v) => struct(Column(Literal(k)), Column(Literal(v)))}
- call_function("map_from_entries", call_function("array", structures: _*))
+ call_function("map_from_entries", call_function("array",
structures.toImmutableArraySeq: _*))
}
Seq(fromArr(_, _), createMap(_, _), callFromArr(_, _), callMap(_,
_)).foreach { f =>
diff --git
a/sql/core/src/test/scala/org/apache/spark/sql/connector/SimpleWritableDataSource.scala
b/sql/core/src/test/scala/org/apache/spark/sql/connector/SimpleWritableDataSource.scala
index 235a8ff3869..de8cf7a7b2d 100644
---
a/sql/core/src/test/scala/org/apache/spark/sql/connector/SimpleWritableDataSource.scala
+++
b/sql/core/src/test/scala/org/apache/spark/sql/connector/SimpleWritableDataSource.scala
@@ -157,6 +157,7 @@ class CSVReaderFactory(conf: SerializableConfiguration)
val fs = filePath.getFileSystem(conf.value)
new PartitionReader[InternalRow] {
+ import org.apache.spark.util.ArrayImplicits._
private val inputStream = fs.open(filePath)
private val lines = new BufferedReader(new
InputStreamReader(inputStream))
.lines().iterator().asScala
@@ -172,7 +173,8 @@ class CSVReaderFactory(conf: SerializableConfiguration)
}
}
- override def get(): InternalRow =
InternalRow(currentLine.split(",").map(_.trim.toInt): _*)
+ override def get(): InternalRow =
+
InternalRow(currentLine.split(",").map(_.trim.toInt).toImmutableArraySeq: _*)
override def close(): Unit = {
inputStream.close()
diff --git
a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/FileMetadataStructSuite.scala
b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/FileMetadataStructSuite.scala
index 0e4985bac99..6bf72b82564 100644
---
a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/FileMetadataStructSuite.scala
+++
b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/FileMetadataStructSuite.scala
@@ -1083,7 +1083,8 @@ class FileMetadataStructSuite extends QueryTest with
SharedSparkSession {
// Transform the result into a literal that can be used in an expression.
val metadataColumnFields = metadataColumnRow.schema.fields
.map(field =>
lit(metadataColumnRow.getAs[Any](field.name)).as(field.name))
- val metadataColumnStruct = struct(metadataColumnFields: _*)
+ import org.apache.spark.util.ArrayImplicits._
+ val metadataColumnStruct =
struct(metadataColumnFields.toImmutableArraySeq: _*)
val selectSingleRowDf = spark.read.load(dir.getAbsolutePath)
.where(col("_metadata").equalTo(lit(metadataColumnStruct)))
diff --git
a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/csv/CSVBenchmark.scala
b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/csv/CSVBenchmark.scala
index eb561e13fc6..e9cf35d9fab 100644
---
a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/csv/CSVBenchmark.scala
+++
b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/csv/CSVBenchmark.scala
@@ -70,6 +70,7 @@ object CSVBenchmark extends SqlBasedBenchmark {
val benchmark = new Benchmark(s"Wide rows with $colsNum columns", rowsNum,
output = output)
withTempPath { path =>
+ import org.apache.spark.util.ArrayImplicits._
val fields = Seq.tabulate(colsNum)(i => StructField(s"col$i",
IntegerType))
val schema = StructType(fields)
val values = (0 until colsNum).map(i => i.toString).mkString(",")
@@ -87,7 +88,7 @@ object CSVBenchmark extends SqlBasedBenchmark {
}
val cols100 = columnNames.take(100).map(Column(_))
benchmark.addCase(s"Select 100 columns", numIters) { _ =>
- ds.select(cols100: _*).noop()
+ ds.select(cols100.toImmutableArraySeq: _*).noop()
}
benchmark.addCase(s"Select one column", numIters) { _ =>
ds.select($"col1").noop()
@@ -100,7 +101,7 @@ object CSVBenchmark extends SqlBasedBenchmark {
(1 until colsNum).map(i => StructField(s"col$i", IntegerType)))
val dsErr1 = spark.read.schema(schemaErr1).csv(path.getAbsolutePath)
benchmark.addCase(s"Select 100 columns, one bad input field", numIters)
{ _ =>
- dsErr1.select(cols100: _*).noop()
+ dsErr1.select(cols100.toImmutableArraySeq: _*).noop()
}
val badRecColName = "badRecord"
@@ -109,7 +110,7 @@ object CSVBenchmark extends SqlBasedBenchmark {
.option("columnNameOfCorruptRecord", badRecColName)
.csv(path.getAbsolutePath)
benchmark.addCase(s"Select 100 columns, corrupt record field", numIters)
{ _ =>
- dsErr2.select((Column(badRecColName) +: cols100): _*).noop()
+ dsErr2.select((Column(badRecColName) +: cols100).toImmutableArraySeq:
_*).noop()
}
benchmark.run()
diff --git
a/sql/core/src/test/scala/org/apache/spark/sql/streaming/StreamSuite.scala
b/sql/core/src/test/scala/org/apache/spark/sql/streaming/StreamSuite.scala
index 66d37e996a6..953bbddf6ab 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/streaming/StreamSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/streaming/StreamSuite.scala
@@ -224,7 +224,7 @@ class StreamSuite extends StreamTest {
// Parquet write page-level CRC checksums will change the file
size and
// affect the data order when reading these files. Please see
PARQUET-1746 for details.
val outputDf =
spark.read.parquet(outputDir.getAbsolutePath).sort($"a").as[Long]
- checkDataset[Long](outputDf, (0L to 10L).toArray: _*)
+ checkDataset[Long](outputDf, 0L to 10L: _*)
} finally {
query.stop()
}
diff --git
a/sql/core/src/test/scala/org/apache/spark/sql/streaming/StreamingQuerySuite.scala
b/sql/core/src/test/scala/org/apache/spark/sql/streaming/StreamingQuerySuite.scala
index 1e0fa5b6bc9..e388de21405 100644
---
a/sql/core/src/test/scala/org/apache/spark/sql/streaming/StreamingQuerySuite.scala
+++
b/sql/core/src/test/scala/org/apache/spark/sql/streaming/StreamingQuerySuite.scala
@@ -891,7 +891,8 @@ class StreamingQuerySuite extends StreamTest with
BeforeAndAfter with Logging wi
}
override def getOffset: Option[Offset] = Some(LongOffset(1))
override def getBatch(start: Option[Offset], end: Offset): DataFrame = {
- spark.range(2).toDF(MockSourceProvider.fakeSchema.fieldNames: _*)
+ import org.apache.spark.util.ArrayImplicits._
+
spark.range(2).toDF(MockSourceProvider.fakeSchema.fieldNames.toImmutableArraySeq:
_*)
}
override def schema: StructType = MockSourceProvider.fakeSchema
}
diff --git
a/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/CliSuite.scala
b/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/CliSuite.scala
index 110ef7b0aff..649c985cade 100644
---
a/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/CliSuite.scala
+++
b/sql/hive-thriftserver/src/test/scala/org/apache/spark/sql/hive/thriftserver/CliSuite.scala
@@ -703,6 +703,7 @@ class CliSuite extends SparkFunSuite {
testRetry("formats of error messages") {
def check(format: ErrorMessageFormat.Value, errorMessage: String, silent:
Boolean): Unit = {
val expected = errorMessage.split(System.lineSeparator()).map("" -> _)
+ import org.apache.spark.util.ArrayImplicits._
runCliWithin(
1.minute,
extraArgs = Seq(
@@ -710,7 +711,7 @@ class CliSuite extends SparkFunSuite {
"--conf", s"${SQLConf.ERROR_MESSAGE_FORMAT.key}=$format",
"--conf", s"${SQLConf.ANSI_ENABLED.key}=true",
"-e", "select 1 / 0"),
- errorResponses = Seq("DIVIDE_BY_ZERO"))(expected: _*)
+ errorResponses = Seq("DIVIDE_BY_ZERO"))(expected.toImmutableArraySeq:
_*)
}
check(
format = ErrorMessageFormat.PRETTY,
diff --git
a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/AggregationQuerySuite.scala
b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/AggregationQuerySuite.scala
index dc8b184fcee..4b000fff0eb 100644
---
a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/AggregationQuerySuite.scala
+++
b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/AggregationQuerySuite.scala
@@ -941,8 +941,10 @@ abstract class AggregationQuerySuite extends QueryTest
with SQLTestUtils with Te
data
.find(r => r.getInt(0) == 50)
.getOrElse(fail("A row with id 50 should be the expected answer."))
+
+ import org.apache.spark.util.ArrayImplicits._
checkAnswer(
- df.agg(udaf(allColumns: _*)),
+ df.agg(udaf(allColumns.toImmutableArraySeq: _*)),
// udaf returns a Row as the output value.
Row(expectedAnswer)
)
diff --git
a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/ObjectHashAggregateSuite.scala
b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/ObjectHashAggregateSuite.scala
index cc95de793ee..4e2db214035 100644
---
a/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/ObjectHashAggregateSuite.scala
+++
b/sql/hive/src/test/scala/org/apache/spark/sql/hive/execution/ObjectHashAggregateSuite.scala
@@ -152,13 +152,15 @@ class ObjectHashAggregateSuite
val df = spark.createDataFrame(spark.sparkContext.parallelize(data, 1),
schema)
val aggFunctions = schema.fieldNames.map(f => typed_count(col(f)))
+ import org.apache.spark.util.ArrayImplicits._
checkAnswer(
- df.agg(aggFunctions.head, aggFunctions.tail: _*),
+ df.agg(aggFunctions.head, aggFunctions.tail.toImmutableArraySeq: _*),
Row.fromSeq(data.map(_.toSeq).transpose.map(_.count(_ != null): Long))
)
checkAnswer(
- df.groupBy($"id" % 4 as "mod").agg(aggFunctions.head,
aggFunctions.tail: _*),
+ df.groupBy($"id" % 4 as "mod")
+ .agg(aggFunctions.head, aggFunctions.tail.toImmutableArraySeq: _*),
data.groupBy(_.getInt(0) % 4).map { case (key, value) =>
key -> Row.fromSeq(value.map(_.toSeq).transpose.map(_.count(_ !=
null): Long))
}.toSeq.map {
@@ -168,7 +170,7 @@ class ObjectHashAggregateSuite
withSQLConf(SQLConf.OBJECT_AGG_SORT_BASED_FALLBACK_THRESHOLD.key -> "5")
{
checkAnswer(
- df.agg(aggFunctions.head, aggFunctions.tail: _*),
+ df.agg(aggFunctions.head, aggFunctions.tail.toImmutableArraySeq: _*),
Row.fromSeq(data.map(_.toSeq).transpose.map(_.count(_ != null):
Long))
)
}
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