[SPARK-49568][CONNECT][SQL] Remove self type from Dataset

### What changes were proposed in this pull request?
This PR removes the self type parameter from Dataset. This turned out to be a bit noisy. The self type is replaced by a combination of covariant return types and abstract types. Abstract types are used when a method takes a Dataset (or a KeyValueGroupedDataset) as an argument.

### Why are the changes needed?
The self type made using the classes in sql/api a bit noisy.

### Does this PR introduce _any_ user-facing change?
No.

### How was this patch tested?
Existing tests.

### Was this patch authored or co-authored using generative AI tooling?
No.

Closes #48146 from hvanhovell/SPARK-49568.

Authored-by: Herman van Hovell <[email protected]>
Signed-off-by: Herman van Hovell <[email protected]>

connector/connect/client/jvm/src/main/scala/org/apache/spark/sql/DataFrameNaFunctions.scala

@@ -22,14 +22,15 @@ import scala.jdk.CollectionConverters._
 import org.apache.spark.connect.proto.{NAReplace, Relation}
 import org.apache.spark.connect.proto.Expression.{Literal => GLiteral}
 import org.apache.spark.connect.proto.NAReplace.Replacement
+import org.apache.spark.sql.connect.ConnectConversions._
 
 /**
  * Functionality for working with missing data in `DataFrame`s.
  *
  * @since 3.4.0
  */
 final class DataFrameNaFunctions private[sql] (sparkSession: SparkSession, root: Relation)
-    extends api.DataFrameNaFunctions[Dataset] {
+    extends api.DataFrameNaFunctions {
   import sparkSession.RichColumn
 
   override protected def drop(minNonNulls: Option[Int]): Dataset[Row] =

connector/connect/client/jvm/src/main/scala/org/apache/spark/sql/DataFrameReader.scala

@@ -23,6 +23,7 @@ import scala.jdk.CollectionConverters._
 
 import org.apache.spark.annotation.Stable
 import org.apache.spark.connect.proto.Parse.ParseFormat
+import org.apache.spark.sql.connect.ConnectConversions._
 import org.apache.spark.sql.connect.common.DataTypeProtoConverter
 import org.apache.spark.sql.types.StructType
 
@@ -33,8 +34,8 @@ import org.apache.spark.sql.types.StructType
  * @since 3.4.0
  */
 @Stable
-class DataFrameReader private[sql] (sparkSession: SparkSession)
-    extends api.DataFrameReader[Dataset] {
+class DataFrameReader private[sql] (sparkSession: SparkSession) extends api.DataFrameReader {
+  type DS[U] = Dataset[U]
 
   /** @inheritdoc */
   override def format(source: String): this.type = super.format(source)

connector/connect/client/jvm/src/main/scala/org/apache/spark/sql/DataFrameStatFunctions.scala

@@ -22,6 +22,7 @@ import java.{lang => jl, util => ju}
 import org.apache.spark.connect.proto.{Relation, StatSampleBy}
 import org.apache.spark.sql.DataFrameStatFunctions.approxQuantileResultEncoder
 import org.apache.spark.sql.catalyst.encoders.AgnosticEncoders.{ArrayEncoder, PrimitiveDoubleEncoder}
+import org.apache.spark.sql.connect.ConnectConversions._
 import org.apache.spark.sql.functions.lit
 
 /**
@@ -30,7 +31,7 @@ import org.apache.spark.sql.functions.lit
  * @since 3.4.0
  */
 final class DataFrameStatFunctions private[sql] (protected val df: DataFrame)
-    extends api.DataFrameStatFunctions[Dataset] {
+    extends api.DataFrameStatFunctions {
   private def root: Relation = df.plan.getRoot
   private val sparkSession: SparkSession = df.sparkSession
 

connector/connect/client/jvm/src/main/scala/org/apache/spark/sql/Dataset.scala

@@ -32,6 +32,7 @@ import org.apache.spark.sql.catalyst.ScalaReflection
 import org.apache.spark.sql.catalyst.encoders.AgnosticEncoder
 import org.apache.spark.sql.catalyst.encoders.AgnosticEncoders._
 import org.apache.spark.sql.catalyst.expressions.OrderUtils
+import org.apache.spark.sql.connect.ConnectConversions._
 import org.apache.spark.sql.connect.client.SparkResult
 import org.apache.spark.sql.connect.common.{DataTypeProtoConverter, StorageLevelProtoConverter}
 import org.apache.spark.sql.errors.DataTypeErrors.toSQLId
@@ -134,8 +135,8 @@ class Dataset[T] private[sql] (
     val sparkSession: SparkSession,
     @DeveloperApi val plan: proto.Plan,
     val encoder: Encoder[T])
-    extends api.Dataset[T, Dataset] {
-  type RGD = RelationalGroupedDataset
+    extends api.Dataset[T] {
+  type DS[U] = Dataset[U]
 
   import sparkSession.RichColumn
 

connector/connect/client/jvm/src/main/scala/org/apache/spark/sql/KeyValueGroupedDataset.scala

@@ -26,6 +26,7 @@ import org.apache.spark.api.java.function._
 import org.apache.spark.connect.proto
 import org.apache.spark.sql.catalyst.encoders.AgnosticEncoder
 import org.apache.spark.sql.catalyst.encoders.AgnosticEncoders.ProductEncoder
+import org.apache.spark.sql.connect.ConnectConversions._
 import org.apache.spark.sql.connect.common.UdfUtils
 import org.apache.spark.sql.expressions.SparkUserDefinedFunction
 import org.apache.spark.sql.functions.col
@@ -40,8 +41,7 @@ import org.apache.spark.sql.streaming.{GroupState, GroupStateTimeout, OutputMode
  *
  * @since 3.5.0
  */
-class KeyValueGroupedDataset[K, V] private[sql] ()
-    extends api.KeyValueGroupedDataset[K, V, Dataset] {
+class KeyValueGroupedDataset[K, V] private[sql] () extends api.KeyValueGroupedDataset[K, V] {
   type KVDS[KY, VL] = KeyValueGroupedDataset[KY, VL]
 
   private def unsupported(): Nothing = throw new UnsupportedOperationException()

connector/connect/client/jvm/src/main/scala/org/apache/spark/sql/RelationalGroupedDataset.scala

@@ -20,6 +20,7 @@ package org.apache.spark.sql
 import scala.jdk.CollectionConverters._
 
 import org.apache.spark.connect.proto
+import org.apache.spark.sql.connect.ConnectConversions._
 
 /**
  * A set of methods for aggregations on a `DataFrame`, created by [[Dataset#groupBy groupBy]],
@@ -39,8 +40,7 @@ class RelationalGroupedDataset private[sql] (
     groupType: proto.Aggregate.GroupType,
     pivot: Option[proto.Aggregate.Pivot] = None,
     groupingSets: Option[Seq[proto.Aggregate.GroupingSets]] = None)
-    extends api.RelationalGroupedDataset[Dataset] {
-  type RGD = RelationalGroupedDataset
+    extends api.RelationalGroupedDataset {
   import df.sparkSession.RichColumn
 
   protected def toDF(aggExprs: Seq[Column]): DataFrame = {

connector/connect/client/jvm/src/main/scala/org/apache/spark/sql/SparkSession.scala

@@ -69,7 +69,7 @@ import org.apache.spark.util.ArrayImplicits._
 class SparkSession private[sql] (
     private[sql] val client: SparkConnectClient,
     private val planIdGenerator: AtomicLong)
-    extends api.SparkSession[Dataset]
+    extends api.SparkSession
     with Logging {
 
   private[this] val allocator = new RootAllocator()

connector/connect/client/jvm/src/main/scala/org/apache/spark/sql/catalog/Catalog.scala

@@ -20,10 +20,11 @@ package org.apache.spark.sql.catalog
 import java.util
 
 import org.apache.spark.sql.{api, DataFrame, Dataset}
+import org.apache.spark.sql.connect.ConnectConversions._
 import org.apache.spark.sql.types.StructType
 
 /** @inheritdoc */
-abstract class Catalog extends api.Catalog[Dataset] {
+abstract class Catalog extends api.Catalog {
 
   /** @inheritdoc */
   override def listDatabases(): Dataset[Database]

connector/connect/client/jvm/src/main/scala/org/apache/spark/sql/connect/ConnectConversions.scala

@@ -0,0 +1,51 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.spark.sql.connect
+
+import scala.language.implicitConversions
+
+import org.apache.spark.annotation.DeveloperApi
+import org.apache.spark.sql._
+
+/**
+ * Conversions from sql interfaces to the Connect specific implementation.
+ *
+ * This class is mainly used by the implementation. In the case of connect it should be extremely
+ * rare that a developer needs these classes.
+ *
+ * We provide both a trait and an object. The trait is useful in situations where an extension
+ * developer needs to use these conversions in a project covering multiple Spark versions. They
+ * can create a shim for these conversions, the Spark 4+ version of the shim implements this
+ * trait, and shims for older versions do not.
+ */
+@DeveloperApi
+trait ConnectConversions {
+  implicit def castToImpl(session: api.SparkSession): SparkSession =
+    session.asInstanceOf[SparkSession]
+
+  implicit def castToImpl[T](ds: api.Dataset[T]): Dataset[T] =
+    ds.asInstanceOf[Dataset[T]]
+
+  implicit def castToImpl(rgds: api.RelationalGroupedDataset): RelationalGroupedDataset =
+    rgds.asInstanceOf[RelationalGroupedDataset]
+
+  implicit def castToImpl[K, V](
+      kvds: api.KeyValueGroupedDataset[K, V]): KeyValueGroupedDataset[K, V] =
+    kvds.asInstanceOf[KeyValueGroupedDataset[K, V]]
+}
+
+object ConnectConversions extends ConnectConversions

connector/connect/client/jvm/src/main/scala/org/apache/spark/sql/streaming/StreamingQuery.scala

@@ -26,10 +26,10 @@ import org.apache.spark.connect.proto.ExecutePlanResponse
 import org.apache.spark.connect.proto.StreamingQueryCommand
 import org.apache.spark.connect.proto.StreamingQueryCommandResult
 import org.apache.spark.connect.proto.StreamingQueryManagerCommandResult.StreamingQueryInstance
-import org.apache.spark.sql.{api, Dataset, SparkSession}
+import org.apache.spark.sql.{api, SparkSession}
 
 /** @inheritdoc */
-trait StreamingQuery extends api.StreamingQuery[Dataset] {
+trait StreamingQuery extends api.StreamingQuery {
 
   /** @inheritdoc */
   override def sparkSession: SparkSession

connector/connect/client/jvm/src/test/scala/org/apache/spark/sql/connect/client/CheckConnectJvmClientCompatibility.scala

@@ -158,6 +158,7 @@ object CheckConnectJvmClientCompatibility {
       ProblemFilters.exclude[Problem]("org.apache.spark.sql.catalyst.*"),
       ProblemFilters.exclude[Problem]("org.apache.spark.sql.columnar.*"),
       ProblemFilters.exclude[Problem]("org.apache.spark.sql.connector.*"),
+      ProblemFilters.exclude[Problem]("org.apache.spark.sql.classic.*"),
       ProblemFilters.exclude[Problem]("org.apache.spark.sql.execution.*"),
       ProblemFilters.exclude[Problem]("org.apache.spark.sql.internal.*"),
       ProblemFilters.exclude[Problem]("org.apache.spark.sql.jdbc.*"),

project/MimaExcludes.scala

@@ -201,6 +201,8 @@ object MimaExcludes {
     ProblemFilters.exclude[Problem]("org.apache.spark.sql.execution.*"),
     ProblemFilters.exclude[Problem]("org.apache.spark.sql.internal.*"),
     ProblemFilters.exclude[Problem]("org.apache.spark.sql.errors.*"),
+    ProblemFilters.exclude[Problem]("org.apache.spark.sql.classic.*"),
+    ProblemFilters.exclude[Problem]("org.apache.spark.sql.connect.*"),
     // DSv2 catalog and expression APIs are unstable yet. We should enable this back.
     ProblemFilters.exclude[Problem]("org.apache.spark.sql.connector.catalog.*"),
     ProblemFilters.exclude[Problem]("org.apache.spark.sql.connector.expressions.*"),

project/SparkBuild.scala

@@ -1352,6 +1352,7 @@ trait SharedUnidocSettings {
       .map(_.filterNot(_.getCanonicalPath.contains("org/apache/spark/util/kvstore")))
       .map(_.filterNot(_.getCanonicalPath.contains("org/apache/spark/sql/catalyst")))
       .map(_.filterNot(_.getCanonicalPath.contains("org/apache/spark/sql/connect/")))
+      .map(_.filterNot(_.getCanonicalPath.contains("org/apache/spark/sql/classic/")))
       .map(_.filterNot(_.getCanonicalPath.contains("org/apache/spark/sql/execution")))
       .map(_.filterNot(_.getCanonicalPath.contains("org/apache/spark/sql/hive")))
       .map(_.filterNot(_.getCanonicalPath.contains("org/apache/spark/sql/catalog/v2/utils")))