Revert "[SPARK-49700][CONNECT][SQL] Unified Scala Interface for Connect and Classic"

### Why are the changes needed?

This reverts commit 86efd59 from branch-4.0.

### Does this PR introduce _any_ user-facing change?

This commit causes SBT and Maven test failure.
#48818 (comment)

### How was this patch tested?

Pass the CIs and manual test.

**BEFORE**
```
$ build/sbt clean "catalyst/testOnly org.apache.spark.sql.catalyst.encoders.EncoderResolutionSuite"
...
[info] *** 1 SUITE ABORTED ***
[error] Error during tests:
[error] 	org.apache.spark.sql.catalyst.encoders.EncoderResolutionSuite
[error] (catalyst / Test / testOnly) sbt.TestsFailedException: Tests unsuccessful
[error] Total time: 66 s (01:06), completed Jan 27, 2025, 9:52:35 AM
```

**AFTER**
```
$ build/sbt clean "catalyst/testOnly org.apache.spark.sql.catalyst.encoders.EncoderResolutionSuite"
...
[info] Run completed in 2 seconds, 236 milliseconds.
[info] Total number of tests run: 28
[info] Suites: completed 1, aborted 0
[info] Tests: succeeded 28, failed 0, canceled 0, ignored 0, pending 0
[info] All tests passed.
[success] Total time: 68 s (01:08), completed Jan 27, 2025, 9:51:08 AM
```

### Was this patch authored or co-authored using generative AI tooling?

No.

Closes #49696 from dongjoon-hyun/SPARK-49700.

Authored-by: Dongjoon Hyun <dongjoon@apache.org>
Signed-off-by: Dongjoon Hyun <dongjoon@apache.org>

Author: dongjoon-hyun

common/utils/src/main/resources/error/error-conditions.json

@@ -5283,11 +5283,6 @@
           "Resilient Distributed Datasets (RDDs)."
         ]
       },
-      "REGISTER_UDAF" : {
-        "message" : [
-          "Registering User Defined Aggregate Functions (UDAFs)."
-        ]
-      },
       "SESSION_BASE_RELATION_TO_DATAFRAME" : {
         "message" : [
           "Invoking SparkSession 'baseRelationToDataFrame'. This is server side developer API"

…k/sql/connect/DataFrameNaFunctions.scala …che/spark/sql/DataFrameNaFunctions.scalasql/connect/common/src/main/scala/org/apache/spark/sql/connect/DataFrameNaFunctions.scala renamed to connector/connect/client/jvm/src/main/scala/org/apache/spark/sql/DataFrameNaFunctions.scala sql/connect/common/src/main/scala/org/apache/spark/sql/connect/DataFrameNaFunctions.scala renamed to connector/connect/client/jvm/src/main/scala/org/apache/spark/sql/DataFrameNaFunctions.scala

@@ -15,30 +15,28 @@
  * limitations under the License.
  */
 
-package org.apache.spark.sql.connect
+package org.apache.spark.sql
 
 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
 import org.apache.spark.sql.connect.ConnectConversions._
-import org.apache.spark.sql.functions
 
 /**
  * Functionality for working with missing data in `DataFrame`s.
  *
  * @since 3.4.0
  */
 final class DataFrameNaFunctions private[sql] (sparkSession: SparkSession, root: Relation)
-    extends sql.DataFrameNaFunctions {
+    extends api.DataFrameNaFunctions {
   import sparkSession.RichColumn
 
-  override protected def drop(minNonNulls: Option[Int]): DataFrame =
+  override protected def drop(minNonNulls: Option[Int]): Dataset[Row] =
     buildDropDataFrame(None, minNonNulls)
 
-  override protected def drop(minNonNulls: Option[Int], cols: Seq[String]): DataFrame =
+  override protected def drop(minNonNulls: Option[Int], cols: Seq[String]): Dataset[Row] =
     buildDropDataFrame(Option(cols), minNonNulls)
 
   private def buildDropDataFrame(

…/spark/sql/connect/DataFrameReader.scala …g/apache/spark/sql/DataFrameReader.scalasql/connect/common/src/main/scala/org/apache/spark/sql/connect/DataFrameReader.scala renamed to connector/connect/client/jvm/src/main/scala/org/apache/spark/sql/DataFrameReader.scala sql/connect/common/src/main/scala/org/apache/spark/sql/connect/DataFrameReader.scala renamed to connector/connect/client/jvm/src/main/scala/org/apache/spark/sql/DataFrameReader.scala

@@ -15,7 +15,7 @@
  * limitations under the License.
  */
 
-package org.apache.spark.sql.connect
+package org.apache.spark.sql
 
 import java.util.Properties
 
@@ -25,7 +25,6 @@ import org.apache.spark.annotation.Stable
 import org.apache.spark.api.java.JavaRDD
 import org.apache.spark.connect.proto.Parse.ParseFormat
 import org.apache.spark.rdd.RDD
-import org.apache.spark.sql
 import org.apache.spark.sql.connect.ConnectClientUnsupportedErrors
 import org.apache.spark.sql.connect.ConnectConversions._
 import org.apache.spark.sql.connect.common.DataTypeProtoConverter
@@ -38,7 +37,8 @@ import org.apache.spark.sql.types.StructType
  * @since 3.4.0
  */
 @Stable
-class DataFrameReader private[sql] (sparkSession: SparkSession) extends sql.DataFrameReader {
+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)
@@ -140,15 +140,15 @@ class DataFrameReader private[sql] (sparkSession: SparkSession) extends sql.Data
   override def json(paths: String*): DataFrame = super.json(paths: _*)
 
   /** @inheritdoc */
-  def json(jsonDataset: sql.Dataset[String]): DataFrame =
+  def json(jsonDataset: Dataset[String]): DataFrame =
     parse(jsonDataset, ParseFormat.PARSE_FORMAT_JSON)
 
   /** @inheritdoc */
-  override def json(jsonRDD: JavaRDD[String]): DataFrame =
+  override def json(jsonRDD: JavaRDD[String]): Dataset[Row] =
     throw ConnectClientUnsupportedErrors.rdd()
 
   /** @inheritdoc */
-  override def json(jsonRDD: RDD[String]): DataFrame =
+  override def json(jsonRDD: RDD[String]): Dataset[Row] =
     throw ConnectClientUnsupportedErrors.rdd()
 
   /** @inheritdoc */
@@ -159,7 +159,7 @@ class DataFrameReader private[sql] (sparkSession: SparkSession) extends sql.Data
   override def csv(paths: String*): DataFrame = super.csv(paths: _*)
 
   /** @inheritdoc */
-  def csv(csvDataset: sql.Dataset[String]): DataFrame =
+  def csv(csvDataset: Dataset[String]): DataFrame =
     parse(csvDataset, ParseFormat.PARSE_FORMAT_CSV)
 
   /** @inheritdoc */
@@ -170,7 +170,7 @@ class DataFrameReader private[sql] (sparkSession: SparkSession) extends sql.Data
   override def xml(paths: String*): DataFrame = super.xml(paths: _*)
 
   /** @inheritdoc */
-  def xml(xmlDataset: sql.Dataset[String]): DataFrame =
+  def xml(xmlDataset: Dataset[String]): DataFrame =
     parse(xmlDataset, ParseFormat.PARSE_FORMAT_UNSPECIFIED)
 
   /** @inheritdoc */

…sql/connect/DataFrameStatFunctions.scala …e/spark/sql/DataFrameStatFunctions.scalasql/connect/common/src/main/scala/org/apache/spark/sql/connect/DataFrameStatFunctions.scala renamed to connector/connect/client/jvm/src/main/scala/org/apache/spark/sql/DataFrameStatFunctions.scala sql/connect/common/src/main/scala/org/apache/spark/sql/connect/DataFrameStatFunctions.scala renamed to connector/connect/client/jvm/src/main/scala/org/apache/spark/sql/DataFrameStatFunctions.scala

@@ -15,16 +15,14 @@
  * limitations under the License.
  */
 
-package org.apache.spark.sql.connect
+package org.apache.spark.sql
 
 import java.{lang => jl, util => ju}
 
 import org.apache.spark.connect.proto.{Relation, StatSampleBy}
-import org.apache.spark.sql
-import org.apache.spark.sql.Column
+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.connect.DataFrameStatFunctions.approxQuantileResultEncoder
 import org.apache.spark.sql.functions.lit
 
 /**
@@ -33,7 +31,7 @@ import org.apache.spark.sql.functions.lit
  * @since 3.4.0
  */
 final class DataFrameStatFunctions private[sql] (protected val df: DataFrame)
-    extends sql.DataFrameStatFunctions {
+    extends api.DataFrameStatFunctions {
   private def root: Relation = df.plan.getRoot
   private val sparkSession: SparkSession = df.sparkSession