diff --git a/dataset/src/main/scala/frameless/functions/AggregateFunctions.scala b/dataset/src/main/scala/frameless/functions/AggregateFunctions.scala
index 4dae010a5..6b466b3e4 100644
--- a/dataset/src/main/scala/frameless/functions/AggregateFunctions.scala
+++ b/dataset/src/main/scala/frameless/functions/AggregateFunctions.scala
@@ -6,8 +6,6 @@ import org.apache.spark.sql.catalyst.expressions._
 import org.apache.spark.sql.{functions => sparkFunctions}
 import frameless.syntax._
 
-import scala.annotation.nowarn
-
 trait AggregateFunctions {
   /** Aggregate function: returns the number of items in a group.
     *
@@ -79,24 +77,14 @@ trait AggregateFunctions {
     *
     * apache/spark
     */
-  @deprecated("Use sum_distinct", "3.2.0")
   def sumDistinct[A, T, Out](column: TypedColumn[T, A])(
     implicit
     summable: CatalystSummable[A, Out],
     oencoder: TypedEncoder[Out],
     aencoder: TypedEncoder[A]
-  ): TypedAggregate[T, Out] = sum_distinct(column)
-
-  // supress sparkFunstion.sumDistinct call which is used to maintain Spark 3.1.x backwards compat
-  @nowarn
-  def sum_distinct[A, T, Out](column: TypedColumn[T, A])(
-    implicit
-    summable: CatalystSummable[A, Out],
-    oencoder: TypedEncoder[Out],
-    aencoder: TypedEncoder[A]
   ): TypedAggregate[T, Out] = {
     val zeroExpr = Literal.create(summable.zero, TypedEncoder[A].catalystRepr)
-    val sumExpr = expr(sparkFunctions.sumDistinct(column.untyped))
+    val sumExpr = expr(sparkFunctions.sum_distinct(column.untyped))
     val sumOrZero = Coalesce(Seq(sumExpr, zeroExpr))
 
     new TypedAggregate[T, Out](sumOrZero)
diff --git a/dataset/src/main/scala/frameless/functions/NonAggregateFunctions.scala b/dataset/src/main/scala/frameless/functions/NonAggregateFunctions.scala
index 478efdbb6..fc0597d42 100644
--- a/dataset/src/main/scala/frameless/functions/NonAggregateFunctions.scala
+++ b/dataset/src/main/scala/frameless/functions/NonAggregateFunctions.scala
@@ -3,7 +3,6 @@ package functions
 
 import org.apache.spark.sql.{Column, functions => sparkFunctions}
 
-import scala.annotation.nowarn
 import scala.util.matching.Regex
 
 trait NonAggregateFunctions {
@@ -87,61 +86,34 @@ trait NonAggregateFunctions {
     *
     * apache/spark
     */
-  @deprecated("Use shiftrightunsigned", "3.2.0")
   def shiftRightUnsigned[A, B, T](column: AbstractTypedColumn[T, A], numBits: Int)
-    (implicit
-      i0: CatalystBitShift[A, B],
-      i1: TypedEncoder[B]
-    ): column.ThisType[T, B] = shiftrightunsigned(column, numBits)
-
-  // supress sparkFunstion.shiftRightUnsigned call which is used to maintain Spark 3.1.x backwards compat
-  @nowarn
-  def shiftrightunsigned[A, B, T](column: AbstractTypedColumn[T, A], numBits: Int)
     (implicit
       i0: CatalystBitShift[A, B],
       i1: TypedEncoder[B]
     ): column.ThisType[T, B] =
-      column.typed(sparkFunctions.shiftRightUnsigned(column.untyped, numBits))
+      column.typed(sparkFunctions.shiftrightunsigned(column.untyped, numBits))
 
   /** Non-Aggregate function: shift the the given value numBits right. If given long, will return long else it will return an integer.
     *
     * apache/spark
     */
-  @deprecated("Use shiftright", "3.2.0")
   def shiftRight[A, B, T](column: AbstractTypedColumn[T, A], numBits: Int)
-    (implicit
-      i0: CatalystBitShift[A, B],
-      i1: TypedEncoder[B]
-    ): column.ThisType[T, B] = shiftright(column, numBits)
-
-  // supress sparkFunstion.shiftRight call which is used to maintain Spark 3.1.x backwards compat
-  @nowarn
-  def shiftright[A, B, T](column: AbstractTypedColumn[T, A], numBits: Int)
     (implicit
       i0: CatalystBitShift[A, B],
       i1: TypedEncoder[B]
     ): column.ThisType[T, B] =
-      column.typed(sparkFunctions.shiftRight(column.untyped, numBits))
+      column.typed(sparkFunctions.shiftright(column.untyped, numBits))
 
   /** Non-Aggregate function: shift the the given value numBits left. If given long, will return long else it will return an integer.
     *
     * apache/spark
     */
-  @deprecated("Use shiftleft", "3.2.0")
   def shiftLeft[A, B, T](column: AbstractTypedColumn[T, A], numBits: Int)
-    (implicit
-      i0: CatalystBitShift[A, B],
-      i1: TypedEncoder[B]
-    ): column.ThisType[T, B] = shiftleft(column, numBits)
-
-  // supress sparkFunstion.shiftLeft call which is used to maintain Spark 3.1.x backwards compat
-  @nowarn
-  def shiftleft[A, B, T](column: AbstractTypedColumn[T, A], numBits: Int)
     (implicit
       i0: CatalystBitShift[A, B],
       i1: TypedEncoder[B]
     ): column.ThisType[T, B] =
-    column.typed(sparkFunctions.shiftLeft(column.untyped, numBits))
+    column.typed(sparkFunctions.shiftleft(column.untyped, numBits))
   
   /** Non-Aggregate function: returns the absolute value of a numeric column
     *
@@ -519,14 +491,8 @@ trait NonAggregateFunctions {
     *
     * apache/spark
     */
-  @deprecated("Use bitwise_not", "3.2.0")
   def bitwiseNOT[A: CatalystBitwise, T](column: AbstractTypedColumn[T, A]): column.ThisType[T, A] =
-    bitwise_not(column)
-
-  // supress sparkFunstion.bitwiseNOT call which is used to maintain Spark 3.1.x backwards compat
-  @nowarn
-  def bitwise_not[A: CatalystBitwise, T](column: AbstractTypedColumn[T, A]): column.ThisType[T, A] =
-    column.typed(sparkFunctions.bitwiseNOT(column.untyped))(column.uencoder)
+    column.typed(sparkFunctions.bitwise_not(column.untyped))(column.uencoder)
 
   /** Non-Aggregate function: file name of the current Spark task. Empty string if row did not originate from
     * a file
diff --git a/dataset/src/test/scala/frameless/functions/AggregateFunctionsTests.scala b/dataset/src/test/scala/frameless/functions/AggregateFunctionsTests.scala
index 64f5b3445..8a5479eb6 100644
--- a/dataset/src/test/scala/frameless/functions/AggregateFunctionsTests.scala
+++ b/dataset/src/test/scala/frameless/functions/AggregateFunctionsTests.scala
@@ -57,7 +57,7 @@ class AggregateFunctionsTests extends TypedDatasetSuite {
     check(sparkSchema[Short, Long](sum))
   }
 
-  test("sum_distinct") {
+  test("sumDistinct") {
     case class Sum4Tests[A, B](sum: Seq[A] => B)
 
     def prop[A: TypedEncoder, Out: TypedEncoder : Numeric](xs: List[A])(
@@ -68,7 +68,7 @@ class AggregateFunctionsTests extends TypedDatasetSuite {
       val dataset = TypedDataset.create(xs.map(X1(_)))
       val A = dataset.col[A]('a)
 
-      val datasetSum: List[Out] = dataset.agg(sum_distinct(A)).collect().run().toList
+      val datasetSum: List[Out] = dataset.agg(sumDistinct(A)).collect().run().toList
 
       datasetSum match {
         case x :: Nil => approximatelyEqual(summer.sum(xs), x)
diff --git a/dataset/src/test/scala/frameless/functions/NonAggregateFunctionsTests.scala b/dataset/src/test/scala/frameless/functions/NonAggregateFunctionsTests.scala
index 8205871c2..7f8528e39 100644
--- a/dataset/src/test/scala/frameless/functions/NonAggregateFunctionsTests.scala
+++ b/dataset/src/test/scala/frameless/functions/NonAggregateFunctionsTests.scala
@@ -176,7 +176,7 @@ class NonAggregateFunctionsTests extends TypedDatasetSuite {
     res ?= resCompare
   }
 
-  test("shiftrightunsigned") {
+  test("shiftRightUnsigned") {
     val spark = session
     import spark.implicits._
 
@@ -184,7 +184,7 @@ class NonAggregateFunctionsTests extends TypedDatasetSuite {
     (values: List[X1[A]], numBits: Int)
     (implicit catalystBitShift: CatalystBitShift[A, B], encX1: Encoder[X1[A]]) = {
       val typedDS = TypedDataset.create(values)
-      propBitShift(typedDS)(shiftrightunsigned(typedDS('a), numBits), sparkFunctions.shiftrightunsigned, numBits)
+      propBitShift(typedDS)(shiftRightUnsigned(typedDS('a), numBits), sparkFunctions.shiftrightunsigned, numBits)
     }
 
     check(forAll(prop[Byte, Int] _))
@@ -194,7 +194,7 @@ class NonAggregateFunctionsTests extends TypedDatasetSuite {
     check(forAll(prop[BigDecimal, Int] _))
   }
 
-  test("shiftright") {
+  test("shiftRight") {
     val spark = session
     import spark.implicits._
 
@@ -202,7 +202,7 @@ class NonAggregateFunctionsTests extends TypedDatasetSuite {
     (values: List[X1[A]], numBits: Int)
     (implicit catalystBitShift: CatalystBitShift[A, B], encX1: Encoder[X1[A]]) = {
       val typedDS = TypedDataset.create(values)
-      propBitShift(typedDS)(shiftright(typedDS('a), numBits), sparkFunctions.shiftright, numBits)
+      propBitShift(typedDS)(shiftRight(typedDS('a), numBits), sparkFunctions.shiftright, numBits)
     }
 
     check(forAll(prop[Byte, Int] _))
@@ -212,7 +212,7 @@ class NonAggregateFunctionsTests extends TypedDatasetSuite {
     check(forAll(prop[BigDecimal, Int] _))
   }
 
-  test("shiftleft") {
+  test("shiftLeft") {
     val spark = session
     import spark.implicits._
 
@@ -220,7 +220,7 @@ class NonAggregateFunctionsTests extends TypedDatasetSuite {
     (values: List[X1[A]], numBits: Int)
     (implicit catalystBitShift: CatalystBitShift[A, B], encX1: Encoder[X1[A]]) = {
       val typedDS = TypedDataset.create(values)
-      propBitShift(typedDS)(shiftleft(typedDS('a), numBits), sparkFunctions.shiftleft, numBits)
+      propBitShift(typedDS)(shiftLeft(typedDS('a), numBits), sparkFunctions.shiftleft, numBits)
     }
 
     check(forAll(prop[Byte, Int] _))
@@ -1648,7 +1648,7 @@ class NonAggregateFunctionsTests extends TypedDatasetSuite {
     check(forAll(prop _))
   }
 
-  test("bitwise_not"){
+  test("bitwiseNOT"){
     val spark = session
     import spark.implicits._
 
@@ -1656,13 +1656,13 @@ class NonAggregateFunctionsTests extends TypedDatasetSuite {
     (values:List[X1[A]])(implicit encX1:Encoder[X1[A]]) = {
       val cDS = session.createDataset(values)
       val resCompare = cDS
-        .select(sparkFunctions.bitwise_not(cDS("a")))
+        .select(sparkFunctions.bitwiseNOT(cDS("a")))
         .map(_.getAs[A](0))
         .collect().toList
 
       val typedDS = TypedDataset.create(values)
       val res = typedDS
-        .select(bitwise_not(typedDS('a)))
+        .select(bitwiseNOT(typedDS('a)))
         .collect()
         .run()
         .toList