[GitHub] cloud-fan commented on a change in pull request #23778: [SPARK-24935][SQL] : Problem with Executing Hive UDF's from Spark 2.2 Onwards

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cloud-fan commented on a change in pull request #23778: [SPARK-24935][SQL] : Problem with Executing Hive UDF's from Spark 2.2 Onwards
URL: https://github.com/apache/spark/pull/23778#discussion_r259873144
 
 

 ##########
 File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/interfaces.scala
 ##########
 @@ -524,23 +524,142 @@ abstract class TypedImperativeAggregate[T] extends ImperativeAggregate {
   /** De-serializes the serialized format Array[Byte], and produces aggregation buffer object T */
   def deserialize(storageFormat: Array[Byte]): T
 
+  override def initialize(buffer: InternalRow): Unit = {
+    buffer(mutableAggBufferOffset) = createAggregationBuffer()
+  }
+
+  override def update(buffer: InternalRow, input: InternalRow): Unit = {
+    buffer(mutableAggBufferOffset) = update(getBufferObject(buffer), input)
+  }
+
+  override def merge(buffer: InternalRow, inputBuffer: InternalRow): Unit = {
+    val bufferObject = getBufferObject(buffer)
+    // The inputBuffer stores serialized aggregation buffer object produced by partial aggregate
+    val inputObject = deserialize(inputBuffer.getBinary(inputAggBufferOffset))
+    buffer(mutableAggBufferOffset) = merge(bufferObject, inputObject)
+  }
+
+  override def eval(buffer: InternalRow): Any = {
+    eval(getBufferObject(buffer))
+  }
+
+  private[this] val anyObjectType = ObjectType(classOf[AnyRef])
+  private def getBufferObject(bufferRow: InternalRow): T = {
+    bufferRow.get(mutableAggBufferOffset, anyObjectType).asInstanceOf[T]
+  }
+
+  override lazy val aggBufferAttributes: Seq[AttributeReference] = {
+    // Underlying storage type for the aggregation buffer object
+    Seq(AttributeReference("buf", BinaryType)())
+  }
+
+  override lazy val inputAggBufferAttributes: Seq[AttributeReference] =
+    aggBufferAttributes.map(_.newInstance())
+
+  override def aggBufferSchema: StructType = StructType.fromAttributes(aggBufferAttributes)
+
+  /**
+   * In-place replaces the aggregation buffer object stored at buffer's index
+   * `mutableAggBufferOffset`, with SparkSQL internally supported underlying storage format
+   * (BinaryType).
+   *
+   * This is only called when doing Partial or PartialMerge mode aggregation, before the framework
+   * shuffle out aggregate buffers.
+   */
+  def serializeAggregateBufferInPlace(buffer: InternalRow): Unit = {
+    buffer(mutableAggBufferOffset) = serialize(getBufferObject(buffer))
+  }
+}
+
+/**
+ * Aggregation function which allows **arbitrary** user-defined java object to be used as internal
+ * aggregation buffer for Hive.
+ */
+abstract class HiveTypedImperativeAggregate[T] extends TypedImperativeAggregate[T] {
+
+  /**
+   * Creates an empty aggregation buffer object for partial 1 mode. This is called
+   * before processing each key group(group by key).
+   *
+   * @return an aggregation buffer object
+   */
+  def createAggregationBuffer(): T
+
+  /**
+   * Creates an empty aggregation buffer object for partial 2 mode.
+   *
+   * @return an aggregation buffer object
+   */
+  def createPartial2ModeAggregationBuffer(): T
+
+  var partial2ModeBuffer: InternalRow = _
+
+  /**
+   * Updates the aggregation buffer object with an input row and returns a new buffer object. For
+   * performance, the function may do in-place update and return it instead of constructing new
+   * buffer object.
+   *
+   * This is typically called when doing Partial or Complete mode aggregation.
+   *
+   * @param buffer The aggregation buffer object.
+   * @param input an input row
+   */
+  def update(buffer: T, input: InternalRow): T
+
+  /**
+   * Merges an input aggregation object into aggregation buffer object and returns a new buffer
+   * object. For performance, the function may do in-place merge and return it instead of
+   * constructing new buffer object.
+   *
+   * This is typically called when doing PartialMerge or Final mode aggregation.
+   *
+   * @param buffer the aggregation buffer object used to store the aggregation result.
+   * @param input an input aggregation object. Input aggregation object can be produced by
+   *              de-serializing the partial aggregate's output from Mapper side.
+   */
+  def merge(buffer: T, input: T): T
+
+  /**
+   * Generates the final aggregation result value for current key group with the aggregation buffer
+   * object.
+   *
+   * Developer note: the only return types accepted by Spark are:
+   *   - primitive types
+   *   - InternalRow and subclasses
+   *   - ArrayData
+   *   - MapData
+   *
+   * @param buffer aggregation buffer object.
+   * @return The aggregation result of current key group
+   */
+  def eval(buffer: T): Any
+
+  /** Serializes the aggregation buffer object T to Array[Byte] */
+  def serialize(buffer: T): Array[Byte]
+
+  /** De-serializes the serialized format Array[Byte], and produces aggregation buffer object T */
+  def deserialize(storageFormat: Array[Byte]): T
+
   final override def initialize(buffer: InternalRow): Unit = {
+    partial2ModeBuffer = buffer.copy()
+    partial2ModeBuffer(mutableAggBufferOffset) = createPartial2ModeAggregationBuffer()
 
 Review comment:
   I'm a little lost here. So this `HiveTypedImperativeAggregate` has 2 buffers? What's the difference between `partial2ModeBuffer` and `buffer`?

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