cboumalh commented on code in PR #52883: URL: https://github.com/apache/spark/pull/52883#discussion_r2627592603
########## sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/tuplesketchesAggregates.scala: ########## @@ -0,0 +1,1895 @@ +/* + * 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.catalyst.expressions.aggregate + +import org.apache.datasketches.memory.Memory +import org.apache.datasketches.tuple.{Intersection, Sketch, Sketches, Summary, SummaryFactory, SummarySetOperations, Union, UpdatableSketch, UpdatableSketchBuilder, UpdatableSummary} +import org.apache.datasketches.tuple.adouble.{DoubleSummary, DoubleSummaryDeserializer, DoubleSummaryFactory, DoubleSummarySetOperations} +import org.apache.datasketches.tuple.aninteger.{IntegerSummary, IntegerSummaryDeserializer, IntegerSummaryFactory, IntegerSummarySetOperations} +import org.apache.datasketches.tuple.strings.{ArrayOfStringsSummary, ArrayOfStringsSummaryDeserializer, ArrayOfStringsSummaryFactory, ArrayOfStringsSummarySetOperations} + +import org.apache.spark.SparkUnsupportedOperationException +import org.apache.spark.sql.catalyst.InternalRow +import org.apache.spark.sql.catalyst.analysis.{ExpressionBuilder, TypeCheckResult} +import org.apache.spark.sql.catalyst.analysis.TypeCheckResult.DataTypeMismatch +import org.apache.spark.sql.catalyst.expressions.{ExpectsInputTypes, Expression, ExpressionDescription, Literal} +import org.apache.spark.sql.catalyst.expressions.aggregate.TypedImperativeAggregate +import org.apache.spark.sql.catalyst.plans.logical.{FunctionSignature, InputParameter} +import org.apache.spark.sql.catalyst.trees.{BinaryLike, QuaternaryLike, TernaryLike, UnaryLike} +import org.apache.spark.sql.catalyst.util.{ArrayData, CollationFactory, ThetaSketchUtils} +import org.apache.spark.sql.errors.QueryExecutionErrors +import org.apache.spark.sql.internal.types.StringTypeWithCollation +import org.apache.spark.sql.types.{AbstractDataType, ArrayType, BinaryType, DataType, DoubleType, FloatType, IntegerType, LongType, StringType, TypeCollection} +import org.apache.spark.unsafe.types.UTF8String + +sealed trait TupleSketchState[S <: Summary] { + def serialize(): Array[Byte] + def eval(): Array[Byte] +} +case class UpdatableTupleSketchBuffer[U, S <: UpdatableSummary[U]](sketch: UpdatableSketch[U, S]) + extends TupleSketchState[S] { + override def serialize(): Array[Byte] = sketch.compact.toByteArray + override def eval(): Array[Byte] = sketch.compact.toByteArray + + /** Returns compact form of the sketch, needed for merge operations that require Sketch type. */ + def compactSketch: Sketch[S] = sketch.compact +} +case class UnionTupleAggregationBuffer[S <: Summary](union: Union[S]) + extends TupleSketchState[S] { + override def serialize(): Array[Byte] = union.getResult.toByteArray + override def eval(): Array[Byte] = union.getResult.toByteArray +} +case class IntersectionTupleAggregationBuffer[S <: Summary](intersection: Intersection[S]) + extends TupleSketchState[S] { + override def serialize(): Array[Byte] = intersection.getResult.toByteArray + override def eval(): Array[Byte] = intersection.getResult.toByteArray +} +case class FinalizedTupleSketch[S <: Summary](sketch: Sketch[S]) extends TupleSketchState[S] { + override def serialize(): Array[Byte] = sketch.toByteArray + override def eval(): Array[Byte] = sketch.toByteArray +} + +/** + * The TupleSketchAggDouble function utilizes a Datasketches TupleSketch instance to count a + * probabilistic approximation of the number of unique values in a given column with associated + * double type summary values, and outputs the binary representation of the TupleSketch. + * + * See [[https://datasketches.apache.org/docs/Tuple/TupleSketches.html]] for more information. + * + * @param key + * key expression against which unique counting will occur + * @param summary + * summary expression (double type) against which different mode aggregations will occur + * @param lgNomEntries + * the log-base-2 of nomEntries decides the number of buckets for the sketch + * @param mode + * the aggregation mode for numeric summaries (sum, min, max, alwaysone) + * @param mutableAggBufferOffset + * offset for mutable aggregation buffer + * @param inputAggBufferOffset + * offset for input aggregation buffer + */ +case class TupleSketchAggDouble( + key: Expression, + summary: Expression, + lgNomEntries: Expression, + mode: Expression, + override val mutableAggBufferOffset: Int, + override val inputAggBufferOffset: Int) + extends TupleSketchAggBase[java.lang.Double, DoubleSummary] + with QuaternaryLike[Expression] + with SummaryAggregateMode { + + // Constructors + def this(key: Expression, summary: Expression) = { + this( + key, + summary, + Literal(ThetaSketchUtils.DEFAULT_LG_NOM_LONGS), + Literal(ThetaSketchUtils.MODE_SUM), + 0, + 0) + } + + def this(key: Expression, summary: Expression, lgNomEntries: Expression) = { + this(key, summary, lgNomEntries, Literal(ThetaSketchUtils.MODE_SUM), 0, 0) + } + + def this(key: Expression, summary: Expression, lgNomEntries: Expression, mode: Expression) = { + this(key, summary, lgNomEntries, mode, 0, 0) + } + + /** + * Override inputTypes to specify key, summary (double/float), lgNomEntries (int), and mode + * (string) parameters. + */ + override def inputTypes: Seq[AbstractDataType] = + Seq( + keyInputTypes, + summaryInputType, + IntegerType, + StringTypeWithCollation(supportsTrimCollation = true)) + + /** + * Override checkInputDataTypes to validate base inputs (key, summary, lgNomEntries) and mode + * parameter. + */ + override def checkInputDataTypes(): TypeCheckResult = { + val defaultCheck = checkBaseInputDataTypes() + if (defaultCheck.isFailure) return defaultCheck + + checkModeParameter() + } + + // Copy constructors required by ImperativeAggregate + override def withNewMutableAggBufferOffset( + newMutableAggBufferOffset: Int): TupleSketchAggDouble = + copy(mutableAggBufferOffset = newMutableAggBufferOffset) + + override def withNewInputAggBufferOffset(newInputAggBufferOffset: Int): TupleSketchAggDouble = + copy(inputAggBufferOffset = newInputAggBufferOffset) + + override protected def withNewChildrenInternal( + newFirst: Expression, + newSecond: Expression, + newThird: Expression, + newFourth: Expression): TupleSketchAggDouble = + copy(key = newFirst, summary = newSecond, lgNomEntries = newThird, mode = newFourth) + + override def first: Expression = key + override def second: Expression = summary + override def third: Expression = lgNomEntries + override def fourth: Expression = mode + + // Overrides for TypedImperativeAggregate + override def prettyName: String = "tuple_sketch_agg_double" + + /** Specifies accepted summary input types (double and float). */ + override protected def summaryInputType: AbstractDataType = + TypeCollection(DoubleType, FloatType) + + /** + * Creates a DoubleSummaryFactory with the configured aggregation mode. + * + * @return + * a DoubleSummaryFactory instance configured with the aggregation mode + */ + override protected def createSummaryFactory(): SummaryFactory[DoubleSummary] = { + val mode = ThetaSketchUtils.getDoubleSummaryMode(modeInput) + new DoubleSummaryFactory(mode) + } + + /** + * Creates DoubleSummarySetOperations for merge operations with the configured mode. + * + * @return + * a DoubleSummarySetOperations instance configured with the aggregation mode + */ + override protected def createSummarySetOperations(): SummarySetOperations[DoubleSummary] = { + val mode = ThetaSketchUtils.getDoubleSummaryMode(modeInput) + new DoubleSummarySetOperations(mode) + } + + /** + * Converts Float inputs to Double, ensuring compatibility with DoubleSummary. + * + * @param input + * the input value to normalize (Float or Double) + * @return + * the normalized Double value + */ + override protected def normalizeSummaryValue(input: Any): java.lang.Double = { + input match { + case d: Double => d + case f: Float => f.toDouble + case _ => + val actualType = input.getClass.getSimpleName + throw QueryExecutionErrors.tupleInvalidSummaryValueType(prettyName, actualType) + } + } + + /** + * Heapify a CompactSketch from the sketch byte array. + * + * @param buffer + * A serialized sketch byte array + * @return + * A CompactSketch instance wrapped with FinalizedTupleSketch + */ + override def deserialize(buffer: Array[Byte]): TupleSketchState[DoubleSummary] = { + if (buffer.nonEmpty) { + FinalizedTupleSketch( + Sketches.heapifySketch(Memory.wrap(buffer), new DoubleSummaryDeserializer())) + } else { + this.createAggregationBuffer() + } + } +} + +/** + * The TupleSketchAggInteger function utilizes a Datasketches TupleSketch instance to count a + * probabilistic approximation of the number of unique values in a given column with associated + * integer type summary values, and outputs the binary representation of the TupleSketch. + * + * See [[https://datasketches.apache.org/docs/Tuple/TupleSketches.html]] for more information. + * + * @param key + * key expression against which unique counting will occur + * @param summary + * summary expression (integer type) against which different mode aggregations will occur + * @param lgNomEntries + * the log-base-2 of nomEntries decides the number of buckets for the sketch + * @param mode + * the aggregation mode for numeric summaries (sum, min, max, alwaysone) + * @param mutableAggBufferOffset + * offset for mutable aggregation buffer + * @param inputAggBufferOffset + * offset for input aggregation buffer + */ +case class TupleSketchAggInteger( + key: Expression, + summary: Expression, + lgNomEntries: Expression, + mode: Expression, + override val mutableAggBufferOffset: Int, + override val inputAggBufferOffset: Int) + extends TupleSketchAggBase[Integer, IntegerSummary] + with QuaternaryLike[Expression] + with SummaryAggregateMode { + + // Constructors + def this(key: Expression, summary: Expression) = { + this( + key, + summary, + Literal(ThetaSketchUtils.DEFAULT_LG_NOM_LONGS), + Literal(ThetaSketchUtils.MODE_SUM), + 0, + 0) + } + + def this(key: Expression, summary: Expression, lgNomEntries: Expression) = { + this(key, summary, lgNomEntries, Literal(ThetaSketchUtils.MODE_SUM), 0, 0) + } + + def this(key: Expression, summary: Expression, lgNomEntries: Expression, mode: Expression) = { + this(key, summary, lgNomEntries, mode, 0, 0) + } + + /** + * Override inputTypes to specify key, summary (integer), lgNomEntries (int), and mode (string) + * parameters. + */ + override def inputTypes: Seq[AbstractDataType] = + Seq( + keyInputTypes, + summaryInputType, + IntegerType, + StringTypeWithCollation(supportsTrimCollation = true)) + + /** + * Override checkInputDataTypes to validate base inputs (key, summary, lgNomEntries) and mode + * parameter. + */ + override def checkInputDataTypes(): TypeCheckResult = { + val defaultCheck = checkBaseInputDataTypes() + if (defaultCheck.isFailure) return defaultCheck + + checkModeParameter() + } + + // Copy constructors required by ImperativeAggregate + override def withNewMutableAggBufferOffset( + newMutableAggBufferOffset: Int): TupleSketchAggInteger = + copy(mutableAggBufferOffset = newMutableAggBufferOffset) + + override def withNewInputAggBufferOffset(newInputAggBufferOffset: Int): TupleSketchAggInteger = + copy(inputAggBufferOffset = newInputAggBufferOffset) + + override protected def withNewChildrenInternal( + newFirst: Expression, + newSecond: Expression, + newThird: Expression, + newFourth: Expression): TupleSketchAggInteger = + copy(key = newFirst, summary = newSecond, lgNomEntries = newThird, mode = newFourth) + + override def first: Expression = key + override def second: Expression = summary + override def third: Expression = lgNomEntries + override def fourth: Expression = mode + + // Overrides for TypedImperativeAggregate + override def prettyName: String = "tuple_sketch_agg_integer" + + /** Specifies accepted summary input types (integer). */ + override protected def summaryInputType: AbstractDataType = + IntegerType + + /** + * Creates an IntegerSummaryFactory with the configured aggregation mode. + * + * @return + * an IntegerSummaryFactory instance configured with the aggregation mode + */ + override protected def createSummaryFactory(): SummaryFactory[IntegerSummary] = { + val mode = ThetaSketchUtils.getIntegerSummaryMode(modeInput) + new IntegerSummaryFactory(mode) + } + + /** + * Creates IntegerSummarySetOperations for merge operations with the configured mode. + * + * @return + * an IntegerSummarySetOperations instance configured with the aggregation mode + */ + override protected def createSummarySetOperations(): SummarySetOperations[IntegerSummary] = { + val mode = ThetaSketchUtils.getIntegerSummaryMode(modeInput) + new IntegerSummarySetOperations(mode, mode) + } + + /** + * Ensures compatibility with IntegerSummary. + * + * @param input + * the input value to normalize (Integer) + * @return + * the normalized Integer value + */ + override protected def normalizeSummaryValue(input: Any): Integer = { + input match { + case i: Int => i + case _ => + val actualType = input.getClass.getSimpleName + throw QueryExecutionErrors.tupleInvalidSummaryValueType(prettyName, actualType) + } + } + + /** + * Heapify a CompactSketch from the sketch byte array. + * + * @param buffer + * A serialized sketch byte array + * @return + * A CompactSketch instance wrapped with FinalizedTupleSketch + */ + override def deserialize(buffer: Array[Byte]): TupleSketchState[IntegerSummary] = { + if (buffer.nonEmpty) { + FinalizedTupleSketch( + Sketches.heapifySketch(Memory.wrap(buffer), new IntegerSummaryDeserializer())) + } else { + this.createAggregationBuffer() + } + } +} + +/** + * The TupleSketchAggString function utilizes a Datasketches TupleSketch instance to count a + * probabilistic approximation of the number of unique values in a given column with associated + * string or string array type summary values, and outputs the binary representation of the + * TupleSketch. + * + * See [[https://datasketches.apache.org/docs/Tuple/TupleSketches.html]] for more information. + * + * @param key + * key expression against which unique counting will occur + * @param summary + * summary expression (string or array of strings) to be collected + * @param lgNomEntries + * the log-base-2 of nomEntries decides the number of buckets for the sketch + * @param mutableAggBufferOffset + * offset for mutable aggregation buffer + * @param inputAggBufferOffset + * offset for input aggregation buffer + */ +// scalastyle:off line.size.limit +@ExpressionDescription( + usage = """ + _FUNC_(key, summary, lgNomEntries) - Returns the TupleSketch compact binary representation. + `key` is the expression for unique value counting. + `summary` is the string or array of strings to be collected. + `lgNomEntries` is the log-base-2 of nominal entries, with nominal entries deciding + the number buckets or slots for the TupleSketch. Default is 12. """, + examples = """ + Examples: + > SELECT tuple_sketch_estimate_string(_FUNC_(key, summary, 12)) FROM VALUES (1, 'a'), (1, 'b'), (2, 'c'), (2, 'd'), (3, 'e') tab(key, summary); + 3.0 + """, + group = "agg_funcs", + since = "4.2.0") +// scalastyle:on line.size.limit +case class TupleSketchAggString( + key: Expression, + summary: Expression, + lgNomEntries: Expression, + override val mutableAggBufferOffset: Int, + override val inputAggBufferOffset: Int) + extends TupleSketchAggBase[Array[String], ArrayOfStringsSummary] + with TernaryLike[Expression] { + + // Constructors + def this(key: Expression, summary: Expression) = { + this(key, summary, Literal(ThetaSketchUtils.DEFAULT_LG_NOM_LONGS), 0, 0) + } + + def this(key: Expression, summary: Expression, lgNomEntries: Expression) = { + this(key, summary, lgNomEntries, 0, 0) + } + + /** + * Override inputTypes to specify key, summary (string or array of strings), and lgNomEntries + * (int) parameters. + */ + override def inputTypes: Seq[AbstractDataType] = + Seq(keyInputTypes, summaryInputType, IntegerType) + + /** + * Override checkInputDataTypes to validate base inputs (key, summary, lgNomEntries) only. + */ + override def checkInputDataTypes(): TypeCheckResult = checkBaseInputDataTypes() + + // Copy constructors required by ImperativeAggregate + override def withNewMutableAggBufferOffset( + newMutableAggBufferOffset: Int): TupleSketchAggString = + copy(mutableAggBufferOffset = newMutableAggBufferOffset) + + override def withNewInputAggBufferOffset(newInputAggBufferOffset: Int): TupleSketchAggString = + copy(inputAggBufferOffset = newInputAggBufferOffset) + + override protected def withNewChildrenInternal( + newFirst: Expression, + newSecond: Expression, + newThird: Expression): TupleSketchAggString = + copy(key = newFirst, summary = newSecond, lgNomEntries = newThird) + + override def first: Expression = key + override def second: Expression = summary + override def third: Expression = lgNomEntries + + // Overrides for TypedImperativeAggregate + override def prettyName: String = "tuple_sketch_agg_string" + + /** Specifies accepted summary input types (string or array of strings). */ + override protected def summaryInputType: AbstractDataType = + TypeCollection(StringTypeWithCollation(supportsTrimCollation = true), ArrayType(StringType)) + + /** + * Creates an ArrayOfStringsSummaryFactory. Aggregation mode is not supported here. + * + * @return + * an ArrayOfStringsSummaryFactory instance + */ + override protected def createSummaryFactory(): SummaryFactory[ArrayOfStringsSummary] = { + new ArrayOfStringsSummaryFactory() + } + + /** + * Creates ArrayOfStringsSummarySetOperations for merge operations. Aggregation mode is not + * supported here. + * + * @return + * an ArrayOfStringsSummarySetOperations instance + */ + override protected def createSummarySetOperations() + : SummarySetOperations[ArrayOfStringsSummary] = { + new ArrayOfStringsSummarySetOperations() + } + + /** + * Converts String inputs to String Arrays, ensuring compatibility with ArrayOfStringsSummary. + * + * @param input + * the input value to normalize (UTF8String or ArrayData) + * @return + * the normalized Array[String] value + */ + override protected def normalizeSummaryValue(input: Any): Array[String] = { + input match { + case str: UTF8String => + Array(str.toString) + case arr: ArrayData => + (0 until arr.numElements()) + .filter(i => !arr.isNullAt(i)) + .map(i => arr.getUTF8String(i).toString) + .toArray + case _ => + val actualType = input.getClass.getSimpleName + throw QueryExecutionErrors.tupleInvalidSummaryValueType(prettyName, actualType) + } + } + + /** + * Heapify a CompactSketch from the sketch byte array. + * + * @param buffer + * A serialized sketch byte array + * @return + * A CompactSketch instance wrapped with FinalizedTupleSketch + */ + override def deserialize(buffer: Array[Byte]): TupleSketchState[ArrayOfStringsSummary] = { + if (buffer.nonEmpty) { + FinalizedTupleSketch( + Sketches.heapifySketch(Memory.wrap(buffer), new ArrayOfStringsSummaryDeserializer())) + } else { + this.createAggregationBuffer() + } + } +} + +abstract class TupleSketchAggBase[U, S <: UpdatableSummary[U]] + extends TypedImperativeAggregate[TupleSketchState[S]] + with SketchSize + with ExpectsInputTypes { + + // Abstract methods that subclasses must implement + protected def summaryInputType: AbstractDataType + protected def normalizeSummaryValue(input: Any): U + protected def createSummaryFactory(): SummaryFactory[S] + protected def createSummarySetOperations(): SummarySetOperations[S] + + // Abstract members that subclasses must implement + protected def key: Expression + protected def summary: Expression + + protected final val keyInputTypes: AbstractDataType = + TypeCollection( + ArrayType(IntegerType), + ArrayType(LongType), + BinaryType, + DoubleType, + FloatType, + IntegerType, + LongType, + StringTypeWithCollation(supportsTrimCollation = true)) + + override def dataType: DataType = BinaryType + override def nullable: Boolean = false + + protected def checkBaseInputDataTypes(): TypeCheckResult = { + val defaultCheck = super.checkInputDataTypes() + if (defaultCheck.isFailure) return defaultCheck + + checkLgNomEntriesParameter() + } + + /** + * Instantiate an UpdatableSketch instance using the lgNomEntries param and summary factory. + * + * @return + * an UpdatableSketch instance wrapped with UpdatableTupleSketchBuffer + */ + override def createAggregationBuffer(): TupleSketchState[S] = { + val factory = createSummaryFactory() + val builder = new UpdatableSketchBuilder[U, S](factory) + builder.setNominalEntries(1 << lgNomEntriesInput) + val sketch = builder.build() + UpdatableTupleSketchBuffer(sketch) + } + + /** + * Evaluate the input row and update the UpdatableSketch instance with the row's key and summary + * value. The update function only supports a subset of Spark SQL types, and an exception will + * be thrown for unsupported types. Notes: + * - Null values are ignored. + * - Empty byte arrays are ignored + * - Empty arrays of supported element types are ignored + * - Strings that are collation-equal to the empty string are ignored. + * + * @param updateBuffer + * A previously initialized UpdatableSketch instance + * @param input + * An input row + */ + override def update( + updateBuffer: TupleSketchState[S], + input: InternalRow): TupleSketchState[S] = { + val keyValue = key.eval(input) + val summaryValue = summary.eval(input) + + // Return early for null values. + if (keyValue == null || summaryValue == null) return updateBuffer + + /** + * Normalize summary to a datasketch supported type if possible. Type checking is already done + * at this point. + */ + val normalizedSummary = normalizeSummaryValue(summaryValue) + + // Initialized buffer should be UpdatableTupleSketchBuffer, else error out. + val sketch = updateBuffer match { + case UpdatableTupleSketchBuffer(s) => s + case _ => throw QueryExecutionErrors.tupleInvalidInputSketchBuffer(prettyName) + } + + key.dataType match { + case ArrayType(IntegerType, _) => + val arr = keyValue.asInstanceOf[ArrayData].toIntArray() + sketch.update(arr, normalizedSummary) + case ArrayType(LongType, _) => + val arr = keyValue.asInstanceOf[ArrayData].toLongArray() + sketch.update(arr, normalizedSummary) + case BinaryType => + val bytes = keyValue.asInstanceOf[Array[Byte]] + sketch.update(bytes, normalizedSummary) + case DoubleType => + sketch.update(keyValue.asInstanceOf[Double], normalizedSummary) + case FloatType => + sketch.update(keyValue.asInstanceOf[Float].toDouble, normalizedSummary) + case IntegerType => + sketch.update(keyValue.asInstanceOf[Int].toLong, normalizedSummary) + case LongType => + sketch.update(keyValue.asInstanceOf[Long], normalizedSummary) + case st: StringType => + val collation = CollationFactory.fetchCollation(st.collationId) + val str = keyValue.asInstanceOf[UTF8String] + if (!collation.equalsFunction(str, UTF8String.EMPTY_UTF8)) { + sketch.update(collation.sortKeyFunction.apply(str), normalizedSummary) + } + case _ => + throw new SparkUnsupportedOperationException( + errorClass = "_LEGACY_ERROR_TEMP_3121", + messageParameters = Map("dataType" -> key.dataType.toString)) + } + + updateBuffer + } + + /** + * Merges an input CompactSketch into the UpdatableSketch which is acting as the aggregation + * buffer. + * + * @param updateBuffer + * The UpdatableSketch or Union instance used to store the aggregation result + * @param input + * An input UpdatableSketch, Union, or CompactSketch instance + */ + override def merge( + updateBuffer: TupleSketchState[S], + input: TupleSketchState[S]): TupleSketchState[S] = { + + def createUnionWith( + sketch1: Sketch[S], + sketch2: Sketch[S]): UnionTupleAggregationBuffer[S] = { + val summarySetOps = createSummarySetOperations() + val union = new Union[S](1 << lgNomEntriesInput, summarySetOps) + union.union(sketch1) + union.union(sketch2) + UnionTupleAggregationBuffer(union) + } + + (updateBuffer, input) match { + case (UnionTupleAggregationBuffer(union), buffer: UpdatableTupleSketchBuffer[_, S]) => + union.union(buffer.compactSketch) + UnionTupleAggregationBuffer(union) + + case (UnionTupleAggregationBuffer(union), FinalizedTupleSketch(sketch)) => + union.union(sketch) + UnionTupleAggregationBuffer(union) + + case (UnionTupleAggregationBuffer(union1), UnionTupleAggregationBuffer(union2)) => + union1.union(union2.getResult) + UnionTupleAggregationBuffer(union1) + + case ( + buffer1: UpdatableTupleSketchBuffer[_, S], + buffer2: UpdatableTupleSketchBuffer[_, S]) => + createUnionWith(buffer1.compactSketch, buffer2.compactSketch) + + case (buffer: UpdatableTupleSketchBuffer[_, S], FinalizedTupleSketch(sketch)) => + createUnionWith(buffer.compactSketch, sketch) + + case _ => throw QueryExecutionErrors.tupleInvalidInputSketchBuffer(prettyName) + } + } + + /** + * Returns a CompactSketch binary derived from the input column or expression + * + * @param sketchState + * Union or UpdatableSketch instance used as an aggregation buffer + * @return + * A CompactSketch binary representation + */ + override def eval(sketchState: TupleSketchState[S]): Any = sketchState.eval() + + /** + * Returns a CompactSketch binary derived from the input column or expression + * + * @param sketchState + * Union or UpdatableSketch instance used as an aggregation buffer + * @return + * A CompactSketch binary representation + */ + override def serialize(sketchState: TupleSketchState[S]): Array[Byte] = + sketchState.serialize() +} + +/** + * The TupleUnionAggDouble function unions multiple TupleSketch binary representations with a + * double type summary to produce a single merged TupleSketch. This is useful for combining + * pre-aggregated TupleSketch results from different partitions or data sources. + * + * See [[https://datasketches.apache.org/docs/Tuple/TupleSketches.html]] for more information. + * + * @param child + * child expression (binary TupleSketch representation created with a double type summary) to be + * unioned + * @param lgNomEntries + * the log-base-2 of nomEntries decides the number of buckets for the union operation + * @param mode + * the aggregation mode for numeric summaries during union (sum, min, max, alwaysone) + * @param mutableAggBufferOffset + * offset for mutable aggregation buffer + * @param inputAggBufferOffset + * offset for input aggregation buffer + */ +case class TupleUnionAggDouble( + child: Expression, + lgNomEntries: Expression, + mode: Expression, + override val mutableAggBufferOffset: Int, + override val inputAggBufferOffset: Int) + extends TupleUnionAggBase[DoubleSummary] + with TernaryLike[Expression] + with SummaryAggregateMode { + + // Constructors + def this(child: Expression) = { + this( + child, + Literal(ThetaSketchUtils.DEFAULT_LG_NOM_LONGS), + Literal(ThetaSketchUtils.MODE_SUM), + 0, + 0) + } + + def this(child: Expression, lgNomEntries: Expression) = { + this(child, lgNomEntries, Literal(ThetaSketchUtils.MODE_SUM), 0, 0) + } + + def this(child: Expression, lgNomEntries: Expression, mode: Expression) = { + this(child, lgNomEntries, mode, 0, 0) + } + + /** + * Override inputTypes to specify sketch binary (BinaryType), lgNomEntries (int), and mode + * (string) parameters. + */ + override def inputTypes: Seq[AbstractDataType] = + Seq(BinaryType, IntegerType, StringTypeWithCollation(supportsTrimCollation = true)) + + /** + * Override checkInputDataTypes to validate base inputs (sketch binary, lgNomEntries) and mode + * parameter. + */ + override def checkInputDataTypes(): TypeCheckResult = { + val defaultCheck = checkBaseInputDataTypes() + if (defaultCheck.isFailure) return defaultCheck + + checkModeParameter() + } + + // Copy constructors required by ImperativeAggregate + override def withNewMutableAggBufferOffset( + newMutableAggBufferOffset: Int): TupleUnionAggDouble = + copy(mutableAggBufferOffset = newMutableAggBufferOffset) + + override def withNewInputAggBufferOffset(newInputAggBufferOffset: Int): TupleUnionAggDouble = + copy(inputAggBufferOffset = newInputAggBufferOffset) + + override protected def withNewChildrenInternal( + newFirst: Expression, + newSecond: Expression, + newThird: Expression): TupleUnionAggDouble = + copy(child = newFirst, lgNomEntries = newSecond, mode = newThird) + + override def first: Expression = child + override def second: Expression = lgNomEntries + override def third: Expression = mode + + // Overrides for TypedImperativeAggregate + override def prettyName: String = "tuple_union_agg_double" + + /** + * Creates DoubleSummarySetOperations for merge operations. + * + * @return + * a DoubleSummarySetOperations instance configured with the aggregation mode + */ + override protected def createSummarySetOperations(): SummarySetOperations[DoubleSummary] = { + val mode = ThetaSketchUtils.getDoubleSummaryMode(modeInput) + new DoubleSummarySetOperations(mode) + } + + /** + * Heapify a sketch from a byte array. + * + * @param buffer + * the serialized sketch byte array + * @return + * a Sketch[DoubleSummary] instance + */ + override protected def heapifySketch(buffer: Array[Byte]): Sketch[DoubleSummary] = { + ThetaSketchUtils.heapifyDoubleTupleSketch(buffer, prettyName) + } + + /** + * Heapify a CompactSketch from the sketch byte array. + * + * @param buffer + * A serialized sketch byte array + * @return + * A CompactSketch instance wrapped with FinalizedTupleSketch + */ + override def deserialize(buffer: Array[Byte]): TupleSketchState[DoubleSummary] = { + if (buffer.nonEmpty) { + FinalizedTupleSketch(heapifySketch(buffer)) + } else { + this.createAggregationBuffer() + } + } +} + +/** + * The TupleUnionAggInteger function unions multiple TupleSketch binary representations with an + * integer type summary to produce a single merged TupleSketch. This is useful for combining + * pre-aggregated TupleSketch results from different partitions or data sources. + * + * See [[https://datasketches.apache.org/docs/Tuple/TupleSketches.html]] for more information. + * + * @param child + * child expression (binary TupleSketch representation created with an integer type summary) to + * be unioned + * @param lgNomEntries + * the log-base-2 of nomEntries decides the number of buckets for the union operation + * @param mode + * the aggregation mode for numeric summaries during union (sum, min, max, alwaysone) + * @param mutableAggBufferOffset + * offset for mutable aggregation buffer + * @param inputAggBufferOffset + * offset for input aggregation buffer + */ +case class TupleUnionAggInteger( + child: Expression, + lgNomEntries: Expression, + mode: Expression, + override val mutableAggBufferOffset: Int, + override val inputAggBufferOffset: Int) + extends TupleUnionAggBase[IntegerSummary] + with TernaryLike[Expression] + with SummaryAggregateMode { + + // Constructors + def this(child: Expression) = { + this( + child, + Literal(ThetaSketchUtils.DEFAULT_LG_NOM_LONGS), + Literal(ThetaSketchUtils.MODE_SUM), + 0, + 0) + } + + def this(child: Expression, lgNomEntries: Expression) = { + this(child, lgNomEntries, Literal(ThetaSketchUtils.MODE_SUM), 0, 0) + } + + def this(child: Expression, lgNomEntries: Expression, mode: Expression) = { + this(child, lgNomEntries, mode, 0, 0) + } + + /** + * Override inputTypes to specify sketch binary (BinaryType), lgNomEntries (int), and mode + * (string) parameters. + */ + override def inputTypes: Seq[AbstractDataType] = + Seq(BinaryType, IntegerType, StringTypeWithCollation(supportsTrimCollation = true)) + + /** + * Override checkInputDataTypes to validate base inputs (sketch binary, lgNomEntries) and mode + * parameter. + */ + override def checkInputDataTypes(): TypeCheckResult = { + val defaultCheck = checkBaseInputDataTypes() + if (defaultCheck.isFailure) return defaultCheck + + checkModeParameter() + } + + // Copy constructors required by ImperativeAggregate + override def withNewMutableAggBufferOffset( + newMutableAggBufferOffset: Int): TupleUnionAggInteger = + copy(mutableAggBufferOffset = newMutableAggBufferOffset) + + override def withNewInputAggBufferOffset(newInputAggBufferOffset: Int): TupleUnionAggInteger = + copy(inputAggBufferOffset = newInputAggBufferOffset) + + override protected def withNewChildrenInternal( + newFirst: Expression, + newSecond: Expression, + newThird: Expression): TupleUnionAggInteger = + copy(child = newFirst, lgNomEntries = newSecond, mode = newThird) + + override def first: Expression = child + override def second: Expression = lgNomEntries + override def third: Expression = mode + + // Overrides for TypedImperativeAggregate + override def prettyName: String = "tuple_union_agg_integer" + + /** + * Creates IntegerSummarySetOperations for merge operations. + * + * @return + * an IntegerSummarySetOperations instance configured with the aggregation mode + */ + override protected def createSummarySetOperations(): SummarySetOperations[IntegerSummary] = { + val mode = ThetaSketchUtils.getIntegerSummaryMode(modeInput) + new IntegerSummarySetOperations(mode, mode) + } + + /** + * Heapify a sketch from a byte array. + * + * @param buffer + * the serialized sketch byte array + * @return + * a Sketch[IntegerSummary] instance + */ + override protected def heapifySketch(buffer: Array[Byte]): Sketch[IntegerSummary] = { + ThetaSketchUtils.heapifyIntegerTupleSketch(buffer, prettyName) + } + + /** + * Heapify a CompactSketch from the sketch byte array. + * + * @param buffer + * A serialized sketch byte array + * @return + * A CompactSketch instance wrapped with FinalizedTupleSketch + */ + override def deserialize(buffer: Array[Byte]): TupleSketchState[IntegerSummary] = { + if (buffer.nonEmpty) { + FinalizedTupleSketch(heapifySketch(buffer)) + } else { + this.createAggregationBuffer() + } + } +} + +/** + * The TupleUnionAggString function unions multiple TupleSketch binary representations with a + * string or string array type summary to produce a single merged TupleSketch. This is useful for + * combining pre-aggregated TupleSketch results from different partitions or data sources. + * + * See [[https://datasketches.apache.org/docs/Tuple/TupleSketches.html]] for more information. + * + * @param child + * child expression (binary TupleSketch representation created with a string or array of strings + * summary) to be unioned + * @param lgNomEntries + * the log-base-2 of nomEntries decides the number of buckets for the union operation + * @param mutableAggBufferOffset + * offset for mutable aggregation buffer + * @param inputAggBufferOffset + * offset for input aggregation buffer + */ +// scalastyle:off line.size.limit +@ExpressionDescription( + usage = """ + _FUNC_(child, lgNomEntries) - Returns the unioned TupleSketch compact binary representation. + `child` should be a binary TupleSketch representation created with a string or array of strings summary. + `lgNomEntries` is the log-base-2 of nominal entries for the union operation. Default is 12. """, + examples = """ + Examples: + > SELECT tuple_sketch_estimate_string(_FUNC_(sketch)) FROM (SELECT tuple_sketch_agg_string(key, summary) as sketch FROM VALUES (1, 'a'), (2, 'b') tab(key, summary) UNION ALL SELECT tuple_sketch_agg_string(key, summary) as sketch FROM VALUES (2, 'c'), (3, 'd') tab(key, summary)); + 3.0 + """, + group = "agg_funcs", + since = "4.2.0") +// scalastyle:on line.size.limit +case class TupleUnionAggString( + child: Expression, + lgNomEntries: Expression, + override val mutableAggBufferOffset: Int, + override val inputAggBufferOffset: Int) + extends TupleUnionAggBase[ArrayOfStringsSummary] + with BinaryLike[Expression] { + + // Constructors + def this(child: Expression) = { + this(child, Literal(ThetaSketchUtils.DEFAULT_LG_NOM_LONGS), 0, 0) + } + + def this(child: Expression, lgNomEntries: Expression) = { + this(child, lgNomEntries, 0, 0) + } + + /** + * Override inputTypes to specify sketch binary (BinaryType) and lgNomEntries (int) parameters. + */ + override def inputTypes: Seq[AbstractDataType] = + Seq(BinaryType, IntegerType) + + /** + * Override checkInputDataTypes to validate base inputs (sketch binary, lgNomEntries) only. + */ + override def checkInputDataTypes(): TypeCheckResult = checkBaseInputDataTypes() + + // Copy constructors required by ImperativeAggregate + override def withNewMutableAggBufferOffset( + newMutableAggBufferOffset: Int): TupleUnionAggString = + copy(mutableAggBufferOffset = newMutableAggBufferOffset) + + override def withNewInputAggBufferOffset(newInputAggBufferOffset: Int): TupleUnionAggString = + copy(inputAggBufferOffset = newInputAggBufferOffset) + + override protected def withNewChildrenInternal( + newLeft: Expression, + newRight: Expression): TupleUnionAggString = + copy(child = newLeft, lgNomEntries = newRight) + + override def left: Expression = child + override def right: Expression = lgNomEntries + + // Overrides for TypedImperativeAggregate + override def prettyName: String = "tuple_union_agg_string" + + /** + * Creates ArrayOfStringsSummarySetOperations for merge operations. + * + * @return + * an ArrayOfStringsSummarySetOperations instance + */ + override protected def createSummarySetOperations() + : SummarySetOperations[ArrayOfStringsSummary] = { + new ArrayOfStringsSummarySetOperations() + } + + /** + * Heapify a sketch from a byte array. + * + * @param buffer + * the serialized sketch byte array + * @return + * a Sketch[ArrayOfStringsSummary] instance + */ + override protected def heapifySketch(buffer: Array[Byte]): Sketch[ArrayOfStringsSummary] = { + ThetaSketchUtils.heapifyStringTupleSketch(buffer, prettyName) + } + + /** + * Heapify a CompactSketch from the sketch byte array. + * + * @param buffer + * A serialized sketch byte array + * @return + * A CompactSketch instance wrapped with FinalizedTupleSketch + */ + override def deserialize(buffer: Array[Byte]): TupleSketchState[ArrayOfStringsSummary] = { + if (buffer.nonEmpty) { + FinalizedTupleSketch(heapifySketch(buffer)) + } else { + this.createAggregationBuffer() + } + } +} + +abstract class TupleUnionAggBase[S <: Summary] + extends TypedImperativeAggregate[TupleSketchState[S]] + with SketchSize + with ExpectsInputTypes { + + // Abstract methods that subclasses must implement + protected def createSummarySetOperations(): SummarySetOperations[S] + protected def heapifySketch(buffer: Array[Byte]): Sketch[S] + + // Abstract members that subclasses must implement + protected def child: Expression + + override def dataType: DataType = BinaryType + override def nullable: Boolean = false + + protected def checkBaseInputDataTypes(): TypeCheckResult = { + val defaultCheck = super.checkInputDataTypes() + if (defaultCheck.isFailure) return defaultCheck + + checkLgNomEntriesParameter() + } + + /** + * Instantiate a Union instance using the lgNomEntries param and summary set operations. + * + * @return + * a Union instance wrapped with UnionTupleAggregationBuffer + */ + override def createAggregationBuffer(): TupleSketchState[S] = { + val summarySetOps = createSummarySetOperations() + val union = new Union[S](1 << lgNomEntriesInput, summarySetOps) + UnionTupleAggregationBuffer(union) + } + + /** + * Deserialize the input TupleSketch binary representation and union it with the aggregation + * buffer. The input must be a valid TupleSketch binary representation. Notes: + * - Null values are ignored. + * - Invalid binary sketches will throw an exception. + * + * @param unionBuffer + * A Union instance used as the aggregation buffer + * @param input + * An input row containing a TupleSketch binary representation + */ + override def update( + unionBuffer: TupleSketchState[S], + input: InternalRow): TupleSketchState[S] = { + // Get the binary sketch from the input + val sketchBytes = child.eval(input) + + // Return early for null values + if (sketchBytes == null) return unionBuffer + + val bytes = sketchBytes.asInstanceOf[Array[Byte]] + val inputSketch = heapifySketch(bytes) + + val union = unionBuffer match { + case UnionTupleAggregationBuffer(existingUnion) => existingUnion + case _ => throw QueryExecutionErrors.tupleInvalidInputSketchBuffer(prettyName) + } + + // Merge it with the buffer + union.union(inputSketch) + unionBuffer + } + + /** + * Merges an input TupleSketch state into the Union aggregation buffer. + * + * @param unionBuffer + * The Union instance used to store the aggregation result + * @param input + * An input Union or CompactSketch instance + */ + override def merge( + unionBuffer: TupleSketchState[S], + input: TupleSketchState[S]): TupleSketchState[S] = { + (unionBuffer, input) match { + // The input was serialized then deserialized. + case (UnionTupleAggregationBuffer(union), FinalizedTupleSketch(sketch)) => + union.union(sketch) + UnionTupleAggregationBuffer(union) + // If both arguments are union objects, merge them directly. + case (UnionTupleAggregationBuffer(union1), UnionTupleAggregationBuffer(union2)) => + union1.union(union2.getResult) + UnionTupleAggregationBuffer(union1) + case _ => throw QueryExecutionErrors.tupleInvalidInputSketchBuffer(prettyName) + } + } + + /** + * Returns a CompactSketch binary representation from the Union aggregation buffer. + * + * @param sketchState + * Union instance used as an aggregation buffer + * @return + * A CompactSketch binary representation + */ + override def eval(sketchState: TupleSketchState[S]): Any = sketchState.eval() + + /** + * Returns a CompactSketch binary representation from the Union aggregation buffer. + * + * @param sketchState + * Union instance used as an aggregation buffer + * @return + * A CompactSketch binary representation + */ + override def serialize(sketchState: TupleSketchState[S]): Array[Byte] = + sketchState.serialize() +} + +/** + * The TupleIntersectionAggDouble function computes the intersection of multiple TupleSketch + * binary representations with a double type summary to produce a single TupleSketch containing + * only the elements common to all input sketches. This is useful for finding overlapping unique + * values across different datasets. + * + * See [[https://datasketches.apache.org/docs/Tuple/TupleSketches.html]] for more information. + * + * @param child + * child expression (binary TupleSketch representation created with a double type summary) to be + * intersected + * @param mode + * the aggregation mode for numeric summaries during intersection (sum, min, max, alwaysone) + * @param mutableAggBufferOffset + * offset for mutable aggregation buffer + * @param inputAggBufferOffset + * offset for input aggregation buffer + */ +// scalastyle:off line.size.limit +@ExpressionDescription( + usage = """ + _FUNC_(child, mode) - Returns the intersected TupleSketch compact binary representation. + `child` should be a binary TupleSketch representation created with a double type summary. + `mode` is the aggregation mode for numeric summaries during intersection (sum, min, max, alwaysone). Default is sum. """, + examples = """ + Examples: + > SELECT tuple_sketch_estimate_double(_FUNC_(sketch)) FROM (SELECT tuple_sketch_agg_double(key, summary) as sketch FROM VALUES (1, 5.0D), (2, 10.0D), (3, 15.0D) tab(key, summary) UNION ALL SELECT tuple_sketch_agg_double(key, summary) as sketch FROM VALUES (2, 3.0D), (3, 7.0D), (4, 12.0D) tab(key, summary)); + 2.0 + """, + group = "agg_funcs", + since = "4.2.0") +// scalastyle:on line.size.limit +case class TupleIntersectionAggDouble( + child: Expression, + mode: Expression, + override val mutableAggBufferOffset: Int, + override val inputAggBufferOffset: Int) + extends TupleIntersectionAggBase[DoubleSummary] + with BinaryLike[Expression] + with SummaryAggregateMode { + + // Constructors + def this(child: Expression) = { + this(child, Literal(ThetaSketchUtils.MODE_SUM), 0, 0) + } + + def this(child: Expression, mode: Expression) = { + this(child, mode, 0, 0) + } + + /** + * Override inputTypes to specify sketch binary (BinaryType) and mode (string) parameters. + */ + override def inputTypes: Seq[AbstractDataType] = + Seq(BinaryType, StringTypeWithCollation(supportsTrimCollation = true)) + + /** + * Override checkInputDataTypes to validate sketch binary input and mode parameter. + */ + override def checkInputDataTypes(): TypeCheckResult = { + val defaultCheck = super.checkInputDataTypes() + if (defaultCheck.isFailure) return defaultCheck + + checkModeParameter() + } + + // Copy constructors required by ImperativeAggregate + override def withNewMutableAggBufferOffset( + newMutableAggBufferOffset: Int): TupleIntersectionAggDouble = + copy(mutableAggBufferOffset = newMutableAggBufferOffset) + + override def withNewInputAggBufferOffset( + newInputAggBufferOffset: Int): TupleIntersectionAggDouble = + copy(inputAggBufferOffset = newInputAggBufferOffset) + + override protected def withNewChildrenInternal( + newLeft: Expression, + newRight: Expression): TupleIntersectionAggDouble = + copy(child = newLeft, mode = newRight) + + override def left: Expression = child + override def right: Expression = mode + + // Overrides for TypedImperativeAggregate + override def prettyName: String = "tuple_intersection_agg_double" + + /** + * Creates DoubleSummarySetOperations for intersection operations. + * + * @return + * a DoubleSummarySetOperations instance configured with the aggregation mode + */ + override protected def createSummarySetOperations(): SummarySetOperations[DoubleSummary] = { + val mode = ThetaSketchUtils.getDoubleSummaryMode(modeInput) + new DoubleSummarySetOperations(mode) + } + + /** + * Heapify a sketch from a byte array. + * + * @param buffer + * the serialized sketch byte array + * @return + * a Sketch[DoubleSummary] instance + */ + override protected def heapifySketch(buffer: Array[Byte]): Sketch[DoubleSummary] = { + ThetaSketchUtils.heapifyDoubleTupleSketch(buffer, prettyName) + } + + /** + * Heapify a CompactSketch from the sketch byte array. + * + * @param buffer + * A serialized sketch byte array + * @return + * A CompactSketch instance wrapped with FinalizedTupleSketch + */ + override def deserialize(buffer: Array[Byte]): TupleSketchState[DoubleSummary] = { + if (buffer.nonEmpty) { + FinalizedTupleSketch(heapifySketch(buffer)) + } else { + this.createAggregationBuffer() + } + } +} + +/** + * The TupleIntersectionAggInteger function computes the intersection of multiple TupleSketch + * binary representations with an integer type summary to produce a single TupleSketch containing + * only the elements common to all input sketches. This is useful for finding overlapping unique + * values across different datasets. + * + * See [[https://datasketches.apache.org/docs/Tuple/TupleSketches.html]] for more information. + * + * @param child + * child expression (binary TupleSketch representation created with an integer type summary) to + * be intersected + * @param mode + * the aggregation mode for numeric summaries during intersection (sum, min, max, alwaysone) + * @param mutableAggBufferOffset + * offset for mutable aggregation buffer + * @param inputAggBufferOffset + * offset for input aggregation buffer + */ +// scalastyle:off line.size.limit +@ExpressionDescription( + usage = """ + _FUNC_(child, mode) - Returns the intersected TupleSketch compact binary representation. + `child` should be a binary TupleSketch representation created with an integer type summary. + `mode` is the aggregation mode for numeric summaries during intersection (sum, min, max, alwaysone). Default is sum. """, + examples = """ + Examples: + > SELECT tuple_sketch_estimate_integer(_FUNC_(sketch)) FROM (SELECT tuple_sketch_agg_integer(key, summary) as sketch FROM VALUES (1, 1), (2, 2), (3, 3) tab(key, summary) UNION ALL SELECT tuple_sketch_agg_integer(key, summary) as sketch FROM VALUES (2, 2), (3, 3), (4, 4) tab(key, summary)); + 2.0 + """, + group = "agg_funcs", + since = "4.2.0") +// scalastyle:on line.size.limit +case class TupleIntersectionAggInteger( + child: Expression, + mode: Expression, + override val mutableAggBufferOffset: Int, + override val inputAggBufferOffset: Int) + extends TupleIntersectionAggBase[IntegerSummary] + with BinaryLike[Expression] + with SummaryAggregateMode { + + // Constructors + def this(child: Expression) = { + this(child, Literal(ThetaSketchUtils.MODE_SUM), 0, 0) + } + + def this(child: Expression, mode: Expression) = { + this(child, mode, 0, 0) + } + + /** + * Override inputTypes to specify sketch binary (BinaryType) and mode (string) parameters. + */ + override def inputTypes: Seq[AbstractDataType] = + Seq(BinaryType, StringTypeWithCollation(supportsTrimCollation = true)) + + /** + * Override checkInputDataTypes to validate sketch binary input and mode parameter. + */ + override def checkInputDataTypes(): TypeCheckResult = { + val defaultCheck = super.checkInputDataTypes() + if (defaultCheck.isFailure) return defaultCheck + + checkModeParameter() + } + + // Copy constructors required by ImperativeAggregate + override def withNewMutableAggBufferOffset( + newMutableAggBufferOffset: Int): TupleIntersectionAggInteger = + copy(mutableAggBufferOffset = newMutableAggBufferOffset) + + override def withNewInputAggBufferOffset( + newInputAggBufferOffset: Int): TupleIntersectionAggInteger = + copy(inputAggBufferOffset = newInputAggBufferOffset) + + override protected def withNewChildrenInternal( + newLeft: Expression, + newRight: Expression): TupleIntersectionAggInteger = + copy(child = newLeft, mode = newRight) + + override def left: Expression = child + override def right: Expression = mode + + // Overrides for TypedImperativeAggregate + override def prettyName: String = "tuple_intersection_agg_integer" + + /** + * Creates IntegerSummarySetOperations for intersection operations. + * + * @return + * an IntegerSummarySetOperations instance configured with the aggregation mode + */ + override protected def createSummarySetOperations(): SummarySetOperations[IntegerSummary] = { + val mode = ThetaSketchUtils.getIntegerSummaryMode(modeInput) + new IntegerSummarySetOperations(mode, mode) + } + + /** + * Heapify a sketch from a byte array. + * + * @param buffer + * the serialized sketch byte array + * @return + * a Sketch[IntegerSummary] instance + */ + override protected def heapifySketch(buffer: Array[Byte]): Sketch[IntegerSummary] = { + ThetaSketchUtils.heapifyIntegerTupleSketch(buffer, prettyName) Review Comment: These function calls are using the function from `ThetaSketchUtils` [here](https://github.com/apache/spark/blob/2bd1d48477f394bdba6ce39eeb13f22e83f731e6/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/util/ThetaSketchUtils.scala#L179) which catches the Datasketches errors! 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