RyanBerti commented on code in PR #40615: URL: https://github.com/apache/spark/pull/40615#discussion_r1172909432
########## sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/datasketchesAggregates.scala: ########## @@ -0,0 +1,336 @@ +/* + * 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 java.util.Locale + +import org.apache.datasketches.SketchesArgumentException +import org.apache.datasketches.hll.{HllSketch, TgtHllType, Union} +import org.apache.datasketches.memory.Memory + +import org.apache.spark.sql.catalyst.InternalRow +import org.apache.spark.sql.catalyst.expressions.{ExpectsInputTypes, Expression, ExpressionDescription, Literal} +import org.apache.spark.sql.catalyst.trees.{BinaryLike, TernaryLike} +import org.apache.spark.sql.types.{AbstractDataType, AnyDataType, BinaryType, DataType, IntegerType, LongType, StringType} +import org.apache.spark.unsafe.types.UTF8String + + +/** + * The HllSketchAgg function utilizes a Datasketches HllSketch instance to + * probabilistically count the number of unique values in a given column, and + * outputs the binary representation of the HllSketch. + * + * See [[https://datasketches.apache.org/docs/HLL/HLL.html]] for more information + * + * @param child child expression against which unique counting will occur + * @param lgConfigK the log-base-2 of K, where K is the number of buckets or slots for the sketch + * @param tgtHllType the target type of the HllSketch to be used (HLL_4, HLL_6, HLL_8) + */ +@ExpressionDescription( + usage = """ + _FUNC_(expr, lgConfigK, tgtHllType) - Returns the HllSketch's compact binary representation. + `lgConfigK` (optional) the log-base-2 of K, with K = the number of buckets for the HllSketch. + `tgtHllType` (optional) the target type of the HllSketch (HLL_4, HLL_6, HLL_8). """, + examples = """ + Examples: + > SELECT hll_sketch_estimate(_FUNC_(col1, 12, 'HLL_4')) + FROM VALUES (1), (1), (2), (2), (3) tab(col1); + 3 + """, + group = "agg_funcs", + since = "3.5.0") +case class HllSketchAgg( + child: Expression, + lgConfigKExpression: Expression, + tgtHllTypeExpression: Expression, + mutableAggBufferOffset: Int = 0, + inputAggBufferOffset: Int = 0) + extends TypedImperativeAggregate[HllSketch] with TernaryLike[Expression] with ExpectsInputTypes { + + // Hllsketch config - mark as lazy so that they're not evaluated during tree transformation. + + lazy val lgConfigK: Int = second.eval().asInstanceOf[Int] + lazy val tgtHllType: TgtHllType = try { + TgtHllType.valueOf(third.eval().asInstanceOf[UTF8String].toString.toUpperCase(Locale.ROOT)) + } catch { + case _: IllegalArgumentException => + throw new SketchesArgumentException("Invalid tgtHllType value") + } + + // Constructors + + def this(child: Expression) = { + this(child, Literal(HllSketch.DEFAULT_LG_K), Literal(HllSketch.DEFAULT_HLL_TYPE.toString), 0, 0) + } + + def this(child: Expression, lgConfigK: Expression) = { + this(child, lgConfigK, Literal(HllSketch.DEFAULT_HLL_TYPE.toString), 0, 0) + } + + def this(child: Expression, lgConfigK: Int) = { + this(child, Literal(lgConfigK), Literal(HllSketch.DEFAULT_HLL_TYPE.toString), 0, 0) + } + + def this(child: Expression, lgConfigK: Expression, tgtHllType: Expression) = { + this(child, lgConfigK, tgtHllType, 0, 0) + } + + def this(child: Expression, lgConfigK: Int, tgtHllType: String) = { + this(child, Literal(lgConfigK), Literal(tgtHllType), 0, 0) + } + + // Copy constructors required by ImperativeAggregate + + override def withNewMutableAggBufferOffset(newMutableAggBufferOffset: Int): HllSketchAgg = + copy(mutableAggBufferOffset = newMutableAggBufferOffset) + + override def withNewInputAggBufferOffset(newInputAggBufferOffset: Int): HllSketchAgg = + copy(inputAggBufferOffset = newInputAggBufferOffset) + + override protected def withNewChildrenInternal(newFirst: Expression, + newSecond: Expression, + newThird: Expression): HllSketchAgg = + copy(child = newFirst, lgConfigKExpression = newSecond, tgtHllTypeExpression = newThird) + + // Overrides for TernaryLike + + override def first: Expression = child + + override def second: Expression = lgConfigKExpression + + override def third: Expression = tgtHllTypeExpression + + // Overrides for TypedImperativeAggregate + + override def prettyName: String = "hll_sketch_agg" + + override def inputTypes: Seq[AbstractDataType] = Seq(AnyDataType, IntegerType, StringType) + + override def dataType: DataType = BinaryType + + override def nullable: Boolean = false + + /** + * Instantiate an HllSketch instance using the lgConfigK and tgtHllType params. + * + * @return an HllSketch instance + */ + override def createAggregationBuffer(): HllSketch = { + new HllSketch(lgConfigK, tgtHllType) + } + + /** + * Evaluate the input row and update the HllSketch instance with the row's value. + * The update function only supports a subset of Spark SQL types, and an + * UnsupportedOperationException will be thrown for unsupported types. + * + * @param sketch The HllSketch instance. + * @param input an input row + */ + override def update(sketch: HllSketch, input: InternalRow): HllSketch = { + val v = first.eval(input) + if (v != null) { + first.dataType match { + // Update implemented for a subset of types supported by HllSketch + // Spark SQL doesn't have equivalent types for ByteBuffer or char[] so leave those out + // Leaving out support for Array types, as unique counting these aren't a common use case + // Leaving out support for floating point types (IE DoubleType) due to imprecision + // TODO: implement support for decimal/datetime/interval types + case IntegerType => sketch.update(v.asInstanceOf[Int]) + case LongType => sketch.update(v.asInstanceOf[Long]) + case StringType => sketch.update(v.asInstanceOf[UTF8String].toString) + case BinaryType => sketch.update(v.asInstanceOf[Array[Byte]]) + case dataType => throw new UnsupportedOperationException( + s"A HllSketch instance cannot be updates with a Spark ${dataType.toString} type") + } + } + sketch + } + + /** + * Merges an input HllSketch into the sketch which is acting as the aggregation buffer. + * + * @param sketch the HllSketch instance used to store the aggregation result. + * @param input an input HllSketch instance + */ + override def merge(sketch: HllSketch, input: HllSketch): HllSketch = { + val union = new Union(sketch.getLgConfigK) + union.update(sketch) + union.update(input) + union.getResult(sketch.getTgtHllType) + } + + /** + * Returns an HllSketch derived from the input column or expression + * + * @param sketch HllSketch instance used as an aggregation buffer + * @return A binary sketch which can be evaluated or merged + */ + override def eval(sketch: HllSketch): Any = { + sketch.toCompactByteArray + } + + /** Convert the underlying HllSketch into an updatable byte array */ + override def serialize(sketch: HllSketch): Array[Byte] = { + sketch.toUpdatableByteArray + } + + /** De-serializes the updatable byte array into a HllSketch instance */ + override def deserialize(buffer: Array[Byte]): HllSketch = { + HllSketch.heapify(buffer) + } +} + +/** + * The HllUnionAgg function ingests and merges Datasketches HllSketch + * instances previously produced by the HllSketchBinary function, and + * outputs the merged HllSketch. + * + * See [[https://datasketches.apache.org/docs/HLL/HLL.html]] for more information + * + * @param child child expression against which unique counting will occur + * @param lgMaxK The largest maximum size for lgConfigK for the union operation. + */ +@ExpressionDescription( + usage = """ + _FUNC_(expr, lgMaxK) - Returns the estimated number of unique values. + `lgMaxK` (optional) The largest maximum size for lgConfigK for the union operation.""", + examples = """ + Examples: + > SELECT hll_sketch_estimate(_FUNC_(sketch, 12)) + FROM ( + SELECT hll_sketch_agg(col1) as sketch FROMVALUES (1), (1), (2), (2), (3) tab(col1) + UNION ALL + SELECT hll_sketch_agg(col1) as sketch FROMVALUES (4), (4), (5), (5), (6) tab(col1) + ); + 3 + """, + group = "agg_funcs", + since = "3.5.0") +case class HllUnionAgg( + child: Expression, + lgMaxKExpression: Expression, + mutableAggBufferOffset: Int = 0, + inputAggBufferOffset: Int = 0) + extends TypedImperativeAggregate[Union] with BinaryLike[Expression] with ExpectsInputTypes { + + // Union config - mark as lazy so that they're not evaluated during tree transformation. + + lazy val lgMaxK: Int = lgMaxKExpression.eval().asInstanceOf[Int] + + // Constructors + + def this(child: Expression) = { + this(child, Literal(HllSketch.DEFAULT_LG_K), 0, 0) + } + + def this(child: Expression, lgMaxK: Expression) = { + this(child, lgMaxK, 0, 0) + } + + def this(child: Expression, lgMaxK: Int) = { + this(child, Literal(lgMaxK), 0, 0) + } + + // Copy constructors required by ImperativeAggregate + + override def withNewMutableAggBufferOffset(newMutableAggBufferOffset: Int): + HllUnionAgg = copy(mutableAggBufferOffset = newMutableAggBufferOffset) + + override def withNewInputAggBufferOffset(newInputAggBufferOffset: Int): HllUnionAgg = + copy(inputAggBufferOffset = newInputAggBufferOffset) + + override protected def withNewChildrenInternal(newLeft: Expression, newRight: Expression): + HllUnionAgg = copy(child = newLeft, lgMaxKExpression = newRight) + + // Overrides for BinaryLike + + override def left: Expression = child + + override def right: Expression = lgMaxKExpression + + // Overrides for TypedImperativeAggregate + + override def prettyName: String = "hll_union_agg" + + override def inputTypes: Seq[AbstractDataType] = Seq(BinaryType, IntegerType) + + override def dataType: DataType = BinaryType + + override def nullable: Boolean = false + + /** + * Instantiate an Union instance using the lgMaxK param. + * + * @return an Union instance + */ + override def createAggregationBuffer(): Union = { + new Union(lgMaxK) + } + + /** + * Update the Union instance with the HllSketch byte array obtained from the row. + * + * @param union The Union instance. + * @param input an input row + */ + override def update(union: Union, input: InternalRow): Union = { + val v = child.eval(input) + if (v != null) { + child.dataType match { + case BinaryType => + union.update(HllSketch.wrap(Memory.wrap(v.asInstanceOf[Array[Byte]]))) + case _ => throw new UnsupportedOperationException( + s"A Union instance can only be updated with a valid HllSketch byte array") Review Comment: I think we can keep this exception for cases where the update() is being called outside of normal Spark operations. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
