-
Notifications
You must be signed in to change notification settings - Fork 28.5k
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
[SPARK-18429][SQL] implement a new Aggregate for CountMinSketch
## What changes were proposed in this pull request? This PR implements a new Aggregate to generate count min sketch, which is a wrapper of CountMinSketch. ## How was this patch tested? add test cases Author: wangzhenhua <[email protected]> Closes #15877 from wzhfy/cms.
- Loading branch information
Showing
8 changed files
with
710 additions
and
8 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
146 changes: 146 additions & 0 deletions
146
...rc/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/CountMinSketchAgg.scala
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,146 @@ | ||
| /* | ||
| * 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.io.{ByteArrayInputStream, ByteArrayOutputStream} | ||
|
|
||
| import org.apache.spark.sql.catalyst.InternalRow | ||
| import org.apache.spark.sql.catalyst.analysis.TypeCheckResult | ||
| import org.apache.spark.sql.catalyst.analysis.TypeCheckResult.{TypeCheckFailure, TypeCheckSuccess} | ||
| import org.apache.spark.sql.catalyst.expressions.{Expression, ExpressionDescription} | ||
| import org.apache.spark.sql.types._ | ||
| import org.apache.spark.unsafe.types.UTF8String | ||
| import org.apache.spark.util.sketch.CountMinSketch | ||
|
|
||
| /** | ||
| * This function returns a count-min sketch of a column with the given esp, confidence and seed. | ||
| * A count-min sketch is a probabilistic data structure used for summarizing streams of data in | ||
| * sub-linear space, which is useful for equality predicates and join size estimation. | ||
| * The result returned by the function is an array of bytes, which should be deserialized to a | ||
| * `CountMinSketch` before usage. | ||
| * | ||
| * @param child child expression that can produce column value with `child.eval(inputRow)` | ||
| * @param epsExpression relative error, must be positive | ||
| * @param confidenceExpression confidence, must be positive and less than 1.0 | ||
| * @param seedExpression random seed | ||
| */ | ||
| @ExpressionDescription( | ||
| usage = """ | ||
| _FUNC_(col, eps, confidence, seed) - Returns a count-min sketch of a column with the given esp, | ||
| confidence and seed. The result is an array of bytes, which should be deserialized to a | ||
| `CountMinSketch` before usage. `CountMinSketch` is useful for equality predicates and join | ||
| size estimation. | ||
| """) | ||
| case class CountMinSketchAgg( | ||
| child: Expression, | ||
| epsExpression: Expression, | ||
| confidenceExpression: Expression, | ||
| seedExpression: Expression, | ||
| override val mutableAggBufferOffset: Int, | ||
| override val inputAggBufferOffset: Int) extends TypedImperativeAggregate[CountMinSketch] { | ||
|
|
||
| def this( | ||
| child: Expression, | ||
| epsExpression: Expression, | ||
| confidenceExpression: Expression, | ||
| seedExpression: Expression) = { | ||
| this(child, epsExpression, confidenceExpression, seedExpression, 0, 0) | ||
| } | ||
|
|
||
| // Mark as lazy so that they are not evaluated during tree transformation. | ||
| private lazy val eps: Double = epsExpression.eval().asInstanceOf[Double] | ||
| private lazy val confidence: Double = confidenceExpression.eval().asInstanceOf[Double] | ||
| private lazy val seed: Int = seedExpression.eval().asInstanceOf[Int] | ||
|
|
||
| override def checkInputDataTypes(): TypeCheckResult = { | ||
| val defaultCheck = super.checkInputDataTypes() | ||
| if (defaultCheck.isFailure) { | ||
| defaultCheck | ||
| } else if (!epsExpression.foldable || !confidenceExpression.foldable || | ||
| !seedExpression.foldable) { | ||
| TypeCheckFailure( | ||
| "The eps, confidence or seed provided must be a literal or constant foldable") | ||
| } else if (epsExpression.eval() == null || confidenceExpression.eval() == null || | ||
| seedExpression.eval() == null) { | ||
| TypeCheckFailure("The eps, confidence or seed provided should not be null") | ||
| } else if (eps <= 0D) { | ||
| TypeCheckFailure(s"Relative error must be positive (current value = $eps)") | ||
| } else if (confidence <= 0D || confidence >= 1D) { | ||
| TypeCheckFailure(s"Confidence must be within range (0.0, 1.0) (current value = $confidence)") | ||
| } else { | ||
| TypeCheckSuccess | ||
| } | ||
| } | ||
|
|
||
| override def createAggregationBuffer(): CountMinSketch = { | ||
| CountMinSketch.create(eps, confidence, seed) | ||
| } | ||
|
|
||
| override def update(buffer: CountMinSketch, input: InternalRow): Unit = { | ||
| val value = child.eval(input) | ||
| // Ignore empty rows | ||
| if (value != null) { | ||
| child.dataType match { | ||
| // `Decimal` and `UTF8String` are internal types in spark sql, we need to convert them | ||
| // into acceptable types for `CountMinSketch`. | ||
| case DecimalType() => buffer.add(value.asInstanceOf[Decimal].toJavaBigDecimal) | ||
| // For string type, we can get bytes of our `UTF8String` directly, and call the `addBinary` | ||
| // instead of `addString` to avoid unnecessary conversion. | ||
| case StringType => buffer.addBinary(value.asInstanceOf[UTF8String].getBytes) | ||
| case _ => buffer.add(value) | ||
| } | ||
| } | ||
| } | ||
|
|
||
| override def merge(buffer: CountMinSketch, input: CountMinSketch): Unit = { | ||
| buffer.mergeInPlace(input) | ||
| } | ||
|
|
||
| override def eval(buffer: CountMinSketch): Any = serialize(buffer) | ||
|
|
||
| override def serialize(buffer: CountMinSketch): Array[Byte] = { | ||
| val out = new ByteArrayOutputStream() | ||
| buffer.writeTo(out) | ||
| out.toByteArray | ||
| } | ||
|
|
||
| override def deserialize(storageFormat: Array[Byte]): CountMinSketch = { | ||
| val in = new ByteArrayInputStream(storageFormat) | ||
| CountMinSketch.readFrom(in) | ||
| } | ||
|
|
||
| override def withNewMutableAggBufferOffset(newMutableAggBufferOffset: Int): CountMinSketchAgg = | ||
| copy(mutableAggBufferOffset = newMutableAggBufferOffset) | ||
|
|
||
| override def withNewInputAggBufferOffset(newInputAggBufferOffset: Int): CountMinSketchAgg = | ||
| copy(inputAggBufferOffset = newInputAggBufferOffset) | ||
|
|
||
| override def inputTypes: Seq[AbstractDataType] = { | ||
| Seq(TypeCollection(NumericType, StringType, DateType, TimestampType, BooleanType, BinaryType), | ||
| DoubleType, DoubleType, IntegerType) | ||
| } | ||
|
|
||
| override def nullable: Boolean = false | ||
|
|
||
| override def dataType: DataType = BinaryType | ||
|
|
||
| override def children: Seq[Expression] = | ||
| Seq(child, epsExpression, confidenceExpression, seedExpression) | ||
|
|
||
| override def prettyName: String = "count_min_sketch" | ||
| } |
Oops, something went wrong.