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From hvanhovell <...@git.apache.org>
Subject [GitHub] spark pull request #14136: [SPARK-16282][SQL] Implement percentile SQL funct...
Date Fri, 25 Nov 2016 17:39:36 GMT
Github user hvanhovell commented on a diff in the pull request:

    https://github.com/apache/spark/pull/14136#discussion_r89645855
  
    --- Diff: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/Percentile.scala
---
    @@ -0,0 +1,201 @@
    +/*
    + * 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.spark.sql.AnalysisException
    +import org.apache.spark.sql.catalyst.InternalRow
    +import org.apache.spark.sql.catalyst.analysis.TypeCheckResult
    +import org.apache.spark.sql.catalyst.expressions._
    +import org.apache.spark.sql.catalyst.util._
    +import org.apache.spark.sql.types._
    +import org.apache.spark.util.collection.OpenHashMap
    +
    +/**
    + * The Percentile aggregate function returns the exact percentile(s) of numeric column
`expr` at
    + * the given percentage(s) with value range in [0.0, 1.0].
    + *
    + * The operator is bound to the slower sort based aggregation path because the number
of elements
    + * and their partial order cannot be determined in advance. Therefore we have to store
all the
    + * elements in memory, and that too many elements can cause GC paused and eventually
OutOfMemory
    + * Errors.
    + *
    + * @param child child expression that produce numeric column value with `child.eval(inputRow)`
    + * @param percentageExpression Expression that represents a single percentage value or
an array of
    + *                             percentage values. Each percentage value must be in the
range
    + *                             [0.0, 1.0].
    + */
    +@ExpressionDescription(
    +  usage =
    +    """
    +      _FUNC_(col, percentage) - Returns the exact percentile value of numeric column
`col` at the
    +      given percentage. The value of percentage must be between 0.0 and 1.0.
    +
    +      _FUNC_(col, array(percentage1 [, percentage2]...)) - Returns the exact percentile
value array
    +      of numeric column `col` at the given percentage(s). Each value of the percentage
array must
    +      be between 0.0 and 1.0.
    +    """)
    +case class Percentile(
    +  child: Expression,
    +  percentageExpression: Expression,
    +  mutableAggBufferOffset: Int = 0,
    +  inputAggBufferOffset: Int = 0) extends ImperativeAggregate {
    +
    +  def this(child: Expression, percentageExpression: Expression) = {
    +    this(child, percentageExpression, 0, 0)
    +  }
    +
    +  override def prettyName: String = "percentile"
    +
    +  override def withNewMutableAggBufferOffset(newMutableAggBufferOffset: Int): ImperativeAggregate
=
    +    copy(mutableAggBufferOffset = newMutableAggBufferOffset)
    +
    +  override def withNewInputAggBufferOffset(newInputAggBufferOffset: Int): ImperativeAggregate
=
    +    copy(inputAggBufferOffset = newInputAggBufferOffset)
    +
    +  private var counts = new OpenHashMap[Number, Long]
    +
    +  // Mark as lazy so that percentageExpression is not evaluated during tree transformation.
    +  private lazy val (returnPercentileArray: Boolean, percentages: Seq[Number]) =
    +    evalPercentages(percentageExpression)
    +
    +  override def children: Seq[Expression] = child :: percentageExpression :: Nil
    +
    +  // Returns null for empty inputs
    +  override def nullable: Boolean = true
    +
    +  override def dataType: DataType =
    +    if (returnPercentileArray) ArrayType(DoubleType) else DoubleType
    +
    +  override def inputTypes: Seq[AbstractDataType] =
    +    Seq(NumericType, TypeCollection(NumericType, ArrayType))
    --- End diff --
    
    BTW - you can make the analyzer add casts for you:
    ```scala
    override def inputTypes: Seq[AbstractDataType] = percentageExpression.dataType match {
      case _: ArrayType => Seq(NumericType, ArrayType(DoubleType, false))
      case _ => Seq(NumericType, DoubleType)
    }
    ```
    
    Then you are alway sure you get a double or a double array for the `percentageExpression`.


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