Github user hvanhovell commented on a diff in the pull request:
https://github.com/apache/spark/pull/14136#discussion_r70822715
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/Percentile.scala
---
@@ -0,0 +1,172 @@
+/*
+ * 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.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 computes the exact percentile(s) of
expr at pc with range in
+ * [0, 1].
+ * The parameter pc can be a DoubleType or DoubleType array.
+ *
+ * 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.
+ */
+@ExpressionDescription(
+ usage = """_FUNC_(epxr, pc) - Returns the percentile(s) of expr at pc
(range: [0,1]). pc can be
+ a double or double array.""")
+case class Percentile(
+ child: Expression,
+ pc: Expression,
+ mutableAggBufferOffset: Int = 0,
+ inputAggBufferOffset: Int = 0) extends ImperativeAggregate {
+
+ def this(child: Expression, pc: Expression) = {
+ this(child = child, pc = pc, mutableAggBufferOffset = 0,
inputAggBufferOffset = 0)
+ }
+
+ private val percentiles: Seq[Double] = pc match {
+ case Literal(ar: GenericArrayData, _: ArrayType) =>
+ ar.asInstanceOf[GenericArrayData].array.map{ d =>
d.asInstanceOf[Double]}
--- End diff --
We should also check if the array is not empty.
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