Github user lw-lin commented on a diff in the pull request:
https://github.com/apache/spark/pull/14298#discussion_r73101674
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/PercentileApprox.scala
---
@@ -0,0 +1,456 @@
+/*
+ * 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 scala.collection.mutable.ArrayBuffer
+
+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.expressions.aggregate.QuantileSummaries.Stats
+import org.apache.spark.sql.catalyst.util._
+import org.apache.spark.sql.types._
+
+/**
+ * Computes an approximate percentile (quantile) using the G-K algorithm
(see below), for very
+ * large numbers of rows where the regular percentile() UDAF might run out
of memory.
+ *
+ * The input is a single double value or an array of double values
representing the percentiles
+ * requested. The output, corresponding to the input, is either an single
double value or an
+ * array of doubles that are the percentile values.
+ */
+@ExpressionDescription(
+ usage = """_FUNC_(col, p [, B]) - Returns an approximate pth percentile
of a numeric column in the
+ group. The B parameter, which defaults to 1000, controls
approximation accuracy at the cost of
+ memory; higher values yield better approximations.
+ _FUNC_(col, array(p1 [, p2]...) [, B]) - Same as above, but accepts
and returns an array of
+ percentile values instead of a single one.
+ """)
+case class PercentileApprox(
+ child: Expression,
+ percentilesExpr: Expression,
+ bExpr: Option[Expression],
+ percentiles: Seq[Double], // the extracted percentiles
+ B: Int, // the extracted B
--- End diff --
I don't have strong preference here -- let's see what reviewers say.
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