[GitHub] spark pull request #14868: [SPARK-16283][SQL] Implements percentile_approx a...
Github user asfgit closed the pull request at: https://github.com/apache/spark/pull/14868 --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark pull request #14868: [SPARK-16283][SQL] Implements percentile_approx a...
Github user clockfly commented on a diff in the pull request:
https://github.com/apache/spark/pull/14868#discussion_r77127003
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/ApproximatePercentile.scala
---
@@ -0,0 +1,321 @@
+/*
+ * 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.nio.ByteBuffer
+
+import com.google.common.primitives.{Doubles, Ints, Longs}
+
+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.analysis.TypeCheckResult.{TypeCheckFailure,
TypeCheckSuccess}
+import org.apache.spark.sql.catalyst.expressions._
+import
org.apache.spark.sql.catalyst.expressions.aggregate.ApproximatePercentile.{PercentileDigest}
+import org.apache.spark.sql.catalyst.util.{ArrayData, GenericArrayData}
+import org.apache.spark.sql.catalyst.util.QuantileSummaries
+import
org.apache.spark.sql.catalyst.util.QuantileSummaries.{defaultCompressThreshold,
Stats}
+import org.apache.spark.sql.types._
+
+/**
+ * The ApproximatePercentile function returns the approximate
percentile(s) of a column at the given
+ * percentage(s). A percentile is a watermark value below which a given
percentage of the column
+ * values fall. For example, the percentile of column `col` at percentage
50% is the median of
+ * column `col`.
+ *
+ * This function supports partial aggregation.
+ *
+ * @param child child expression that can produce 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 between
+ * 0.0 and 1.0.
+ * @param accuracyExpression Integer literal expression of approximation
accuracy. Higher value
+ * yields better accuracy, the default value is
+ * DEFAULT_PERCENTILE_ACCURACY.
+ */
+@ExpressionDescription(
+ usage =
+"""
+ _FUNC_(col, percentage [, accuracy]) - Returns the approximate
percentile value of numeric
+ column `col` at the given percentage. The value of percentage must
be between 0.0
+ and 1.0. The `accuracy` parameter (default: 1) is a positive
integer literal which
+ controls approximation accuracy at the cost of memory. Higher value
of `accuracy` yields
+ better accuracy, `1.0/accuracy` is the relative error of the
approximation.
+
+ _FUNC_(col, array(percentage1 [, percentage2]...) [, accuracy]) -
Returns the approximate
+ percentile array of column `col` at the given percentage array. Each
value of the
+ percentage array must be between 0.0 and 1.0. The `accuracy`
parameter (default: 1) is
+ a positive integer literal which controls approximation accuracy at
the cost of memory.
+ Higher value of `accuracy` yields better accuracy, `1.0/accuracy`
is the relative error of
+ the approximation.
+""")
+case class ApproximatePercentile(
+child: Expression,
+percentageExpression: Expression,
+accuracyExpression: Expression,
+override val mutableAggBufferOffset: Int,
+override val inputAggBufferOffset: Int) extends
TypedImperativeAggregate[PercentileDigest] {
+
+ def this(child: Expression, percentageExpression: Expression,
accuracyExpression: Expression) = {
+this(child, percentageExpression, accuracyExpression, 0, 0)
+ }
+
+ def this(child: Expression, percentageExpression: Expression) = {
+this(child, percentageExpression,
Literal(ApproximatePercentile.DEFAULT_PERCENTILE_ACCURACY))
+ }
+
+ // Mark as lazy so that accuracyExpression is not evaluated during tree
transformation.
+ private lazy val
[GitHub] spark pull request #14868: [SPARK-16283][SQL] Implements percentile_approx a...
Github user clockfly commented on a diff in the pull request:
https://github.com/apache/spark/pull/14868#discussion_r77126967
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/ApproximatePercentile.scala
---
@@ -0,0 +1,321 @@
+/*
+ * 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.nio.ByteBuffer
+
+import com.google.common.primitives.{Doubles, Ints, Longs}
+
+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.analysis.TypeCheckResult.{TypeCheckFailure,
TypeCheckSuccess}
+import org.apache.spark.sql.catalyst.expressions._
+import
org.apache.spark.sql.catalyst.expressions.aggregate.ApproximatePercentile.{PercentileDigest}
+import org.apache.spark.sql.catalyst.util.{ArrayData, GenericArrayData}
+import org.apache.spark.sql.catalyst.util.QuantileSummaries
+import
org.apache.spark.sql.catalyst.util.QuantileSummaries.{defaultCompressThreshold,
Stats}
+import org.apache.spark.sql.types._
+
+/**
+ * The ApproximatePercentile function returns the approximate
percentile(s) of a column at the given
+ * percentage(s). A percentile is a watermark value below which a given
percentage of the column
+ * values fall. For example, the percentile of column `col` at percentage
50% is the median of
+ * column `col`.
+ *
+ * This function supports partial aggregation.
+ *
+ * @param child child expression that can produce 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 between
+ * 0.0 and 1.0.
+ * @param accuracyExpression Integer literal expression of approximation
accuracy. Higher value
+ * yields better accuracy, the default value is
+ * DEFAULT_PERCENTILE_ACCURACY.
+ */
+@ExpressionDescription(
+ usage =
+"""
+ _FUNC_(col, percentage [, accuracy]) - Returns the approximate
percentile value of numeric
+ column `col` at the given percentage. The value of percentage must
be between 0.0
+ and 1.0. The `accuracy` parameter (default: 1) is a positive
integer literal which
+ controls approximation accuracy at the cost of memory. Higher value
of `accuracy` yields
+ better accuracy, `1.0/accuracy` is the relative error of the
approximation.
+
+ _FUNC_(col, array(percentage1 [, percentage2]...) [, accuracy]) -
Returns the approximate
+ percentile array of column `col` at the given percentage array. Each
value of the
+ percentage array must be between 0.0 and 1.0. The `accuracy`
parameter (default: 1) is
+ a positive integer literal which controls approximation accuracy at
the cost of memory.
+ Higher value of `accuracy` yields better accuracy, `1.0/accuracy`
is the relative error of
+ the approximation.
+""")
+case class ApproximatePercentile(
+child: Expression,
+percentageExpression: Expression,
+accuracyExpression: Expression,
+override val mutableAggBufferOffset: Int,
+override val inputAggBufferOffset: Int) extends
TypedImperativeAggregate[PercentileDigest] {
+
+ def this(child: Expression, percentageExpression: Expression,
accuracyExpression: Expression) = {
+this(child, percentageExpression, accuracyExpression, 0, 0)
+ }
+
+ def this(child: Expression, percentageExpression: Expression) = {
+this(child, percentageExpression,
Literal(ApproximatePercentile.DEFAULT_PERCENTILE_ACCURACY))
+ }
+
+ // Mark as lazy so that accuracyExpression is not evaluated during tree
transformation.
+ private lazy val
[GitHub] spark pull request #14868: [SPARK-16283][SQL] Implements percentile_approx a...
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/14868#discussion_r77114814
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/ApproximatePercentile.scala
---
@@ -0,0 +1,321 @@
+/*
+ * 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.nio.ByteBuffer
+
+import com.google.common.primitives.{Doubles, Ints, Longs}
+
+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.analysis.TypeCheckResult.{TypeCheckFailure,
TypeCheckSuccess}
+import org.apache.spark.sql.catalyst.expressions._
+import
org.apache.spark.sql.catalyst.expressions.aggregate.ApproximatePercentile.{PercentileDigest}
+import org.apache.spark.sql.catalyst.util.{ArrayData, GenericArrayData}
+import org.apache.spark.sql.catalyst.util.QuantileSummaries
+import
org.apache.spark.sql.catalyst.util.QuantileSummaries.{defaultCompressThreshold,
Stats}
+import org.apache.spark.sql.types._
+
+/**
+ * The ApproximatePercentile function returns the approximate
percentile(s) of a column at the given
+ * percentage(s). A percentile is a watermark value below which a given
percentage of the column
+ * values fall. For example, the percentile of column `col` at percentage
50% is the median of
+ * column `col`.
+ *
+ * This function supports partial aggregation.
+ *
+ * @param child child expression that can produce 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 between
+ * 0.0 and 1.0.
+ * @param accuracyExpression Integer literal expression of approximation
accuracy. Higher value
+ * yields better accuracy, the default value is
+ * DEFAULT_PERCENTILE_ACCURACY.
+ */
+@ExpressionDescription(
+ usage =
+"""
+ _FUNC_(col, percentage [, accuracy]) - Returns the approximate
percentile value of numeric
+ column `col` at the given percentage. The value of percentage must
be between 0.0
+ and 1.0. The `accuracy` parameter (default: 1) is a positive
integer literal which
+ controls approximation accuracy at the cost of memory. Higher value
of `accuracy` yields
+ better accuracy, `1.0/accuracy` is the relative error of the
approximation.
+
+ _FUNC_(col, array(percentage1 [, percentage2]...) [, accuracy]) -
Returns the approximate
+ percentile array of column `col` at the given percentage array. Each
value of the
+ percentage array must be between 0.0 and 1.0. The `accuracy`
parameter (default: 1) is
+ a positive integer literal which controls approximation accuracy at
the cost of memory.
+ Higher value of `accuracy` yields better accuracy, `1.0/accuracy`
is the relative error of
+ the approximation.
+""")
+case class ApproximatePercentile(
+child: Expression,
+percentageExpression: Expression,
+accuracyExpression: Expression,
+override val mutableAggBufferOffset: Int,
+override val inputAggBufferOffset: Int) extends
TypedImperativeAggregate[PercentileDigest] {
+
+ def this(child: Expression, percentageExpression: Expression,
accuracyExpression: Expression) = {
+this(child, percentageExpression, accuracyExpression, 0, 0)
+ }
+
+ def this(child: Expression, percentageExpression: Expression) = {
+this(child, percentageExpression,
Literal(ApproximatePercentile.DEFAULT_PERCENTILE_ACCURACY))
+ }
+
+ // Mark as lazy so that accuracyExpression is not evaluated during tree
transformation.
+ private lazy va
[GitHub] spark pull request #14868: [SPARK-16283][SQL] Implements percentile_approx a...
Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/14868#discussion_r77114139
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/ApproximatePercentile.scala
---
@@ -0,0 +1,321 @@
+/*
+ * 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.nio.ByteBuffer
+
+import com.google.common.primitives.{Doubles, Ints, Longs}
+
+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.analysis.TypeCheckResult.{TypeCheckFailure,
TypeCheckSuccess}
+import org.apache.spark.sql.catalyst.expressions._
+import
org.apache.spark.sql.catalyst.expressions.aggregate.ApproximatePercentile.{PercentileDigest}
+import org.apache.spark.sql.catalyst.util.{ArrayData, GenericArrayData}
+import org.apache.spark.sql.catalyst.util.QuantileSummaries
+import
org.apache.spark.sql.catalyst.util.QuantileSummaries.{defaultCompressThreshold,
Stats}
+import org.apache.spark.sql.types._
+
+/**
+ * The ApproximatePercentile function returns the approximate
percentile(s) of a column at the given
+ * percentage(s). A percentile is a watermark value below which a given
percentage of the column
+ * values fall. For example, the percentile of column `col` at percentage
50% is the median of
+ * column `col`.
+ *
+ * This function supports partial aggregation.
+ *
+ * @param child child expression that can produce 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 between
+ * 0.0 and 1.0.
+ * @param accuracyExpression Integer literal expression of approximation
accuracy. Higher value
+ * yields better accuracy, the default value is
+ * DEFAULT_PERCENTILE_ACCURACY.
+ */
+@ExpressionDescription(
+ usage =
+"""
+ _FUNC_(col, percentage [, accuracy]) - Returns the approximate
percentile value of numeric
+ column `col` at the given percentage. The value of percentage must
be between 0.0
+ and 1.0. The `accuracy` parameter (default: 1) is a positive
integer literal which
+ controls approximation accuracy at the cost of memory. Higher value
of `accuracy` yields
+ better accuracy, `1.0/accuracy` is the relative error of the
approximation.
+
+ _FUNC_(col, array(percentage1 [, percentage2]...) [, accuracy]) -
Returns the approximate
+ percentile array of column `col` at the given percentage array. Each
value of the
+ percentage array must be between 0.0 and 1.0. The `accuracy`
parameter (default: 1) is
+ a positive integer literal which controls approximation accuracy at
the cost of memory.
+ Higher value of `accuracy` yields better accuracy, `1.0/accuracy`
is the relative error of
+ the approximation.
+""")
+case class ApproximatePercentile(
+child: Expression,
+percentageExpression: Expression,
+accuracyExpression: Expression,
+override val mutableAggBufferOffset: Int,
+override val inputAggBufferOffset: Int) extends
TypedImperativeAggregate[PercentileDigest] {
+
+ def this(child: Expression, percentageExpression: Expression,
accuracyExpression: Expression) = {
+this(child, percentageExpression, accuracyExpression, 0, 0)
+ }
+
+ def this(child: Expression, percentageExpression: Expression) = {
+this(child, percentageExpression,
Literal(ApproximatePercentile.DEFAULT_PERCENTILE_ACCURACY))
+ }
+
+ // Mark as lazy so that accuracyExpression is not evaluated during tree
transformation.
+ private lazy va
