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/*
* 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.expressions
import org.apache.spark.annotation.Experimental
import org.apache.spark.sql.{catalyst, Column}
import org.apache.spark.sql.catalyst.expressions._
/**
* :: Experimental ::
* A window specification that defines the partitioning, ordering, and frame boundaries.
*
* Use the static methods in [[Window]] to create a [[WindowSpec]].
*
* @since 1.4.0
*/
@Experimental
class WindowSpec private[sql](
partitionSpec: Seq[Expression],
orderSpec: Seq[SortOrder],
frame: catalyst.expressions.WindowFrame) {
/**
* Defines the partitioning columns in a [[WindowSpec]].
* @since 1.4.0
*/
@scala.annotation.varargs
def partitionBy(colName: String, colNames: String*): WindowSpec = {
partitionBy((colName +: colNames).map(Column(_)): _*)
}
/**
* Defines the partitioning columns in a [[WindowSpec]].
* @since 1.4.0
*/
@scala.annotation.varargs
def partitionBy(cols: Column*): WindowSpec = {
new WindowSpec(cols.map(_.expr), orderSpec, frame)
}
/**
* Defines the ordering columns in a [[WindowSpec]].
* @since 1.4.0
*/
@scala.annotation.varargs
def orderBy(colName: String, colNames: String*): WindowSpec = {
orderBy((colName +: colNames).map(Column(_)): _*)
}
/**
* Defines the ordering columns in a [[WindowSpec]].
* @since 1.4.0
*/
@scala.annotation.varargs
def orderBy(cols: Column*): WindowSpec = {
val sortOrder: Seq[SortOrder] = cols.map { col =>
col.expr match {
case expr: SortOrder =>
expr
case expr: Expression =>
SortOrder(expr, Ascending)
}
}
new WindowSpec(partitionSpec, sortOrder, frame)
}
/**
* Defines the frame boundaries, from `start` (inclusive) to `end` (inclusive).
*
* Both `start` and `end` are relative positions from the current row. For example, "0" means
* "current row", while "-1" means the row before the current row, and "5" means the fifth row
* after the current row.
*
* @param start boundary start, inclusive.
* The frame is unbounded if this is the minimum long value.
* @param end boundary end, inclusive.
* The frame is unbounded if this is the maximum long value.
* @since 1.4.0
*/
def rowsBetween(start: Long, end: Long): WindowSpec = {
between(RowFrame, start, end)
}
/**
* Defines the frame boundaries, from `start` (inclusive) to `end` (inclusive).
*
* Both `start` and `end` are relative from the current row. For example, "0" means "current row",
* while "-1" means one off before the current row, and "5" means the five off after the
* current row.
*
* @param start boundary start, inclusive.
* The frame is unbounded if this is the minimum long value.
* @param end boundary end, inclusive.
* The frame is unbounded if this is the maximum long value.
* @since 1.4.0
*/
def rangeBetween(start: Long, end: Long): WindowSpec = {
between(RangeFrame, start, end)
}
private def between(typ: FrameType, start: Long, end: Long): WindowSpec = {
val boundaryStart = start match {
case 0 => CurrentRow
case Long.MinValue => UnboundedPreceding
case x if x < 0 => ValuePreceding(-start.toInt)
case x if x > 0 => ValueFollowing(start.toInt)
}
val boundaryEnd = end match {
case 0 => CurrentRow
case Long.MaxValue => UnboundedFollowing
case x if x < 0 => ValuePreceding(-end.toInt)
case x if x > 0 => ValueFollowing(end.toInt)
}
new WindowSpec(
partitionSpec,
orderSpec,
SpecifiedWindowFrame(typ, boundaryStart, boundaryEnd))
}
/**
* Converts this [[WindowSpec]] into a [[Column]] with an aggregate expression.
*/
private[sql] def withAggregate(aggregate: Column): Column = {
val spec = WindowSpecDefinition(partitionSpec, orderSpec, frame)
new Column(WindowExpression(aggregate.expr, spec))
}
}
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