WindowSpec — Window Specification

WindowSpec is a window specification that defines which rows are included in a window (frame), i.e. the set of rows that are associated with the current row by some relation.

WindowSpec takes the following when created:

Partition specification (Seq[Expression]) which defines which records are in the same partition. With no partition defined, all records belong to a single partition
Ordering Specification (Seq[SortOrder]) which defines how records in a partition are ordered that in turn defines the position of a record in a partition. The ordering could be ascending (ASC in SQL or asc in Scala) or descending (DESC or desc).
Frame Specification (WindowFrame) which defines the rows to be included in the frame for the current row, based on their relative position to the current row. For example, "the three rows preceding the current row to the current row" describes a frame including the current input row and three rows appearing before the current row.

You use Window object to create a WindowSpec.

import org.apache.spark.sql.expressions.Window
scala> val byHTokens = Window.partitionBy('token startsWith "h")
byHTokens: org.apache.spark.sql.expressions.WindowSpec = org.apache.spark.sql.expressions.WindowSpec@574985d8

Once the initial version of a WindowSpec is created, you use the methods to further configure the window specification.

Table 1. WindowSpec API
Method	Description
`orderBy`	`orderBy(cols: Column): WindowSpec orderBy(colName: String, colNames: String): WindowSpec`
`partitionBy`	`partitionBy(cols: Column): WindowSpec partitionBy(colName: String, colNames: String): WindowSpec`
`rangeBetween`	`rangeBetween(start: Column, end: Column): WindowSpec rangeBetween(start: Long, end: Long): WindowSpec`
`rowsBetween`	`rowsBetween(start: Long, end: Long): WindowSpec`

With a window specification fully defined, you use Column.over operator that associates the WindowSpec with an aggregate or window function.

scala> :type windowSpec
org.apache.spark.sql.expressions.WindowSpec

import org.apache.spark.sql.functions.rank
val c = rank over windowSpec

`withAggregate` Internal Method

withAggregate(aggregate: Column): Column

withAggregate…FIXME

Note	`withAggregate` is used exclusively when Column.over operator is used.

WindowSpec — Window Specification