Package org.apache.spark.sql.expressions

Class Window

Object
org.apache.spark.sql.expressions.Window
public class Window extends Object
Utility functions for defining window in DataFrames. 


   // PARTITION BY country ORDER BY date ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW
   Window.partitionBy("country").orderBy("date")
     .rowsBetween(Window.unboundedPreceding, Window.currentRow)

   // PARTITION BY country ORDER BY date ROWS BETWEEN 3 PRECEDING AND 3 FOLLOWING
   Window.partitionBy("country").orderBy("date").rowsBetween(-3, 3)

Since:
1.4.0

  • Constructor Details

    • Window

      public Window()

  • Method Details

    • partitionBy

      public static WindowSpec partitionBy(String colName, String... colNames)
      Creates a WindowSpec with the partitioning defined.
      Parameters:
      colName - (undocumented)
      colNames - (undocumented)
      Returns:
      (undocumented)
      Since:
      1.4.0

    • partitionBy

      public static WindowSpec partitionBy(Column... cols)
      Creates a WindowSpec with the partitioning defined.
      Parameters:
      cols - (undocumented)
      Returns:
      (undocumented)
      Since:
      1.4.0

    • orderBy

      public static WindowSpec orderBy(String colName, String... colNames)
      Creates a WindowSpec with the ordering defined.
      Parameters:
      colName - (undocumented)
      colNames - (undocumented)
      Returns:
      (undocumented)
      Since:
      1.4.0

    • orderBy

      public static WindowSpec orderBy(Column... cols)
      Creates a WindowSpec with the ordering defined.
      Parameters:
      cols - (undocumented)
      Returns:
      (undocumented)
      Since:
      1.4.0

    • partitionBy

      public static WindowSpec partitionBy(String colName, scala.collection.immutable.Seq<String> colNames)
      Creates a WindowSpec with the partitioning defined.
      Parameters:
      colName - (undocumented)
      colNames - (undocumented)
      Returns:
      (undocumented)
      Since:
      1.4.0

    • partitionBy

      public static WindowSpec partitionBy(scala.collection.immutable.Seq<Column> cols)
      Creates a WindowSpec with the partitioning defined.
      Parameters:
      cols - (undocumented)
      Returns:
      (undocumented)
      Since:
      1.4.0

    • orderBy

      public static WindowSpec orderBy(String colName, scala.collection.immutable.Seq<String> colNames)
      Creates a WindowSpec with the ordering defined.
      Parameters:
      colName - (undocumented)
      colNames - (undocumented)
      Returns:
      (undocumented)
      Since:
      1.4.0

    • orderBy

      public static WindowSpec orderBy(scala.collection.immutable.Seq<Column> cols)
      Creates a WindowSpec with the ordering defined.
      Parameters:
      cols - (undocumented)
      Returns:
      (undocumented)
      Since:
      1.4.0

    • unboundedPreceding

      public static long unboundedPreceding()
      Value representing the first row in the partition, equivalent to "UNBOUNDED PRECEDING" in SQL. This can be used to specify the frame boundaries: 

      
   Window.rowsBetween(Window.unboundedPreceding, Window.currentRow)

      Returns:
      (undocumented)
      Since:
      2.1.0

    • unboundedFollowing

      public static long unboundedFollowing()
      Value representing the last row in the partition, equivalent to "UNBOUNDED FOLLOWING" in SQL. This can be used to specify the frame boundaries: 

      
   Window.rowsBetween(Window.unboundedPreceding, Window.unboundedFollowing)

      Returns:
      (undocumented)
      Since:
      2.1.0

    • currentRow

      public static long currentRow()
      Value representing the current row. This can be used to specify the frame boundaries: 

      
   Window.rowsBetween(Window.unboundedPreceding, Window.currentRow)

      Returns:
      (undocumented)
      Since:
      2.1.0

    • rowsBetween

      public static WindowSpec rowsBetween(long start, long end)
      Creates a WindowSpec with the frame boundaries defined, from start (inclusive) to end (inclusive).

      Both start and end are positions relative to 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.

      We recommend users use Window.unboundedPreceding, Window.unboundedFollowing, and Window.currentRow to specify special boundary values, rather than using integral values directly.

      A row based boundary is based on the position of the row within the partition. An offset indicates the number of rows above or below the current row, the frame for the current row starts or ends. For instance, given a row based sliding frame with a lower bound offset of -1 and a upper bound offset of +2. The frame for row with index 5 would range from index 4 to index 7. 

      
   import org.apache.spark.sql.expressions.Window
   val df = Seq((1, "a"), (1, "a"), (2, "a"), (1, "b"), (2, "b"), (3, "b"))
     .toDF("id", "category")
   val byCategoryOrderedById =
     Window.partitionBy($"category").orderBy($"id").rowsBetween(Window.currentRow, 1)
   df.withColumn("sum", sum($"id") over byCategoryOrderedById).show()

   +---+--------+---+
   | id|category|sum|
   +---+--------+---+
   |  1|       b|  3|
   |  2|       b|  5|
   |  3|       b|  3|
   |  1|       a|  2|
   |  1|       a|  3|
   |  2|       a|  2|
   +---+--------+---+

      Parameters:
      start - boundary start, inclusive. The frame is unbounded if this is the minimum long value (Window.unboundedPreceding).
      end - boundary end, inclusive. The frame is unbounded if this is the maximum long value (Window.unboundedFollowing).
      Returns:
      (undocumented)
      Since:
      2.1.0

    • rangeBetween

      public static WindowSpec rangeBetween(long start, long end)
      Creates a WindowSpec with the frame boundaries defined, from start (inclusive) to end (inclusive).

      Both start and end are relative to 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.

      We recommend users use Window.unboundedPreceding, Window.unboundedFollowing, and Window.currentRow to specify special boundary values, rather than using long values directly.

      A range-based boundary is based on the actual value of the ORDER BY expression(s). An offset is used to alter the value of the ORDER BY expression, for instance if the current ORDER BY expression has a value of 10 and the lower bound offset is -3, the resulting lower bound for the current row will be 10 - 3 = 7. This however puts a number of constraints on the ORDER BY expressions: there can be only one expression and this expression must have a numerical data type. An exception can be made when the offset is unbounded, because no value modification is needed, in this case multiple and non-numeric ORDER BY expression are allowed. 

      
   import org.apache.spark.sql.expressions.Window
   val df = Seq((1, "a"), (1, "a"), (2, "a"), (1, "b"), (2, "b"), (3, "b"))
     .toDF("id", "category")
   val byCategoryOrderedById =
     Window.partitionBy($"category").orderBy($"id").rangeBetween(Window.currentRow, 1)
   df.withColumn("sum", sum($"id") over byCategoryOrderedById).show()

   +---+--------+---+
   | id|category|sum|
   +---+--------+---+
   |  1|       b|  3|
   |  2|       b|  5|
   |  3|       b|  3|
   |  1|       a|  4|
   |  1|       a|  4|
   |  2|       a|  2|
   +---+--------+---+

      Parameters:
      start - boundary start, inclusive. The frame is unbounded if this is the minimum long value (Window.unboundedPreceding).
      end - boundary end, inclusive. The frame is unbounded if this is the maximum long value (Window.unboundedFollowing).
      Returns:
      (undocumented)
      Since:
      2.1.0