Window Functions

    A frame is one of:

    frame_start and frame_end can be any of:

    The window definition has 3 components:

    • The PARTITION BY clause separates the input rows into different partitions. This is analogous to how the GROUP BY clause separates rows into different groups for aggregate functions. If PARTITION BY is not specified, the entire input is treated as a single partition.

    • The frame clause specifies the sliding window of rows to be processed by the function for a given input row. A frame can be ROWS type or RANGE type, and it runs from frame_start to frame_end. If frame_end is not specified, a default value of CURRENT ROW is used.

      In ROWS mode, CURRENT ROW refers specifically to the current row. In RANGE mode, CURRENT ROW refers to any peer row of the current row for the purpose of the . If no ORDER BY is specified, all rows are considered peers of the current row. In RANGE mode a frame start of CURRENT ROW refers to the first peer row of the current row, while a frame end of CURRENT ROW refers to the last peer row of the current row.

      Frame starts and ends of expression PRECEDING or expression FOLLOWING are currently only allowed in ROWS mode. They define the start or end of the frame as the specified number of rows before or after the current row. The expression must be of type INTEGER.

      If no frame is specified, a default frame of RANGE UNBOUNDED PRECEDING is used.

    The following query ranks orders for each clerk by price:

    All Aggregate Functions can be used as window functions by adding the OVER clause. The aggregate function is computed for each row over the rows within the current row’s window frame.

    cume_dist() → bigint

    Returns the cumulative distribution of a value in a group of values. The result is the number of rows preceding or peer with the row in the window ordering of the window partition divided by the total number of rows in the window partition. Thus, any tie values in the ordering will evaluate to the same distribution value.

    dense_rank() → bigint

    Returns the rank of a value in a group of values. This is similar to , except that tie values do not produce gaps in the sequence.

    ntile(n) → bigint

    Divides the rows for each window partition into n buckets ranging from 1 to at most n. Bucket values will differ by at most 1. If the number of rows in the partition does not divide evenly into the number of buckets, then the remainder values are distributed one per bucket, starting with the first bucket.

    For example, with 6 rows and 4 buckets, the bucket values would be as follows: 1 1 2 2 4

    percent_rank() → double

    Returns the percentage ranking of a value in group of values. The result is (r - 1) / (n - 1) where r is the rank() of the row and n is the total number of rows in the window partition.

    rank() → bigint

    Returns the rank of a value in a group of values. The rank is one plus the number of rows preceding the row that are not peer with the row. Thus, tie values in the ordering will produce gaps in the sequence. The ranking is performed for each window partition.

    Returns a unique, sequential number for each row, starting with one, according to the ordering of rows within the window partition.

    Value functions provide an option to specify how null values should be treated when evaluating the function. Nulls can either be ignored (IGNORE NULLS) or respected (RESPECT NULLS). By default, null values are respected. If IGNORE NULLS is specified, all rows where the value expression is null are excluded from the calculation. If IGNORE NULLS is specified and the value expression is null for all rows, the default_value is returned, or if it is not specified, null is returned.

    first_value(x) → [same as input]

    Returns the first value of the window.

    last_value(x) → [same as input]

    Returns the last value of the window.

    nth_value(x, offset) → [same as input]

    Returns the value at the specified offset from beginning the window. Offsets start at 1. The offset can be any scalar expression. If the offset is null or greater than the number of values in the window, null is returned. It is an error for the offset to be zero or negative.

    lead(x[, offset[, default_value]]) → [same as input]

    Returns the value at offset rows after the current row in the window. Offsets start at 0, which is the current row. The offset can be any scalar expression. The default offset is 1. If the offset is null or larger than the window, the default_value is returned, or if it is not specified null is returned.

    lag(x[, offset[, default_value]]) → [same as input]