Greenplum Analytic Functions and Windowing

Greenplum Database supports analytic functions and windowing functions, which are powerful features for performing advanced analytical and statistical operations on data within a specified window or partition. Analytic functions operate on a set of rows related to the current row and are applied across a specific range of rows defined by the OVER() clause.

Here's an overview of Greenplum's support for analytic functions and windowing:

 Analytic Functions:

1. Common Analytic Functions:

   - Greenplum supports a variety of common analytic functions, including but not limited to:

     - SUM(): Calculates the sum of a numeric column.

     - AVG(): Calculates the average of a numeric column.

     - ROW_NUMBER(): Assigns a unique integer to each row within a partition.

     - RANK(): Assigns a rank to each row within a partition, with ties receiving the same rank.

2. Windowing Clause:

   - The windowing clause is specified using the OVER() clause and defines the window or partition of rows on which the analytic function operates. It can include the PARTITION BY and ORDER BY clauses to define the grouping and ordering of rows within the window.

   

   SELECT

     column1,

     column2,

     SUM(column3) OVER (PARTITION BY column1 ORDER BY column2) AS running_total

   FROM your_table;

   

3. PARTITION BY:

   - The PARTITION BY clause divides the result set into partitions to which the analytic function is applied. Analytic functions are then computed for each partition separately.

   

   SELECT

     column1,

     column2,

     AVG(column3) OVER (PARTITION BY column1) AS avg_per_partition

   FROM your_table;

   

4. ORDER BY:

   - The ORDER BY clause specifies the sort order of the rows within each partition. It determines the sequence in which the analytic function is applied.

   

   SELECT

     column1,

     column2,

     ROW_NUMBER() OVER (PARTITION BY column1 ORDER BY column2) AS row_num

   FROM your_table;

   

 Windowing Functions:

1. Window Frame Specification:

   - The window frame defines the range of rows within the partition over which the analytic function operates. It can be specified using ROWS BETWEEN or RANGE BETWEEN clauses.

   

   SELECT

     column1,

     column2,

     SUM(column3) OVER (PARTITION BY column1 ORDER BY column2 ROWS BETWEEN 1 PRECEDING AND 1 FOLLOWING) AS sum_window

   FROM your_table;

   

2. ROWS BETWEEN:

   - The ROWS BETWEEN clause specifies a range of rows relative to the current row. For example, ROWS BETWEEN 1 PRECEDING AND 1 FOLLOWING includes the current row and its neighboring rows.

3. RANGE BETWEEN:

   - The RANGE BETWEEN clause specifies a range of values relative to the value of the current row. It is applicable to ordered data where the ordering column is numeric.

   

   SELECT

     column1,

     column2,

     AVG(column3) OVER (ORDER BY column2 RANGE BETWEEN 10 PRECEDING AND 10 FOLLOWING) AS avg_range

   FROM your_table;

   

Greenplum's support for analytic functions and windowing provides a flexible and efficient way to perform complex analyses and aggregations within partitions or specified windows. The choice of functions and window specifications depends on the specific analytical requirements of your queries.

Always refer to the official Greenplum documentation for your specific version for detailed information on supported functions and windowing capabilities.