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With PostgreSQL 9.4 everything is reduced to a single SQL command, resulting in significant advantages in terms of readability of the scripts and execution of the commands: Until now, this was only possible by dividing the numbers into 4 sets via the OVER (PARTITION BY/ORDER BY) clause, then order them internally into 4 ordered subsets from which to then take the maximum value – for example, by using a CTE: $ CREATE TABLE t AS SELECT generate_series(1,20) AS val

To better clarify the situation, let’s say, for example, that we want to calculate the 25th, the 50th, the 75th and the 100th percentile of the first 20 integers. rank(), dense_rank(), percent_rank(), cume_dist(): window functions already available in PostgreSQL to be executed on the subsets obtained using the OVER (PARTITION BY/ORDER BY) clause and now able to take as a parameter ordered subsets produced by the WITHIN GROUP clause.mode() a statistical function that calculates the mode on ordered.percentile_cont(), percentile_disc() for the calculation of.In addition, new functions were introduced that can be applied to these subsets and expand the collection of available window With version 9.4 of PostgreSQL the SQL WITHIN GROUP clause was introduced: this simplified many operations that had previously only been possible with the use of the window functions, defining aggregations of ordered subsets of data.

PostgreSQL introduced window functions since version 9.0 in order to work on subsets of data that can be correlated to each current record of tables, defining a sort of “aggregates” centred on any specific record as the query is gradually executed via the SQL OVER(PARTITION BY/ORDER BY) clause and by using the functions that can be performed on those aggregations. The WITHIN GROUP clause is particularly useful when performing aggregations on ordered subsets of data. PostgreSQL 9.4 extends the SQL standard by inserting two new clauses that facilitate many operations required during the development of applications: the WITHIN GROUP and FILTER clauses.