[jira] [Created] (SPARK-8816) Improve Performance of Unbounded Following Window Frame Processing

["Herman van Hovell tot Westerflier (JIRA)" <ji...@apache.org>]

Herman van Hovell tot Westerflier created SPARK-8816:
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             Summary: Improve Performance of Unbounded Following Window Frame Processing
                 Key: SPARK-8816
                 URL: https://issues.apache.org/jira/browse/SPARK-8816
             Project: Spark
          Issue Type: Sub-task
          Components: SQL
    Affects Versions: 1.4.0
            Reporter: Herman van Hovell tot Westerflier
            Priority: Minor


The performance of Unbounded Following frames in both the current and the proposed (SPARK-8638) implementation of Window Functions is quite bad: O(N*(N-1)/2).

A solution to this is to process such frames in reverse. This would effectively reduce the complexity to O(N). The problem with this approach that it assumes  that AggregateExpression are communitative. Most are, but some are actually order based: FIRST/LAST. There are two solution for this:
* Only allow communitative aggregates to processed in reverse order. In practice this would mean, that a white list containing all allowed aggregates  is used, e.g. Sum, Average, Min, Max, ...
* Add functionality to WindowFunction or even better AggregateExpression, which would allow us to get the reverse operator from the expression, and use this reverse for processing, for example:
{noformat}
case class Max(child: Expression) extends AggregateExpression with Ordered {
  ...
  
  def reverse: Min = Min(child)
}
{noformat}

The impact and extensibility of the first option are lower than of the second. 

We might also want to asses how often such frames are used. It might not be a problem at all.



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