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https://issues.apache.org/jira/browse/SPARK-36770?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Guibin Zhang updated SPARK-36770:
---------------------------------
    Description: 
*Context*

The *UnboundedFollowingWindowFunctionFrame* has the time complexity of 
*O(N^2)*, N is the number of rows in the current partition, more specific the 
complexity is O(N* (N - 1)/2).

What happens internally in UnboundedFollowingWindowFunctionFrame:
 In the window frame, while processing each incoming row, it will go through 
current row till the end of partition to do re-calculation. This process will 
be repeated on each incoming row, which causes the high run-time complexity.

But UnboundedPrecedingWindowFunctionFrame has much better time complexity O(N), 
N is the number of rows in the current partition.

 

*What is the idea of the improvement?*

Give the big time complexity difference between 
UnboundedFollowingWindowFunctionFrame and 
UnboundedPrecedingWindowFunctionFrame, we can do following conversions to 
improve the time complexity of first() and last() from O(N^2) to O(N)
{code:java}
case 1:
first() OVER(PARTITION BY colA ORDER BY colB ASC ROWS UNBOUNDED FOLLOWING) 
converts to 
last()  OVER(PARTITION BY colA ORDER BY colB DEAC ROWS UNBOUNDED PRECEDING)

case 2:
last()  OVER(PARTITION BY colA ORDER BY colB ASC ROWS UNBOUNDED FOLLOWING) 
converts to 
first() OVER(PARTITION BY colA ORDER BY colB DESC ROWS UNBOUNDED PRECEDING)

{code}
 

*Summary*

Replace "UNBOUNDED FOLLOWING" with "UNBOUNDED PRECEDING", and flip the ORDER BY 
for the window functions first() and last() for ROWS.

 

 

  was:
*Context*

The *UnboundedFollowingWindowFunctionFrame* has the time complexity of 
*O(N^2)*, N is the number of rows in the current partition, more specific the 
complexity is O(N* (N - 1)/2).

What happens internally in UnboundedFollowingWindowFunctionFrame:
In the window frame, while processing each incoming row, it will go through 
current row till the end of partition to do re-calculation. This process will 
be repeated on each incoming row, which causes the high run-time complexity.

But UnboundedPrecedingWindowFunctionFrame has much better time complexity O(N), 
N is the number of rows in the current partition.

 

*What is the idea of the improvement?*

Give the big time complexity difference between 
UnboundedFollowingWindowFunctionFrame and 
UnboundedPrecedingWindowFunctionFrame, we can do following conversions to 
improve the time complexity of first() and last() from O(N^2) to O(N)
{code:java}
case 1:
first() OVER(PARTITION BY colA ORDER BY colB ASC ROWS UNBOUNDED FOLLOWING) 
converts to 
last()  OVER(PARTITION BY colA ORDER BY colB DEAC ROWS UNBOUNDED PRECEDING)

case 2:
last()  OVER(PARTITION BY colA ORDER BY colB ASC ROWS UNBOUNDED FOLLOWING) 
converts to 
first() OVER(PARTITION BY colA ORDER BY colB DESC ROWS UNBOUNDED PRECEDING)

{code}
 

*Summary*

Replace "UNBOUNDED FOLLOWING" with "UNBOUNDED PRECEDING", and flip the ORDER BY 
for the window functions first() and last().

 

 


> Improve run-time performance for window function first and last against 
> UnboundedFollowing window frame
> -------------------------------------------------------------------------------------------------------
>
>                 Key: SPARK-36770
>                 URL: https://issues.apache.org/jira/browse/SPARK-36770
>             Project: Spark
>          Issue Type: Improvement
>          Components: SQL
>    Affects Versions: 2.4.0, 3.1.2
>            Reporter: Guibin Zhang
>            Priority: Major
>
> *Context*
> The *UnboundedFollowingWindowFunctionFrame* has the time complexity of 
> *O(N^2)*, N is the number of rows in the current partition, more specific the 
> complexity is O(N* (N - 1)/2).
> What happens internally in UnboundedFollowingWindowFunctionFrame:
>  In the window frame, while processing each incoming row, it will go through 
> current row till the end of partition to do re-calculation. This process will 
> be repeated on each incoming row, which causes the high run-time complexity.
> But UnboundedPrecedingWindowFunctionFrame has much better time complexity 
> O(N), N is the number of rows in the current partition.
>  
> *What is the idea of the improvement?*
> Give the big time complexity difference between 
> UnboundedFollowingWindowFunctionFrame and 
> UnboundedPrecedingWindowFunctionFrame, we can do following conversions to 
> improve the time complexity of first() and last() from O(N^2) to O(N)
> {code:java}
> case 1:
> first() OVER(PARTITION BY colA ORDER BY colB ASC ROWS UNBOUNDED FOLLOWING) 
> converts to 
> last()  OVER(PARTITION BY colA ORDER BY colB DEAC ROWS UNBOUNDED PRECEDING)
> case 2:
> last()  OVER(PARTITION BY colA ORDER BY colB ASC ROWS UNBOUNDED FOLLOWING) 
> converts to 
> first() OVER(PARTITION BY colA ORDER BY colB DESC ROWS UNBOUNDED PRECEDING)
> {code}
>  
> *Summary*
> Replace "UNBOUNDED FOLLOWING" with "UNBOUNDED PRECEDING", and flip the ORDER 
> BY for the window functions first() and last() for ROWS.
>  
>  



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