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https://issues.apache.org/jira/browse/CALCITE-4522?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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hqx updated CALCITE-4522:
-------------------------
    Description: 
The old method to compute the cost of sort has some problem.
 # when there is no need to sort, it still to compute the cpu cost of sort.
 # use n * log(n)rowBytes to estimate the cpu cost may be inaccurate, where n 
means the output row count of the sort operator, and rowBytes means the average 
bytes of one row .

Instead, I give follow suggestion.
 # the cpu cost is zero if there is no need to sort.
 # use m * log(n) rowBytes to compute the cpu cost, where m is the sum of 
offset + limit and n means input row count.

  was:
The old method to compute the cost of sort has some problem.
 # when there is no need to sort, it still to compute the cpu cost of sort.
 # use n * log(n) rowBytes to estimate the cpu cost may be inaccurate, where n 
means the output row count of the sort operator, and rowBytes means the average 
bytes of one row .

Instead, I give follow suggestion.
 # the cpu cost is zero if there is no need to sort.
 # use m * log(n) rowBytes to compute the cpu cost, where m is the sum of 
offset + limit and n means input row count.


> optimize sort cost formula
> --------------------------
>
>                 Key: CALCITE-4522
>                 URL: https://issues.apache.org/jira/browse/CALCITE-4522
>             Project: Calcite
>          Issue Type: Improvement
>          Components: core
>            Reporter: hqx
>            Priority: Minor
>
> The old method to compute the cost of sort has some problem.
>  # when there is no need to sort, it still to compute the cpu cost of sort.
>  # use n * log(n)rowBytes to estimate the cpu cost may be inaccurate, where n 
> means the output row count of the sort operator, and rowBytes means the 
> average bytes of one row .
> Instead, I give follow suggestion.
>  # the cpu cost is zero if there is no need to sort.
>  # use m * log(n) rowBytes to compute the cpu cost, where m is the sum of 
> offset + limit and n means input row count.



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