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Date: Mon, 2 Nov 2015 23:57:27 +0000 (UTC)
From: "Deneche A. Hakim (JIRA)" <jira@apache.org>
To: issues@drill.apache.org
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Subject: [jira] [Updated] (DRILL-3952) Improve Window Functions performance
 when not all batches are required to process the current batch
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     [ https://issues.apache.org/jira/browse/DRILL-3952?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Deneche A. Hakim updated DRILL-3952:
------------------------------------
    Assignee: Aman Sinha  (was: Deneche A. Hakim)

> Improve Window Functions performance when not all batches are required to process the current batch
> ---------------------------------------------------------------------------------------------------
>
>                 Key: DRILL-3952
>                 URL: https://issues.apache.org/jira/browse/DRILL-3952
>             Project: Apache Drill
>          Issue Type: Bug
>          Components: Execution - Relational Operators
>    Affects Versions: 1.2.0
>            Reporter: Deneche A. Hakim
>            Assignee: Aman Sinha
>             Fix For: 1.3.0
>
>
> Currently, the window operator blocks until all batches of current partition to be available. For some queries it's necessary (e.g. aggregate with no order-by in the window definition), but for other cases the window operator can process and pass the current batch downstream sooner.
> Implementing this should help the window operator use less memory and run faster, especially in the presence of a limit operator.
> The purpose of this JIRA is to improve the window operator in the following cases:
> - aggregate, when order-by clause is available in window definition, can process current batch as soon as it receives the last peer row
> - lead can process current batch as soon as it receives 1 more batch
> - lag can process current batch immediately
> - first_value can process current batch immediately
> - last_value, when order-by clause is available in window definition, can process current batch as soon as it receives the last peer row
> - row_number, rank and dense_rank can process current batch immediately 


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