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https://issues.apache.org/jira/browse/HIVE-4160?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13601558#comment-13601558
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Jitendra Nath Pandey commented on HIVE-4160:
--------------------------------------------

    This will be an incremental work in multiple phases with no regression on 
current system. We will publish a design/scope document very soon.
    The main idea behind the proposal is to transform the execution engine to 
process a row batch at a time instead of a single row. The row batch will 
consist of column vectors and each operator will process the whole column 
vector at a time. The column vector will consist of array(s) of primitive types 
as far as possible.
    The expressions will be implemented for various data types using 
pre-compiled templates. The appropriate expressions will be added to the 
operators based on data types.
    A vectorized iterator interface will be implemented by the file formats to 
provide vectorized input to the operator tree. 

                
> Vectorized Query Execution in Hive
> ----------------------------------
>
>                 Key: HIVE-4160
>                 URL: https://issues.apache.org/jira/browse/HIVE-4160
>             Project: Hive
>          Issue Type: New Feature
>            Reporter: Jitendra Nath Pandey
>            Assignee: Jitendra Nath Pandey
>
>   Hive query execution engine currently processes one row at a time. A single 
> row of data goes through all the operators before next row can be processed. 
> This mode of processing is very inefficient in terms of CPU usage. Research 
> has demonstrated that this yields very low instructions per cycle [MonetDB]. 
> Also currently hive heavily relies on lazy deserialization and data columns 
> go through a layer of object inspectors that identify column type, 
> de-serialize data and determine appropriate expression routines in the inner 
> loop. These layers of virtual method calls further slow down the processing.
> Reference: http://www-db.cs.wisc.edu/cidr/cidr2005/papers/P19.pdf

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