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From "Eric Hanson (JIRA)" <>
Subject [jira] [Commented] (HIVE-4160) Vectorized Query Execution in Hive
Date Thu, 09 May 2013 22:33:17 GMT


Eric Hanson commented on HIVE-4160:

Updated design document with discussion of precise handling and interpretation of all-non-null
(noNulls) and all identical (isRepeating) column vectors. 

Also included discussion of TIMESTAMP internal vector representation as long integer number
of nonseconds since the epoch.
> Vectorized Query Execution in Hive
> ----------------------------------
>                 Key: HIVE-4160
>                 URL:
>             Project: Hive
>          Issue Type: New Feature
>            Reporter: Jitendra Nath Pandey
>            Assignee: Jitendra Nath Pandey
>         Attachments: Hive-Vectorized-Query-Execution-Design.docx, Hive-Vectorized-Query-Execution-Design-rev2.docx,
Hive-Vectorized-Query-Execution-Design-rev3.docx, Hive-Vectorized-Query-Execution-Design-rev3.docx,
Hive-Vectorized-Query-Execution-Design-rev3.pdf, Hive-Vectorized-Query-Execution-Design-rev4.docx,
Hive-Vectorized-Query-Execution-Design-rev4.pdf, Hive-Vectorized-Query-Execution-Design-rev5.docx,
> The Hive query execution engine currently processes one row at a time. A single row of
data goes through all the operators before the 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 X100]. Also currently Hive heavily relies on lazy deserialization
and data columns go through a layer of object inspectors that identify column type, deserialize
data and determine appropriate expression routines in the inner loop. These layers of virtual
method calls further slow down the processing. 
> This work will add support for vectorized query execution to Hive, where, instead of
individual rows, batches of about a thousand rows at a time are processed. Each column in
the batch is represented as a vector of a primitive data type. The inner loop of execution
scans these vectors very fast, avoiding method calls, deserialization, unnecessary if-then-else,
etc. This substantially reduces CPU time used, and gives excellent instructions per cycle
(i.e. improved processor pipeline utilization). See the attached design specification for
more details.

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