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From "Hyunsik Choi (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (TAJO-104) JIT Query Compilation and Vectorized Engine (Umbrella)
Date Mon, 09 Dec 2013 16:08:08 GMT

     [ https://issues.apache.org/jira/browse/TAJO-104?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel

Hyunsik Choi updated TAJO-104:

    Fix Version/s:     (was: 0.8-incubating)

> JIT Query Compilation and Vectorized Engine (Umbrella)
> ------------------------------------------------------
>                 Key: TAJO-104
>                 URL: https://issues.apache.org/jira/browse/TAJO-104
>             Project: Tajo
>          Issue Type: New Feature
>          Components: physical operator, worker
>            Reporter: Hyunsik Choi
>              Labels: vectorization
> In these days, it's unnecessary to say the advantages of columnar store and vectorized
processing on analytic workloads. These approaches are well known as the state-of-the-art
techniques in database community and are also acceptable in practical areas.
> Since we started Tajo project in 2010 year, we have planed the new engine using both
JIT query compilation and vectorized engine. My colleagues and I have surveyed columnar store,
vectorized processing, cache conscious techniques, and query compilation.
> In this issue, we will design and implement the new engine. The key implementation plan
is as follows:
> * Implemented in C++
> * Vectorization primitives will be generated by LLVM.
> * Two or more primitives by using JIT can be blurred according to the situation.
> This is an umbrella issue, and we will create lots of subtasks for this issue.
> The design references are as follows:
> * DSM vs. NSM: CPU Performance Tradeoffs in Block-Oriented Query Processing.
> * Efficiently Compiling Efficient Query Plans for Modern Hardware
> * Just-in-time Compilation in Vectorized Query Execution
> * MonetDB/X100: Hyper-Pipelining Query Execution
> * Column-Stores vs. Row-Stores: How Different Are They Really?
> * Balancing vectorized query execution with bandwidth-optimized storage

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