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https://issues.apache.org/jira/browse/TAJO-1344?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14385462#comment-14385462
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ASF GitHub Bot commented on TAJO-1344:
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Github user hyunsik commented on the pull request:
https://github.com/apache/tajo/pull/473#issuecomment-87281813
The patch looks good to me.
I have one suggestion. You make new EvalNode Type ```PYTHON_FUNCTION```.
But, it may be not matched to the design of EvalNode, and it will require
duplicated codes for EvalNode visitors.
You seem to do because Python function involcation is different from
existing Java function. I think that the best solution is to separate EvalNode
and Function Invocation code. In more detail, you should implement some
function invocation interface, and separate java function invocation and python
function invocation. Each function invocation implementation can be
initialized at the first function call, or you can use EvalNode::Bind(), being
addressed in TAJO-1436.
> Python UDF support
> ------------------
>
> Key: TAJO-1344
> URL: https://issues.apache.org/jira/browse/TAJO-1344
> Project: Tajo
> Issue Type: New Feature
> Components: function/udf
> Reporter: Hyunsik Choi
> Assignee: Jihoon Son
> Fix For: 0.11.0
>
> Attachments: TAJO-1344.patch, TAJO-1344_2.patch, TAJO-1344_3.patch,
> TAJO-1344_4.patch
>
>
> Python has abundant users and third-party libraries. This language is widely
> used in data analytic area. So, it would be great if Tajo supports Python UDF.
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