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https://issues.apache.org/jira/browse/SPARK-61228?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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ASF GitHub Bot updated SPARK-61228:
-----------------------------------
    Labels: pull-request-available  (was: )

> Add a dedicated vector_to_array Catalyst expression
> ---------------------------------------------------
>
>                 Key: SPARK-61228
>                 URL: https://issues.apache.org/jira/browse/SPARK-61228
>             Project: Spark
>          Issue Type: Improvement
>          Components: ML
>    Affects Versions: 5.0.0
>            Reporter: Ruifeng Zheng
>            Priority: Major
>              Labels: pull-request-available
>
> The current vector_to_array implementation uses Scala UDFs that deserialize 
> vector objects. Add a dedicated Catalyst ML expression that accepts an input 
> expression and a target datatype (double or float), and accepts both a vector 
> SQL struct and any UDT whose underlying SQL type matches the vector schema.
> Use the expression in InternalFunctionRegistration and register 
> ml_vector_to_array in FunctionRegistry. Evaluate directly on Catalyst rows 
> and arrays in interpreted and generated execution, with coverage for dense, 
> sparse, empty, and matching-UDT inputs.
> Pull request: https://github.com/apache/spark/pull/60224



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