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https://issues.apache.org/jira/browse/SPARK-21483?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16094607#comment-16094607
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Aseem Bansal commented on SPARK-21483:
--------------------------------------
Some pseudo code to show what I am trying to achieve
{code:java}
class MyTransformer implemenets Serializable {
public FeaturesAndLabel transform(RawData rawData) {
//Some logic which creates Features and Labels from raw data
//FeaturesAndLabel is a bean which contains a SparseVector as
features, and double as label
}
}
{code}
{code:java}
Dataset<RawData> dataset = //read from somewhere and create Dataset of RawData
bean
Dataset<FeaturesAndLabel> featuresAndLabels = dataset.transform(new
MyTransformer()::transform)
//use features and labels for machine learning
{code}
> Make org.apache.spark.ml.linalg.Vector bean-compliant so it can be used in
> Encoders.bean(Vector.class)
> ------------------------------------------------------------------------------------------------------
>
> Key: SPARK-21483
> URL: https://issues.apache.org/jira/browse/SPARK-21483
> Project: Spark
> Issue Type: Improvement
> Components: ML
> Affects Versions: 2.1.0
> Reporter: Aseem Bansal
> Priority: Minor
>
> The class org.apache.spark.ml.linalg.Vector is currently not bean-compliant
> as per spark.
> This makes it impossible to create a Vector via a dataset.tranform. It should
> be made bean-compliant so it can be used.
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