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https://issues.apache.org/jira/browse/SPARK-14938?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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zhengruifeng closed SPARK-14938.
--------------------------------
Resolution: Not A Problem
> Use Datasets.as to improve internal implementation
> --------------------------------------------------
>
> Key: SPARK-14938
> URL: https://issues.apache.org/jira/browse/SPARK-14938
> Project: Spark
> Issue Type: Improvement
> Components: ML
> Reporter: zhengruifeng
>
> As discussed in [https://github.com/apache/spark/pull/11915], we can use
> {{Dataset.as}} API instead of RDD operations.
> From:
> {code}
> dataset.select(col($(labelCol)).cast(DoubleType), f, w).rdd.map {
> case Row(label: Double, feature: Double, weight: Double) =>
> (label, feature, weight)
> }
> {code}
> To:
> {code}
> dataset.select(col($(labelCol)).cast(DoubleType), f, w)
> .as[(Double, Double, Double)].rdd
> {code}
> From:
> {code}
> dataset.select(col($(featuresCol)), col($(labelCol)).cast(DoubleType),
> col($(censorCol)))
> .rdd.map {
> case Row(features: Vector, label: Double, censor: Double) =>
> AFTPoint(features, label, censor)
> }
> {code}
> To:
> {code}
> val sqlContext = dataset.sqlContext
> import sqlContext.implicits._
> dataset.select(col($(featuresCol)).as("features"),
> col($(labelCol)).cast(DoubleType).as("label"),
> col($(censorCol)).as("censor")).as[AFTPoint].rdd
> {code}
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