[ https://issues.apache.org/jira/browse/SPARK-24406?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Hyukjin Kwon resolved SPARK-24406. ---------------------------------- Resolution: Incomplete > Exposing custom spark scala ml transformers in pyspark > ------------------------------------------------------- > > Key: SPARK-24406 > URL: https://issues.apache.org/jira/browse/SPARK-24406 > Project: Spark > Issue Type: Question > Components: ML, MLlib > Affects Versions: 2.3.0 > Reporter: Pratyush Sharma > Priority: Minor > Labels: bulk-closed > > How can I use a custom transformer written in scala in a pyspark pipeline. > {code:java} > class UpperTransformer(override val uid: String) > extends UnaryTransformer[String, String, UpperTransformer] { > > def this() = this(Identifiable.randomUID("upper")) > > override protected def validateInputType(inputType: DataType): Unit = { > require(inputType == StringType) > } > > protected def createTransformFunc: String => String = { > _.toUpperCase > } > > protected def outputDataType: DataType = StringType > }{code} > > Use this transformer in pyspark pipeline. -- This message was sent by Atlassian Jira (v8.3.4#803005) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org