[jira] [Commented] (SPARK-11569) StringIndexer transform fails when column contains nulls

["Apache Spark (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-11569?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15904448#comment-15904448 ] 

Apache Spark commented on SPARK-11569:
--------------------------------------

User 'crackcell' has created a pull request for this issue:
https://github.com/apache/spark/pull/17233

> StringIndexer transform fails when column contains nulls
> --------------------------------------------------------
>
>                 Key: SPARK-11569
>                 URL: https://issues.apache.org/jira/browse/SPARK-11569
>             Project: Spark
>          Issue Type: Bug
>          Components: ML, PySpark
>    Affects Versions: 1.4.0, 1.5.0, 1.6.0
>            Reporter: Maciej Szymkiewicz
>
> Transforming column containing {{null}} values using {{StringIndexer}} results in {{java.lang.NullPointerException}}
> {code}
> from pyspark.ml.feature import StringIndexer
> df = sqlContext.createDataFrame([("a", 1), (None, 2)], ("k", "v"))
> df.printSchema()
> ## root
> ##  |-- k: string (nullable = true)
> ##  |-- v: long (nullable = true)
> indexer = StringIndexer(inputCol="k", outputCol="kIdx")
> indexer.fit(df).transform(df)
> ## <repr(<pyspark.sql.dataframe.DataFrame at 0x7f4b0d8e7110>) failed: py4j.protocol.Py4JJavaError: An error occurred while calling o75.json.
> ## : java.lang.NullPointerException
> {code}
> Problem disappears when we drop 
> {code}
> df1 = df.na.drop()
> indexer.fit(df1).transform(df1)
> {code}
> or replace {{nulls}}
> {code}
> from pyspark.sql.functions import col, when
> k = col("k")
> df2 = df.withColumn("k", when(k.isNull(), "__NA__").otherwise(k))
> indexer.fit(df2).transform(df2)
> {code}
> and cannot be reproduced using Scala API
> {code}
> import org.apache.spark.ml.feature.StringIndexer
> val df = sc.parallelize(Seq(("a", 1), (null, 2))).toDF("k", "v")
> df.printSchema
> // root
> //  |-- k: string (nullable = true)
> //  |-- v: integer (nullable = false)
> val indexer = new StringIndexer().setInputCol("k").setOutputCol("kIdx")
> indexer.fit(df).transform(df).count
> // 2
> {code}



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