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https://issues.apache.org/jira/browse/SPARK-15230?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15285302#comment-15285302
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Bo Meng commented on SPARK-15230:
---------------------------------
In the description, `it does not work for describe()` should be `it does not
work for distinct()`, please update the description, thanks.
> Back quoted column with dot in it fails when running distinct on dataframe
> --------------------------------------------------------------------------
>
> Key: SPARK-15230
> URL: https://issues.apache.org/jira/browse/SPARK-15230
> Project: Spark
> Issue Type: Bug
> Components: Examples
> Affects Versions: 1.6.0
> Reporter: Barry Becker
>
> When working with a dataframe columns with .'s in them must be backquoted
> (``) or the column name will not be found. This works for most dataframe
> methods, but I discovered that it does not work for describe().
> Suppose you have a dataFrame, testDf, with a DoubleType column named
> {{pos.NoZero}}. This statememt:
> {noformat}
> testDf.select(new Column("`pos.NoZero`")).distinct().collect().mkString(", ")
> {noformat}
> will fail with this error:
> {noformat}
> org.apache.spark.sql.AnalysisException: Cannot resolve column name
> "pos.NoZero" among (pos.NoZero);
> at
> org.apache.spark.sql.DataFrame$$anonfun$resolve$1.apply(DataFrame.scala:152)
> at
> org.apache.spark.sql.DataFrame$$anonfun$resolve$1.apply(DataFrame.scala:152)
> at scala.Option.getOrElse(Option.scala:121)
> at org.apache.spark.sql.DataFrame.resolve(DataFrame.scala:151)
> at
> org.apache.spark.sql.DataFrame$$anonfun$dropDuplicates$1$$anonfun$40.apply(DataFrame.scala:1329)
> at
> org.apache.spark.sql.DataFrame$$anonfun$dropDuplicates$1$$anonfun$40.apply(DataFrame.scala:1329)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:245)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:245)
> at
> scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
> at scala.collection.mutable.WrappedArray.foreach(WrappedArray.scala:35)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:245)
> at scala.collection.AbstractTraversable.map(Traversable.scala:104)
> at
> org.apache.spark.sql.DataFrame$$anonfun$dropDuplicates$1.apply(DataFrame.scala:1329)
> at
> org.apache.spark.sql.DataFrame$$anonfun$dropDuplicates$1.apply(DataFrame.scala:1328)
> at
> org.apache.spark.sql.DataFrame.org$apache$spark$sql$DataFrame$$withPlan(DataFrame.scala:2165)
> at org.apache.spark.sql.DataFrame.dropDuplicates(DataFrame.scala:1328)
> at org.apache.spark.sql.DataFrame.dropDuplicates(DataFrame.scala:1348)
> at org.apache.spark.sql.DataFrame.dropDuplicates(DataFrame.scala:1319)
> at org.apache.spark.sql.DataFrame.distinct(DataFrame.scala:1612)
> at
> com.mineset.spark.vizagg.selection.SelectionExpressionSuite$$anonfun$40.apply$mcV$sp(SelectionExpressionSuite.scala:317)
> {noformat}
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