[jira] [Updated] (SPARK-15230) Back quoted column with dot in it fails when running distinct on dataframe

2016-06-23 Thread Reynold Xin (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-15230?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Reynold Xin updated SPARK-15230:

Component/s: (was: Examples)
 SQL

> 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: SQL
>Affects Versions: 1.6.0
>Reporter: Barry Becker
>Assignee: Bo Meng
> Fix For: 2.0.1
>
>
> 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 distinct().
> 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}



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)

-
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org

[jira] [Updated] (SPARK-15230) Back quoted column with dot in it fails when running distinct on dataframe

2016-06-23 Thread Sean Owen (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-15230?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Sean Owen updated SPARK-15230:
--
Fix Version/s: (was: 2.0.0)
   2.0.1

[~cloud_fan] fix should be 2.0.1

> 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
>Assignee: Bo Meng
> Fix For: 2.0.1
>
>
> 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 distinct().
> 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}



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)

-
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org

[jira] [Updated] (SPARK-15230) Back quoted column with dot in it fails when running distinct on dataframe

2016-06-22 Thread Wenchen Fan (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-15230?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Wenchen Fan updated SPARK-15230:

Assignee: Bo Meng

> 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
>Assignee: Bo Meng
> Fix For: 2.0.0
>
>
> 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 distinct().
> 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}



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)

-
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org

[jira] [Updated] (SPARK-15230) Back quoted column with dot in it fails when running distinct on dataframe

2016-05-16 Thread Barry Becker (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-15230?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Barry Becker updated SPARK-15230:
-
Description: 
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 distinct().

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}


  was:
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}



> Back quoted column with dot in it fails when running distinct on dataframe
>

[jira] [Updated] (SPARK-15230) Back quoted column with dot in it fails when running distinct on dataframe

2016-05-09 Thread Herman van Hovell (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-15230?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Herman van Hovell updated SPARK-15230:
--
Description: 
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}


  was:
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:

testDf.select(new Column("`pos.NoZero`")).distinct().collect().mkString(", ")

will fail with this error:

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)




> Back quoted column with dot in it fails when running distinct on dataframe
>

[jira] [Updated] (SPARK-15230) Back quoted column with dot in it fails when running distinct on dataframe

2016-05-09 Thread Herman van Hovell (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-15230?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Herman van Hovell updated SPARK-15230:
--
Description: 
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}


  was:
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}



> Back quoted column with dot in it fails when running distinct on