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https://issues.apache.org/jira/browse/SPARK-8621?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14602094#comment-14602094
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Reynold Xin commented on SPARK-8621:
------------------------------------
That's one way to do it. The other way is to consider allowing empty (non-null,
but 0-char string) column names in analysis.
cc [~marmbrus] what do you think?
> crosstab exception when one of the value is empty
> -------------------------------------------------
>
> Key: SPARK-8621
> URL: https://issues.apache.org/jira/browse/SPARK-8621
> Project: Spark
> Issue Type: Sub-task
> Components: SQL
> Reporter: Reynold Xin
> Priority: Critical
>
> I think this happened because some value is empty.
> {code}
> scala> df1.stat.crosstab("role", "lang")
> org.apache.spark.sql.AnalysisException: syntax error in attribute name: ;
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.parseAttributeName(LogicalPlan.scala:145)
> at
> org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.resolveQuoted(LogicalPlan.scala:135)
> at org.apache.spark.sql.DataFrame.resolve(DataFrame.scala:157)
> at org.apache.spark.sql.DataFrame.col(DataFrame.scala:603)
> at
> org.apache.spark.sql.DataFrameNaFunctions.org$apache$spark$sql$DataFrameNaFunctions$$fillCol(DataFrameNaFunctions.scala:394)
> at
> org.apache.spark.sql.DataFrameNaFunctions$$anonfun$2.apply(DataFrameNaFunctions.scala:160)
> at
> org.apache.spark.sql.DataFrameNaFunctions$$anonfun$2.apply(DataFrameNaFunctions.scala:157)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> at
> scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
> at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:108)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
> at scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:108)
> at
> org.apache.spark.sql.DataFrameNaFunctions.fill(DataFrameNaFunctions.scala:157)
> at
> org.apache.spark.sql.DataFrameNaFunctions.fill(DataFrameNaFunctions.scala:147)
> at
> org.apache.spark.sql.DataFrameNaFunctions.fill(DataFrameNaFunctions.scala:132)
> at
> org.apache.spark.sql.execution.stat.StatFunctions$.crossTabulate(StatFunctions.scala:132)
> at
> org.apache.spark.sql.DataFrameStatFunctions.crosstab(DataFrameStatFunctions.scala:91)
> {code}
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