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https://issues.apache.org/jira/browse/SPARK-6189?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14357248#comment-14357248
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Joseph K. Bradley commented on SPARK-6189:
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Maybe it's actually OK to allow periods in fields names since SQL does. We
could be like SQL, where periods are OK and users just need to make sure to
quote the field name so that SQL doesn't think the period is indicating a
subfield. I haven't tried this yet with DataFrames to check its behavior.
> Pandas to DataFrame conversion should check field names for periods
> -------------------------------------------------------------------
>
> Key: SPARK-6189
> URL: https://issues.apache.org/jira/browse/SPARK-6189
> Project: Spark
> Issue Type: Improvement
> Components: DataFrame, SQL
> Affects Versions: 1.3.0
> Reporter: Joseph K. Bradley
> Priority: Minor
>
> Issue I ran into: I imported an R dataset in CSV format into a Pandas
> DataFrame and then use toDF() to convert that into a Spark DataFrame. The R
> dataset had a column with a period in it (column "GNP.deflator" in the
> "longley" dataset). When I tried to select it using the Spark DataFrame DSL,
> I could not because the DSL thought the period was selecting a field within
> GNP.
> Also, since "GNP" is another field's name, it gives an error which could be
> obscure to users, complaining:
> {code}
> org.apache.spark.sql.AnalysisException: GetField is not valid on fields of
> type DoubleType;
> {code}
> We should either handle periods in column names or check during loading and
> warn/fail gracefully.
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