[SPARK-6189] Pandas to DataFrame conversion should check field names for periods

• Type: Improvement
• Status: Resolved
• Priority: Minor
• Resolution: Fixed
• Affects Version/s: 1.3.0
• Component/s: SQL
• Target Version/s: 1.6.0
• Assignee: Unassigned
• Reporter: Joseph K. Bradley
• Created: 05/Mar/15 17:51
• Updated: 03/Nov/15 12:00
• Resolved: 03/Nov/15 12:00

Description

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:

org.apache.spark.sql.AnalysisException: GetField is not valid on fields of type DoubleType;

We should either handle periods in column names or check during loading and warn/fail gracefully.

Issue Links

• relates to: SPARK-5632 not able to resolve dot('.') in field name
• links to: [Github] Pull Request #4982 (mgdadv)