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https://issues.apache.org/jira/browse/SPARK-20367?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15976541#comment-15976541
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Apache Spark commented on SPARK-20367:
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User 'juliuszsompolski' has created a pull request for this issue:
https://github.com/apache/spark/pull/17703
> Spark silently escapes partition column names
> ---------------------------------------------
>
> Key: SPARK-20367
> URL: https://issues.apache.org/jira/browse/SPARK-20367
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.1.0, 2.2.0
> Reporter: Juliusz Sompolski
> Priority: Minor
>
> CSV files can have arbitrary column names:
> {code}
> scala> spark.range(1).select(col("id").as("Column?"),
> col("id")).write.option("header", true).csv("/tmp/foo")
> scala> spark.read.option("header", true).csv("/tmp/foo").schema
> res1: org.apache.spark.sql.types.StructType =
> StructType(StructField(Column?,StringType,true),
> StructField(id,StringType,true))
> {code}
> However, once a column with characters like "?" in the name gets used in a
> partitioning column, the column name gets silently escaped, and reading the
> schema information back renders the column name with "?" turned into "%3F":
> {code}
> scala> spark.range(1).select(col("id").as("Column?"),
> col("id")).write.partitionBy("Column?").option("header", true).csv("/tmp/bar")
> scala> spark.read.option("header", true).csv("/tmp/bar").schema
> res3: org.apache.spark.sql.types.StructType =
> StructType(StructField(id,StringType,true),
> StructField(Column%3F,IntegerType,true))
> {code}
> The same happens for other formats, but I encountered it working with CSV,
> since these more often contain ugly schemas...
> Not sure if it's a bug or a feature, but it might be more intuitive to fail
> queries with invalid characters in the partitioning column name, rather than
> silently escaping the name?
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