Juliusz Sompolski created SPARK-20367:
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Summary: Spark silently escapes partition column names
Key: SPARK-20367
URL: https://issues.apache.org/jira/browse/SPARK-20367
Project: Spark
Issue Type: Bug
Components: Spark Core
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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