mcdull_zhang created SPARK-36663:
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             Summary: When the existing field name is a number, an error will 
be reported when reading the orc file
                 Key: SPARK-36663
                 URL: https://issues.apache.org/jira/browse/SPARK-36663
             Project: Spark
          Issue Type: Bug
          Components: SQL
    Affects Versions: 3.1.2, 3.0.3
            Reporter: mcdull_zhang


You can use the following methods to reproduce the problem:
{quote}val path = "file:///tmp/test_orc"

spark.range(1).withColumnRenamed("id", "100").repartition(1).write.orc(path)

spark.read.orc(path)
{quote}
The error message is like this:
{quote}org.apache.spark.sql.catalyst.parser.ParseException:
mismatched input '100' expecting {'ADD', 'AFTER'....

== SQL ==
struct<100:bigint>
-------^^^
{quote}
The error is actually issued by this line of code:
{quote}CatalystSqlParser.parseDataType("100:bigint")
{quote}
 

The specific background is that spark calls the above code in the process of 
converting the schema of the orc file into the catalyst schema.
{quote}// code in OrcUtils
private def toCatalystSchema(schema: TypeDescription): StructType = {
 
CharVarcharUtils.replaceCharVarcharWithStringInSchema(CatalystSqlParser.parseDataType(schema.toString).asInstanceOf[StructType])
}{quote}
There are two solutions I currently think of:
 # Modify the syntax analysis of SparkSQL to identify this kind of schema
 # The TypeDescription.toString method should add the quote symbol to the 
numeric column name, because the following syntax is supported:
{quote}CatalystSqlParser.parseDataType("`100`:bigint"){quote}

But currently TypeDescription does not support changing the UNQUOTED_NAMES 
variable, should we first submit a pr to the orc project to support the 
configuration of this variable。

!image-2021-09-03-20-53-35-626.png!

 

How do spark members think about this issue?

 



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