[jira] [Created] (SPARK-32810) CSV/JSON data sources should avoid globbing paths when inferring schema

["Maxim Gekk (Jira)" <ji...@apache.org>]

Maxim Gekk created SPARK-32810:
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             Summary: CSV/JSON data sources should avoid globbing paths when inferring schema
                 Key: SPARK-32810
                 URL: https://issues.apache.org/jira/browse/SPARK-32810
             Project: Spark
          Issue Type: Bug
          Components: SQL
    Affects Versions: 3.1.0
            Reporter: Maxim Gekk


The problem is that when the user doesn't specify the schema when reading a CSV table, The CSV file format and data source needs to infer schema, and it does so by creating a base DataSource relation, and there's a mismatch: *FileFormat.inferSchema* expects actual file paths without glob patterns, but *DataSource.paths* expects file paths in glob patterns.
 An example is demonstrated below:
{code:java}
^
|         DataSource.resolveRelation    tries to glob again (incorrectly) on glob pattern """[abc].csv"""
|         DataSource.apply                      ^
|       CSVDataSource.inferSchema               |
|     CSVFileFormat.inferSchema                 |
|   ...                                         |
|   DataSource.resolveRelation          globbed into """[abc].csv""", should be treated as verbatim path, not as glob pattern
|   DataSource.apply                            ^
| DataFrameReader.load                          |
|                                       input """\[abc\].csv"""
{code}
The same problem exists in the JSON data source as well. Ditto for MLlib's LibSVM data source.



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