Using the Snowpark XML RowTag Reader

You can activate the Snowpark XML RowTag Reader by specifying .option("rowTag", "<rowtag>") in session.read.option("rowTag", "<rowtag>").xml(). Instead of loading the entire document as a single object, this mode splits the file based on the specified rowTag, loads each matching element as a separate row, and splits each row into multiple columns in a Snowpark DataFrame. The Reader is especially useful for processing only selective elements in XML files or ingesting large XML files in a scalable, Snowpark-native way.

Example

This sample XML is an example:

<library>
    <book id="1">
        <title>The Art of Snowflake</title>
        <author>Jane Doe</author>
        <price>29.99</price>
        <reviews>
            <review>
                <user>tech_guru_87</user>
                <rating>5</rating>
                <comment>Very insightful and practical.</comment>
            </review>
            <review>
                <user>datawizard</user>
                <rating>4</rating>
                <comment>Great read for data engineers.</comment>
            </review>
        </reviews>
        <editions>
            <edition year="2023" format="Hardcover"/>
            <edition year="2024" format="eBook"/>
        </editions>
    </book>

    <book id="2">
        <title>XML for Data Engineers</title>
        <author>John Smith</author>
        <price>35.50</price>
        <reviews>
            <review>
                <user>xml_master</user>
                <rating>5</rating>
                <comment>Perfect for mastering XML parsing.</comment>
            </review>
        </reviews>
        <editions>
            <edition year="2022" format="Paperback"/>
        </editions>
    </book>
</library>
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Snowpark script

df = session.read.option("rowTag", "book").xml("@mystage/books.xml")
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This loads each <book> element from the XML file into its own row, with child elements (for example, <title> and <author>) automatically extracted as columns of type VARIANT.

Output

_id

author

editions

price

reviews

title

“2”

“John Smith”

{ "edition": { "_format": "Paperback", "_year": "2022" } }

“35.50”

{ "review": { "comment": "Perfect for mastering XML parsing.", "rating": "5", "user": "xml_master" } }

“XML for Data Engineers”

“1”

“Jane Doe”

{ "edition": [ { "_format": "Hardcover", "_year": "2023" }, { "_format": "eBook", "_year": "2024" } ] }

“29.99”

{ "review": [ { "comment": "Very insightful and practical.", "rating": "5", "user": "tech_guru_87" }, { "comment": "Great read for data engineers.", "rating": "4", "user": "datawizard" } ] }

“The Art of Snowflake”

  • Each XML element identified by rowTag becomes one row.

  • Each sub-element within that tag becomes a column, stored as a VARIANT. Nested elements are captured as nested VARIANT data.

  • The resulting DataFrame is flattened and columnized and behaves like any other Snowpark DataFrame.

Getting started

  1. Install the Snowpark Python package:

    pip install snowflake-snowpark-python
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  2. Upload your XML file to a Snowflake stage:

    PUT file:///path/to/books.xml @mystage;
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  3. Use Snowpark to read the XML file:

    df = session.read.option("rowTag", "book").xml("@mystage/books.xml")
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  4. Use DataFrame methods to transform or save:

    df.select(col("`title`"), col("`author`")).show()
df.write.save_as_table("books_table")
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Supported options

  • rowTag (Required): The name of the XML element to extract as a row.

  • rowValidationXSDPath (Optional): Stage path to an XSD used to validate each rowTag fragment during load.

  • mode (Optional): Default behavior loads without validation. When rowValidationXSDPath is set:

    • PERMISSIVE: Quarantines invalid rows in _corrupt_record; loads the rest.

    • FAILFAST: Stops at the first invalid row and raises an error.

For more information about XML options, see snowflake.snowpark.DataFrameReader.xml.

Validate XML using XSD

  • To validate each rowTag fragment against an XSD during load, set the XSD path and choose a validation mode:

    df = (
session.read
    .option("rowTag", "book")
    .option("rowValidationXSDPath", "@mystage/schema.xsd")  # validates each row element
    .option("mode", "PERMISSIVE")                         # or "FAILFAST"
    .xml("@mystage/books.xml")
)
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PERMISSIVE: Invalid rows are quarantined in a special _corrupt_record column; valid rows load normally.

  • To persist the result, write the DataFrame to a table with df.write.save_as_table("<table_name>"). The table will include all parsed columns plus an extra _corrupt_record column: it is NULL for valid rows and contains the full XML records for invalid rows (with the other columns showing NULL).

    +-------------------+
| _corrupt_record   |
| <book id="1"> ... |
| <book id="2"> ... |
+-------------------+

FAILFAST: The read stops at the first offending row and returns an error.

Limitations

Snowpark XML RowTag Reader has the following limitations:

  • Doesn’t infer schema, and the output columns are all of type VARIANT.

  • Only supports files stored in Snowflake stages; local files are not supported.

  • Is available only in the Snowpark Python library.

Language: English