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.

示例

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>
Copy

Snowpark 脚本

df = session.read.option("rowTag", "book").xml("@mystage/books.xml")
Copy

这会将每个 <book> 元素从 XML 文件加载到自己的行中,其中子元素(例如,<title><author>)会自动提取为 VARIANT 类型的列。

输出

_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"

  • rowTag 标识的每个 XML 元素都变成一行。

  • 该标签中的每个子元素都成为一列,存储为 VARIANT。嵌套元素被捕获为嵌套 VARIANT 数据。

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

开始使用

  1. 安装 Snowpark Python 包:

    pip install snowflake-snowpark-python
    
    Copy
  2. 将 XML 文件上传到 Snowflake 暂存区:

    PUT file:///path/to/books.xml @mystage;
    
    Copy
  3. 使用 Snowpark 读取 XML 文件:

    df = session.read.option("rowTag", "book").xml("@mystage/books.xml")
    
    Copy
  4. 使用 DataFrame 方法进行转换或保存:

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

支持的选项

  • :code:`rowTag`(必填):要提取为行的 XML 元素的名称。

  • :code:`rowValidationXSDPath`(可选):用于在加载过程中验证每个 rowTag 片段的 XSD 的暂存区路径。

  • mode`(可选):默认行为加载时无需验证。当设置 :code:`rowValidationXSDPath 时:

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

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

有关 XML 选项的更多信息,请参阅 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")
    )
    
    Copy

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:选择使用 时默认使用的角色和仓库。读取操作会在第一个有问题的行处停止并返回错误。

限制

Snowpark XML RowTag Reader 具有以下限制:

  • 不推断架构,并且输出列都是 VARIANT 类型。

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

  • 仅在 Snowpark Python 库中可用。

语言: 中文