[PR] [SPARK-48897][PYTHON][CONNECT] Make `from_xml` support StructType schema [spark]

[via GitHub]

zhengruifeng opened a new pull request, #47355:
URL: https://github.com/apache/spark/pull/47355

   ### What changes were proposed in this pull request?
   Make `from_xml` support StructType schema
   
   ### Why are the changes needed?
   StructType schema was supported in Spark Classic, but not in Spark Connect
   
   to address https://github.com/apache/spark/pull/43680#discussion_r1385332357
   
   
   ### Does this PR introduce _any_ user-facing change?
   
   before:
   ```
   from pyspark.sql.types import StructType, LongType
   import pyspark.sql.functions as sf
   data = [(1, '''<p><a>1</a></p>''')]
   df = spark.createDataFrame(data, ("key", "value"))
   
   schema = StructType().add("a", LongType())
   df.select(sf.from_xml(df.value, schema)).show()
   
   ---------------------------------------------------------------------------
   AnalysisException                         Traceback (most recent call last)
   Cell In[1], line 7
   ...
   AnalysisException: [PARSE_SYNTAX_ERROR] Syntax error at or near '{'. 
SQLSTATE: 42601
   
   JVM stacktrace:
   org.apache.spark.sql.AnalysisException
        at 
org.apache.spark.sql.catalyst.parser.ParseException.withCommand(parsers.scala:278)
        at 
org.apache.spark.sql.catalyst.parser.AbstractParser.parse(parsers.scala:98)
        at 
org.apache.spark.sql.catalyst.parser.AbstractParser.parseDataType(parsers.scala:40)
        at 
org.apache.spark.sql.types.DataType$.$anonfun$fromDDL$1(DataType.scala:126)
        at 
org.apache.spark.sql.types.DataType$.parseTypeWithFallback(DataType.scala:145)
        at org.apache.spark.sql.types.DataType$.fromDDL(DataType.scala:127)
   ```
   
   after:
   ```
   +---------------+
   |from_xml(value)|
   +---------------+
   |            {1}|
   +---------------+
   
   ```
   
   ### How was this patch tested?
   added doctest
   
   
   ### Was this patch authored or co-authored using generative AI tooling?
   no


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