[SPARK-50350][SQL] Avro: add new function schema_of_avro (scala side)

[panbingkun]

What changes were proposed in this pull request?

The pr aims to add new function schema_of_avro for avro.

Why are the changes needed?

• The schema format of Avro is different from that of Spark when presented to end users. In order to facilitate the intuitive understanding of Avro's schema by end users.
• Similar functions exist in other formats of data, such as csv, json and xml,
  

  spark/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/FunctionRegistry.scala

  Lines 872 to 875 in 87a5b37

  	// csv
  	expression[CsvToStructs]("from_csv"),
  	expression[SchemaOfCsv]("schema_of_csv"),
  	expression[StructsToCsv]("to_csv"),

  
  

  spark/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/FunctionRegistry.scala

  Lines 836 to 839 in 87a5b37

  	// json
  	expression[StructsToJson]("to_json"),
  	expression[JsonToStructs]("from_json"),
  	expression[SchemaOfJson]("schema_of_json"),

  
  

  spark/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/FunctionRegistry.scala

  Lines 877 to 880 in 87a5b37

  	// Xml
  	expression[XmlToStructs]("from_xml"),
  	expression[SchemaOfXml]("schema_of_xml"),
  	expression[StructsToXml]("to_xml"),

Does this PR introduce any user-facing change?

Yes, end-users will be able to clearly know what Avro's schema format should look like in Spark through the function schema_of_avro.

How was this patch tested?

• Add new UT.

Was this patch authored or co-authored using generative AI tooling?

No.

[MaxGekk]

cc @gengliangwang

[panbingkun]

cc @gengliangwang

Thanks @MaxGekk !