[spark] Fix nested struct values wrong order for insert columns

[ArnavBalyan]

Purpose

• Insert column lists should order both columns and nested struct fields by position.
• Paimon maps nested struct fields by name, causing values to be reordered when the source and target field orders differ.
• This causes the query results to differ, ensure we can fix by preserving the mapping recursively for structs inside arrays and maps.

Tests

• UT

[ArnavBalyan]

cc @JingsongLi thanks :)

[JingsongLi]

[P1] Preserve positional mapping when nested field counts differ

Returning input here falls back to the downstream by-name resolver whenever merge-schema fills a missing nested field. For target ARRAY<STRUCT<x: INT, y: INT, z: INT>>, a column-list write whose input struct fields are (y=20, x=10) stores [10, 20, null] instead of the positional [20, 10, null]. I reproduced this on Spark 3.5 with spark.paimon.write.merge-schema=true. Please rename the common ordinal prefix even when the lengths differ, preserve unmatched input fields, and let the existing strict/merge-schema handling process missing or extra fields. A regression test with unequal nested field counts would cover this path.