[VL] Struct fields are read from the wrong column when two same-named struct columns meet in one projection #13197

Backend

Velox (Bolt shares the same binding code).

Bug description

When a projection's input holds two struct attributes with the same name but different field layouts, Gluten reads struct fields from the wrong one. ExpressionConverter.bindGetStructField re-resolves the root attribute of a GetStructField chain by name over the whole input and keeps the last match, so l.s.x and r.s.x are both bound against whichever s comes last.

Repro with the default configuration:

spark.sql("select id, named_struct('x', id, 'y', id * 100) as s from range(5)").write.parquet("/tmp/l")
spark.sql("select id, named_struct('y', id * 100, 'x', id) as s from range(5)").write.parquet("/tmp/r")
spark.read.parquet("/tmp/l").createOrReplaceTempView("l")
spark.read.parquet("/tmp/r").createOrReplaceTempView("r")
spark.sql("select l.s.x, l.s.y, r.s.x, r.s.y from l join r on l.id = r.id").show()

Vanilla Spark returns [1, 100, 1, 100] for id 1. Gluten returns [100, 1, 1, 100].

The same function also looks each field up by name and keeps the last match, which misreads structs with duplicate field names. The Velox generate rewrite builds such a struct from the generator output aliases, so select v.* from (select id, array(named_struct('p', id, 'q', id * 10)) as arr from range(5)) lateral view inline(arr) v as x, x returns [10, 10] for id 1 instead of [1, 10].

Gluten version

main (ca7a0a4)

Spark version

Spark 3.5

This issue was written with the assistance of AI (Claude Opus).