feat(parquet): sub-column projection pushdown for struct fields

[EshwarCVS]

Which issue does this PR close?

Closes #

Rationale for this change

When a query accesses only a single field of a wide struct column (e.g.
SELECT event['user_id'] FROM logs), DataFusion today reads all leaf
columns of event from Parquet. For structs with many fields this is
significant unnecessary I/O.

What changes are included in this PR?

Logical optimizer (2-pass pipeline)

• ExtractLeafExpressions (pass 1): detects MoveTowardsLeafNodes
  sub-expressions (including get_field) inside Filter, Sort, Limit,
  Aggregate, and Join nodes and lifts them into named extraction
  projections (__datafusion_extracted_N) inserted below those nodes.
• PushDownLeafProjections (pass 2): pushes those extraction
  projections further down toward leaf/datasource nodes, merging into
  existing projections where possible and routing each expression to the
  correct input side of multi-input nodes (Join, Union).

Physical layer — Parquet leaf-column projection

• PushdownChecker / StructFieldAccess: extended the filter
  pushdown visitor to recognise get_field(Column, "field1", "field2", …)
  patterns and record a StructFieldAccess { root_index, field_path }
  instead of requiring the entire struct column.
• resolve_struct_field_leaves: maps each StructFieldAccess to the
  exact Parquet leaf column indices by prefix-matching against
  SchemaDescriptor, enabling ProjectionMask::leaves() instead of
  ProjectionMask::roots().
• build_filter_schema / prune_struct_type: constructs a narrowed
  Arrow schema that matches what the Parquet reader actually produces when
  projecting specific struct leaves, so reassign_expr_columns can
  correctly remap filter expressions.
• build_projection_read_plan: unified entry point (used by
  opener.rs) that builds a leaf-level ProjectionMask from the physical
  projection expressions, with fast paths for all-plain-column and
  no-struct-column schemas.

Physical optimizer wiring

remove_unnecessary_projections / try_swapping_with_projection already
merges ProjectionExec nodes (including those containing get_field)
into DataSourceExec via ParquetSource::try_pushdown_projection →
try_merge. The new physical-layer code ensures the merged expressions
are then used to build a narrow ProjectionMask.

How are these changes tested?

• Unit tests in row_filter.rs: 10 new tests covering
  get_field pushdown allowance/denial, correct Parquet leaf index
  selection for simple and deeply-nested structs, end-to-end row
  filtering, and the projection-preserves-full-struct invariant.
• Optimizer unit tests in extract_leaf_expressions.rs: 47 tests
  covering extraction from Filter/Sort/Limit/Aggregate/Join/Union/
  SubqueryAlias, deduplication, CSE interaction, and recovery projection
  correctness.
• SQL logic tests in projection_pushdown.slt: end-to-end queries
  covering basic field access, filter pushdown, sort/TopK, multi-partition,
  joins, aggregation, nullable structs, SELECT * with struct field
  filters, and edge cases (Map columns, non-literal field names).

[kumarUjjawal]

This doesn't belong in this PR

[EshwarCVS]

Will update by removing those changes.

[kumarUjjawal]

I don't see the point of this PR since it doesn't do any work which are mentioned in the PR body and the one change it has is unrelated to the body. Please open issue related to what you have mentioned in the body first.

[kumarUjjawal]

@EshwarCVS Please see https://datafusion.apache.org/contributor-guide/index.html#ai-assisted-contributions