[VL] Add LocalTableScanExec support to Velox backend

[minni31]

CONTEXT

LocalTableScanExec is a Spark physical operator that materializes in-memory data (e.g., from Dataset.toDF(), spark.range(), or constant relations optimized by the catalyst planner). Currently, Gluten does not offload this operator, so the output rows stay in Spark's internal row format and require a separate row-to-columnar conversion step before downstream Velox operators can consume them.

This is the companion PR to #12077 (RDDScanExec support) — both follow the same design pattern.

WHAT

Adds a VeloxLocalTableScanTransformer that intercepts LocalTableScanExec in the offload rules and performs row-to-columnar conversion using Velox's native RowToColumnarConverter. The implementation:

• Introduces a LocalTableScanTransformer base trait in gluten-substrait with the backend-agnostic contract (output attributes, row data, schema validation).
• Adds the Velox-specific VeloxLocalTableScanTransformer that delegates schema validation to VeloxValidatorApi.validateSchema — the same canonical validator used by all other Velox operators — ensuring recursive complex-type validation, TimestampNTZ handling, and variant struct detection are handled consistently.
• Wires up the offload rule in OffloadSingleNodeRules and the backend factory method in VeloxSparkPlanExecApi.
• Skips offloading for streaming sources (plan.getStream.isEmpty guard) since those follow a different execution path.
• Propagates SQLMetrics (numInputRows, numOutputBatches, convertTime) so conversion costs are visible in the Spark UI.
• Uses the 7-parameter toColumnarBatchIterator overload to pass plan-level metrics to the native converter.

Tests

Suite	Tests	Status
VeloxLocalTableScanSuite	7 tests covering primitive types, nullable columns, empty datasets, multi-partition, string columns, filter pushdown, multiple column types	Local pass

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