Better handle schema mismatch when writing dataset

import pyarrow as pa
import lance

t = pa.Table.from_pylist([{"test": [1, 2, 3]}])
ds = lance.write_dataset(
    t,
    "test.lance",
    schema=pa.schema([pa.field("test", pa.list_(pa.float32(), 32))]),
    mode="overwrite",
)
print(f"===> schema with pa.Table: \n{t.schema}, lance: \n{ds.schema}")

batch = pa.RecordBatch.from_pylist([{"test": [1, 2, 3]}])
ds = lance.write_dataset(
    pa.RecordBatch.from_pylist([{"test": [1, 2, 3]}]),
    "test.lance",
    schema=pa.schema([pa.field("test", pa.list_(pa.float32(), 32))]),
    mode="overwrite",
)
print(f"===> schema with pa.RecordBatch: \n{batch.schema}, lance: \n{ds.schema}")

lance.write_dataset(
    [pa.RecordBatch.from_pylist([{"test": [1, 2, 3]}])],
    "test.lance",
    schema=pa.schema([pa.field("test", pa.list_(pa.float32(), 32))]),
    mode="overwrite",
)

the above script yields output:

===> schema with pa.Table:
test: list<item: int64>
  child 0, item: int64, lance:
test: list<item: int64>
  child 0, item: int64
===> schema with pa.RecordBatch:
test: list<item: int64>
  child 0, item: int64, lance:
test: list<item: int64>
  child 0, item: int64
munmap_chunk(): invalid pointer
[1]    472488 IOT instruction (core dumped)  python test.py

In the first two cases, maybe we should print a warning about setting schema= when the data source is pa.Table | pa.RecordBatch, where the specified schema is ignored.

In the third case, we crash on abort because the list of record batch and schema mismatches. (ideally user would call with RBR, but sometime just passing a list of RecordBatches is convenient.0

Start by reproducing the issue with the shown Python script and inspect the write_dataset entry point for pa.Table, pa.RecordBatch, and lists of RecordBatches. Done means the requested schema is handled consistently or clearly warned about, and a mismatched list of batches produces a safe error instead of aborting.