Add support for bucket expression to table scans

### Feature Request / Improvement

For time partitioning, we can express time range expressions and they lead to partition pruning when planning an Arrow scan:

```py
scan = table.scan(
row_filter=And(
GreaterThanOrEqual("event_ts", start),
LessThan("event_ts", end),
)
)

arrow_table = scan.to_arrow()
```

It would be useful to be able to filter by other hidden partitioning transforms, such as buckets -- e.g. filtering on `bucket[16](user_id) in {0, 1, 2, 3}`, and getting partition pruning whenever possible based on the underlying table partitioning specs (falling back to filtering rows when files cannot be pruned).

从 issue 中描述的 table.scan 和 scan.to_arrow 入口点开始，然后跟踪用于 Arrow 分区裁剪的现有时间范围表达式处理逻辑。检查分区规范和行过滤器是如何应用的；当 bucket[16](user_id) 这样的 bucket 表达式能够在可能的情况下裁剪文件，并在无法裁剪时回退到行过滤时，即视为完成。

由索引模型根据 Issue 内容生成。