Never fallback to cartesian product for join estimation when we know the min/max values for columns

**Is your feature request related to a problem or challenge? Please describe what you are trying to do.**
`distinct_count` is usually expensive to compute, so some platforms which save parquet files abstain from injecting it at the metadata section. We should be able to estimate the join cardinality without it before falling back to cartesian product.

**Describe the solution you'd like**
Since we already require min/max values to be present, we should be able to just do `min(num_left_rows - num_nulls or 0, scalar_range(left_stats.min, left_stats.max))` to determine an alternative distinct count.

**Describe alternatives you've considered**
None.

**Additional context**
Original discussion was here https://github.com/apache/arrow-datafusion/pull/3787#discussion_r992751749

Start by reading the join cardinality estimation logic and the linked discussion from pull request 3787. Trace how min/max column metadata and null counts are used when distinct_count is absent; done means estimates use the available range information instead of falling back to a cartesian product.

Written by the indexing model from the issue text.