tests and benchmarks on range partitioned data

See https://github.com/datafusion-contrib/datafusion-distributed/blob/a6cff424261623dbdd1e2b5cbe83e5273ebc22de/tests/join.rs?plain=1#L120

It's not valid in datafusion to claim your data source is distributed by hash(expr), so this test isn't useful. We should migrate it to a distribution which maps to range partitioning.

There's several open questions that can only really be solved with tests

• file_scan_config_scale_up_leaf_node in src/events/defaults/file_scan_config.rs if the file scan is claiming range partitioning and we rearrange files, that can cause correctness issues right? Should we call FileScanConfig::repartitioned
• Say target_partitions is 10 and our data source has 100 range partitions. Does this distribute correctly to 10 leaf tasks? Does datafusion introduce range partitions?
• Are all instances of scale_partitioning correct when it comes to range partitioned data? https://github.com/datafusion-contrib/datafusion-distributed/blob/a6cff424261623dbdd1e2b5cbe83e5273ebc22de/src/execution_plans/common.rs?plain=1#L17

Start with the range-related test in tests/join.rs, then read file_scan_config_scale_up_leaf_node in src/events/defaults/file_scan_config.rs and scale_partitioning in src/execution_plans/common.rs. Use the existing questions to determine how range partitioning behaves when files or partitions are scaled, and cover those cases with tests and benchmarks. Done means the tests exercise range-partitioned data and establish whether repartitioning and scaling are correct.