[EPIC] Improving cost calculations and cost based optimizations

Design document: https://docs.google.com/document/d/1M4mmV7KA1LSj-D-WJA338B4ydlm-8A8D5OPuDE5_SD4/edit

This is a meta issue for improving cost calculations and cost-based optimizations in DataFusion. We already have some statistics collected (mainly from the table sources) and there are estimations for statistics by some of the execution plan nodes, and the overall idea is to improve these as well as possible CBOs.

### Main Goals
- Have enough statistics to start nested join optimizations (#3843). This involves being able to estimate the weight of a join side, and do global re-ordering between join sides to minimize the overall cost of parent joins by reducing the output as much as possible at the bottom levels.
- Provide a more reliable static analysis phase for physical execution operators (so that range based pruning/predicate pruning can leverage the existing infrastructure on their implementations)
- What else?

### Work in Progress

- [x] https://github.com/apache/arrow-datafusion/issues/3898
- [x] https://github.com/apache/arrow-datafusion/issues/3845
- [ ] https://github.com/apache/arrow-datafusion/issues/4158
- [ ] https://github.com/apache/arrow-datafusion/issues/4159
- What else?

### Planned
- [ ] Estimating join cardinalities when the underlying table does not have any statistics (https://github.com/apache/arrow-datafusion/issues/3813#issuecomment-1276643214).
- What else?

### Future
- Support for histograms, so better value distribution when working with cardinality estimations / filter selectivity. Currently, none of the providers we use can directly pass it to us, so we either have to take a peek at the data or only expose the API for other services (like ballista) which can actually collect it and pass to us.

P.S.: feel free to update the text directly or let me know (and I can update it myself)

Beginne mit dem verlinkten Designdokument und prüfe anschließend die abgeschlossenen und offenen Issues unter Work in Progress und Planned, insbesondere #3843, #4158, #4159 und #3813. Für dieses Issue gibt es weder einen einzelnen Implementierungseinstiegspunkt noch ein Abschlusskriterium; Fortschritt bedeutet, die aufgeführten statistischen und kostenbasierten Optimierungsziele anzugehen und dieses Meta-Issue zu aktualisieren.

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