Include relationship variables in Feature.get_dependencies

If we have a relationship `log.session_id -> sessions.id` and a feature `sessions: MEAN(log.value)` there is an implicit dependency on the features `sessions: id` and `log: session_id` – to calculate the aggregation we need to be able to join using them.

In `FeatureSetCalculator` we currently keep all ID columns in intermediate feature matrices because we don't know whether there are any features which depend on them:
https://github.com/Featuretools/featuretools/blob/1bc5f971af86fb309f87d7f0bb7db0e6fe29d604/featuretools/computational_backends/feature_set_calculator.py#L630-L636

If `get_dependencies` included the variables which are needed for joining (as `IdentityFeatures`) then these features would be included in the `feature_trie` and we could keep only the columns which are actually necessary.

This is only tangential, but we could also get rid of the first element of the 3-tuples stored in `feature_trie` and simplify its construction some what. Since every node would now have at least one feature, if the first of the two sets is empty then the full entity is not needed. I.e. this would now always be true:
```py
needs_full_entity, full_entity_features, _ = node.value
assert needs_full_entity == (len(full_entity_features) > 0)
```