[FEA] Refactoring JSON reader tree algorithms with Compressed Sparse Row (CSR)

The steady addition of features to the JSON reader has resulted in some code paths that are error-prone (see #15750) and difficult to maintain. Support for mixed types, coercing nested types to string, array of arrays, null literals and more has been added over the past few releases (see [comment](https://github.com/rapidsai/cudf/issues/15750#issuecomment-2121737479)) and stretched the original design of token-to-tree and tree-to-column processing.

| Status | Topic |
|---|---|
| 🔄 | Introduce column vertex structure and graph traversal to the tree representation. Make sure to maintain the pandas requirements for handling array-of-arrays and null literals. |
| | Introduce mixed type handling with pruning for non-conforming dtypes (updated Spark requirement). Also consider the case where a dtype is not provided for a column with mixed types. |
| | Add an pruning option for cross-column pruning, for cases when validation fails and all values in the row become null |
| | https://github.com/rapidsai/cudf/issues/15278 |