* allow customizing GraphQL root field names, close#981
* document v2 track_table API in reference
* support customising column field names in GraphQL schema
* [docs] add custom column fields doc in API reference
* add tests
* rename 'ColField' to 'ColumnField'
* embed column's graphql field in 'PGColumnInfo'
-> Value constructor of 'PGCol' is not exposed
-> Using 'parseJSON' to construct 'PGCol' in 'FromJSON' instances
* avoid using 'Maybe TableConfig'
* refactors & 'custom_column_fields' -> 'custom_column_names'
* cli-test: add configuration field in metadata export test
* update expected keys in `FromJSON` instance of `TableMeta`
* use `buildSchemaCacheFor` to update configuration in v2 track_table
* remove 'GraphQLName' type and use 'isValidName' exposed from parser lib
* point graphql-parser-hs library git repo to hasura
* support 'set_table_custom_fields' query API & added docs and tests
This fixes an issue where queries could incorrectly be considered
reusable if a variable was used in two positions: one where it affected
SQL generation and one where it did not.
These changes also add a new type, PGColumnType, between PGColInfo and
PGScalarType, and they process PGRawColumnType values into PGColumnType
values during schema cache generation.
From `alpha-40` we've been using a `WHERE` clause to fetch required rows and generate mutation response. This has a few limitations like the requirement of a primary key/unique constraint. This also returns inconsistent data on `delete` mutation as mentioned in #1794.
Now, we're using `VALUES (..)` (refer [here](https://www.postgresql.org/docs/current/sql-values.html)) expression to form virtual table rows in `SQL` to generate mutation response.
Internal changes:-
- Not to use primary key/unique constraint columns:-
- Revert back to `ConstraintName` from `TableConstraint` in `TableInfo` type
- Remove `tcCols` field in `TableConstraint` type
- Modify `table_info.sql` and `fetchTableMeta` function `SQL`
- A test case to perform `delete` mutation and returning relational objects.
If returning field contains nested selections then mutation is performed in two steps
1. Mutation is performed with returning columns of any primary key and unique constraints
2. returning fields are queried on rows returned by selecting from table by filtering with column values returned in Step 1.
Since mutation takes two courses based on selecting relations in returning field, it is hard to maintain sequence of prepared arguments (PrepArg) generated while resolving returning field. So, we're using txtConverter instead of prepare to resolve mutation fields.
