It's been 4 months since the 1.0.0 release of pg_graphql.
Since then, we’ve pushed several features to improve the APIs that pg_graphql
produces.
In this article, we’ll walk through those features and show examples of each.
📢 These features are only available on projects with Postgres version 15.1.0.63
or higher. For help with upgrading, please review the migrating and upgrading projects guide.
View Support
Prior to v1.1
, pg_graphql
would only reflect standard tables. Since then, views, materialized views, and foreign tables are now also reflected in the GraphQL schema.
For example:
Since all entities exposed by pg_graphql
require primary keys, we must define that constraint for the view. We do that using a comment directive:
Which yields the GraphQL type:
With associated Edge
and Connection
types. That enables querying via:
Additionally, simple views automatically support mutation events like inserts and updates. You might use these to migrate underlying tables while maintaining backwards compatibility with previous API versions.
Filtering
Filtering in SQL is endlessly flexible. We’ve taken two incremental steps to bring more of that flexibility to the GraphQL interface.
is null
and is not null
Handling null
values can be tricky in both SQL and GraphQL. However, there are similarities we can take advantage of.
In pg_graphql
, every scalar data type has its own filter type, such as IntFilter
and StringFilter
.
Each of these filter types now includes an is
argument, which allows you to filter based on whether a value is null or not null.
You can do this by using {is: NULL}
for null
values and {is: NOT_NULL}
for non-null
values.
For example:
to return all blog
s where the name
is null
.
like
, ilike
, and startsWith
Text filtering options in pg_graphql
have historically been restricted to equality checks. The hesitation was due to concerns about exposing a default filter that is difficult to index. The combination of citext and PGroonga available on the platform solves those scalability risks and enabled us to expand the StringFilter
with options for like
ilike
and startsWith
.
Note that startsWith
filters should be preferred where appropriate because they can leverage simple B-Tree indexes to improve performance.
GraphQL directives @skip
and @include
The GraphQL spec has evolved over time. Although the spec is clear, it is common for GraphQL servers to selectively omit some chunks of functionality. For example, some frameworks intentionally do not expose an introspection schema as a form of security through obscurity.
pg_graphql
aims to be unopinionated and adhere exactly to the spec. The @skip
and @include
directives are part of the GraphQL core specification and are now functional.
The @skip
directive in GraphQL is used to conditionally skip a field or fragment during query execution based on a Boolean variable. It can be used to make the query more efficient by reducing the amount of data retrieved from the server.
The @include
directive is the mirror of @skip
where a field or fragment is conditionally included depending on the value of a Boolean variable.
Here's an example of how the @skip
directive can be used in a GraphQL query:
User Defined Descriptions
Users can now use the comment directive system to assign descriptions to tables, views and columns.
GraphQL IDEs, such as GraphiQL render those descriptions, allowing developers to provide clearer API documentation.
Roadmap
The headline features we aim to launch in coming releases of pg_graphql
include:
- Support for user-defined functions: GitHub issue
- Support for nested inserts: GitHub issue
- An alternative approach to computed relationships based on SQL functions returning
SET OF
rather than comment directives (compatible with PostgREST)