dataloader VS frank_jwt

When I began working with GraphQL, I had concerns about the N+1 query problem. In my research, I came across the DataLoader pattern and its implementation on GitHub. While I explored various examples of its usage, I still struggled to grasp how it operates internally. Join me in delving a bit deeper into GraphQL DataLoader! :)

DataLoader: it is the standard solution to N+1 problem.

Additionally, you can use DataLoader or similar tools to optimize data fetching and avoid over-fetching or under-fetching data. Ultimately, performance and load tests ensure that your GraphQL API delivers optimal performance, meets response time expectations, and provides a smooth experience for users, even under heavy loads.

The most common practice is to turn N+1 into 1+1 using dataloaders (https://github.com/graphql/dataloader for JS, there are equivalents for most implementations). The N resolvers invoke a single batched loader which receives a list of keys and returns a list of values.

Let's take Payload, for example. Surprise, surprise. We have a relationship field, and it can store IDs to other related documents which are seamlessly merged in when you retrieve documents from the DB. We leverage the dataloader pattern to batch together all "populations" required for a given query, returning them all super fast and with as few separate queries to the DB as possible. We actually even outperform SQL-based frameworks quite a bit. In a purely relational test, we were 3x faster than Directus and 7x faster than Strapi while both were running Postgres, and we were on MongoDB.

Also, have a look at Facebook's Dataloader[0].

[0] https://github.com/graphql/dataloader

In the next article, I'm going to implement a GraphQL server with dataloader using the tools we introduced.

The one example of using Scoped dependency that comes to my mind, it's HTTP request level caching for libs like dataloader.

you would fetch these 1000 rows via dataloader that batches all requests for this relation to a single query... solving the n+1 issue

NOTE: Never store sensitive information about a client in the payload as the JWT is just encoded and not encrypted. You can paste the JWT I gave as an example above in this cool site which basically allows you to see in decoded. JSON Web Tokens - jwt.io

Although they did not make it into production, I experimented with the RabbitMQ message broker, Python (Django, Flask), Kubernetes + minikube, JWT, and NGINX. This was a hobby project, but I intended to learn about microservices along the way.

JSON Web Token (JWT) creation to extend user authentication to server-side functions

The (probably) most famous web resource about JWT - https://jwt.io - provides such a definition of JSON Web Tokens:

If you want to play with JWT and put these concepts into practice, you can use jwt.ioDebugger to decode, verify, and generate JWTs.

In this context, JSON Web Tokens (JWTs) play a crucial role.

Json Web Token (JWT): Even though it is more like an industry standard, we will use JWTs for stateless authentication in this article. If you want to learn more, you can refer to the official documentation.

Se pegar o token jwt podemos ver o que tem dentro, usando o site jwt.io.