Question 1

How to create a custom loader in GraphQL::Batch?

Accepted Answer

Define a class inheriting from GraphQL::Batch::Loader with an initialize method for grouping and a perform method to batch load data, as shown in the RecordLoader example in the README. This allows you to handle specific data models and edge cases like caching.

Question 2

GraphQL::Batch vs DataLoader in JavaScript?

Accepted Answer

GraphQL::Batch is Ruby's implementation of the DataLoader pattern, tailored for graphql-ruby and promise.rb, whereas DataLoader in JavaScript is more generic and works with various GraphQL servers. GraphQL::Batch integrates directly into Ruby's ecosystem, offering similar batching but with Ruby-specific APIs and ActiveRecord examples.

Question 3

How to handle errors in GraphQL::Batch promises?

Accepted Answer

Use the .then method with two lambda arguments: the first for success and the second for handling exceptions, as demonstrated in the README's CacheLoader example. This allows fallback logic, such as retrying with a different loader if an error occurs.

Question 4

Can GraphQL::Batch work with non-ActiveRecord databases?

Accepted Answer

Yes, it doesn't depend on ActiveRecord, but you'll need to write custom loaders for your data source, as the README states it handles edge cases for ActiveRecord but provides a framework for other setups. This requires more manual implementation compared to using the provided examples.

Question 5

How to test GraphQL::Batch loaders outside of GraphQL?

Accepted Answer

Use the GraphQL::Batch.batch helper to run batch loads in a block, as described in the unit testing section. This sets up thread-local state to simulate batching and clears it after, allowing isolated testing of loader logic without executing full GraphQL queries.

Question 6

What are common performance issues with GraphQL::Batch?

Accepted Answer

If loaders are not implemented correctly, it can still lead to N+1 problems or memory leaks due to caching. The README emphasizes proper grouping in perform methods and cache priming, but misuse, such as inefficient queries or missing fulfill calls, can negate benefits.

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