Core Concept Questions
Interviewers frequently start with fundamentals: the difference between GraphQL and REST, what a resolver is, and how queries, mutations, and subscriptions differ. A strong answer explains that REST exposes fixed endpoints returning fixed shapes, causing over-fetching or under-fetching, while GraphQL exposes a single endpoint where clients specify exactly the fields they need via a query document validated against a strongly typed schema.
Cricket analogy: Like a buffet-style scorecard where a fan picks exactly the stats they want (batting average, strike rate, not bowling figures) versus being handed one fixed printed scorecard for everyone, GraphQL lets clients request exactly the fields they need versus REST's fixed response shapes.
N+1 Problem and Performance Questions
A near-universal interview question is explaining the N+1 problem: when resolving a list of parent objects, a naive resolver issues one query per child field access, resulting in N+1 database round trips. The expected answer is DataLoader, which batches and caches individual .load(id) calls within a single event-loop tick into one batched database query, plus request-scoped caching so the same entity isn't fetched twice within one operation.
Cricket analogy: Like a scorer calling the stats office separately for every single player's career average instead of requesting the whole squad's stats in one batched call, the N+1 problem wastes round trips that DataLoader batches into one.
const DataLoader = require('dataloader');
const authorLoader = new DataLoader(async (authorIds) => {
const authors = await db.authors.findByIds(authorIds);
const byId = new Map(authors.map((a) => [a.id, a]));
return authorIds.map((id) => byId.get(id));
});
const resolvers = {
Book: {
author: (book) => authorLoader.load(book.authorId),
},
};Design and Tradeoff Questions
Senior-level interviews often probe schema design tradeoffs: when to use a single mutation with many optional arguments versus multiple focused mutations, how to version a schema without breaking clients (deprecate fields with @deprecated rather than removing them abruptly), and when GraphQL is a poor fit — such as simple CRUD services with no aggregation needs, or file upload-heavy APIs where REST's multipart handling is simpler.
Cricket analogy: Like debating whether to pick a single all-rounder to cover multiple roles versus separate specialists for batting, bowling, and fielding, schema design weighs one flexible mutation against several focused ones.
When answering design questions, always mention @deprecated as the standard, non-breaking way to phase out schema fields — it lets tooling and clients see a deprecation reason while the field still resolves, avoiding a hard breaking change.
- Be ready to explain GraphQL vs REST in terms of over-fetching, under-fetching, and single-endpoint design.
- The N+1 problem and DataLoader batching is one of the most commonly asked GraphQL interview topics.
- Know the resolver signature (parent, args, context, info) and what each argument represents.
- Understand query, mutation, and subscription as the three root operation types.
- Be able to discuss schema evolution using @deprecated instead of breaking removals.
- Discuss tradeoffs of coarse versus fine-grained mutations and when GraphQL isn't the right fit.
- Practice explaining persisted queries, caching challenges, and authorization patterns at the resolver level.
Practice what you learned
1. What is the standard solution to the N+1 query problem in GraphQL?
2. What are the four arguments passed to a GraphQL resolver function?
3. What is the recommended way to phase out a schema field without breaking existing clients?
4. According to common interview guidance, GraphQL may be a poor fit for which scenario?
5. How does GraphQL primarily address the over-fetching problem common in REST APIs?
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