Performance (N+1 & DataLoader) interview questions

1. A.the inefficiency where resolving a list triggers one backend call per item plus the initial list fetch
2. B.a per-request utility that batches and caches backend key lookups within a single tick to eliminate redundant fetches
3. C.an optimization sending a hash instead of the full document, with the server caching the text after a first registration
4. D.the short-lived memoization of loaded keys, scoped to one operation, that dedupes repeat lookups for the same id

Answer + AI explanation with Pro

1. A.Batching
2. B.DataLoader
3. C.N+1 problem
4. D.Automatic persisted queries

Answer + AI explanation with Pro

1. A.N+1 problem — collapsing many individual same-type key lookups gathered in one event-loop tick into a single backend request
2. B.N+1 problem — an optimization sending a hash instead of the full document, with the server caching the text after a first registration
3. C.N+1 problem — the inefficiency where resolving a list triggers one backend call per item plus the initial list fetch
4. D.N+1 problem — the short-lived memoization of loaded keys, scoped to one operation, that dedupes repeat lookups for the same id

Answer + AI explanation with Pro

1. A.collapsing many individual same-type key lookups gathered in one event-loop tick into a single backend request
2. B.a per-request utility that batches and caches backend key lookups within a single tick to eliminate redundant fetches
3. C.the short-lived memoization of loaded keys, scoped to one operation, that dedupes repeat lookups for the same id
4. D.an optimization sending a hash instead of the full document, with the server caching the text after a first registration

Answer + AI explanation with Pro

1. A.Batching
2. B.Per-request cache
3. C.DataLoader
4. D.N+1 problem

Answer + AI explanation with Pro

1. A.DataLoader — scoring a document's cost before execution to reject overly expensive or deeply nested requests
2. B.DataLoader — an optimization sending a hash instead of the full document, with the server caching the text after a first registration
3. C.DataLoader — the short-lived memoization of loaded keys, scoped to one operation, that dedupes repeat lookups for the same id
4. D.DataLoader — a per-request utility that batches and caches backend key lookups within a single tick to eliminate redundant fetches

Answer + AI explanation with Pro

1. A.collapsing many individual same-type key lookups gathered in one event-loop tick into a single backend request
2. B.scoring a document's cost before execution to reject overly expensive or deeply nested requests
3. C.the inefficiency where resolving a list triggers one backend call per item plus the initial list fetch
4. D.an optimization sending a hash instead of the full document, with the server caching the text after a first registration

Answer + AI explanation with Pro

1. A.Automatic persisted queries
2. B.Batching
3. C.DataLoader
4. D.N+1 problem

Answer + AI explanation with Pro

1. A.Batching — the short-lived memoization of loaded keys, scoped to one operation, that dedupes repeat lookups for the same id
2. B.Batching — collapsing many individual same-type key lookups gathered in one event-loop tick into a single backend request
3. C.Batching — a per-request utility that batches and caches backend key lookups within a single tick to eliminate redundant fetches
4. D.Batching — the inefficiency where resolving a list triggers one backend call per item plus the initial list fetch

Answer + AI explanation with Pro

1. A.a per-request utility that batches and caches backend key lookups within a single tick to eliminate redundant fetches
2. B.the short-lived memoization of loaded keys, scoped to one operation, that dedupes repeat lookups for the same id
3. C.scoring a document's cost before execution to reject overly expensive or deeply nested requests
4. D.collapsing many individual same-type key lookups gathered in one event-loop tick into a single backend request

Answer + AI explanation with Pro

1. A.Query complexity analysis
2. B.Batching
3. C.N+1 problem
4. D.Per-request cache

Answer + AI explanation with Pro

1. A.Per-request cache — a per-request utility that batches and caches backend key lookups within a single tick to eliminate redundant fetches
2. B.Per-request cache — an optimization sending a hash instead of the full document, with the server caching the text after a first registration
3. C.Per-request cache — the short-lived memoization of loaded keys, scoped to one operation, that dedupes repeat lookups for the same id
4. D.Per-request cache — collapsing many individual same-type key lookups gathered in one event-loop tick into a single backend request

Answer + AI explanation with Pro

1. A.an optimization sending a hash instead of the full document, with the server caching the text after a first registration
2. B.collapsing many individual same-type key lookups gathered in one event-loop tick into a single backend request
3. C.the short-lived memoization of loaded keys, scoped to one operation, that dedupes repeat lookups for the same id
4. D.scoring a document's cost before execution to reject overly expensive or deeply nested requests

Answer + AI explanation with Pro

1. A.DataLoader
2. B.N+1 problem
3. C.Per-request cache
4. D.Query complexity analysis

Answer + AI explanation with Pro

1. A.Query complexity analysis — a per-request utility that batches and caches backend key lookups within a single tick to eliminate redundant fetches
2. B.Query complexity analysis — scoring a document's cost before execution to reject overly expensive or deeply nested requests
3. C.Query complexity analysis — the short-lived memoization of loaded keys, scoped to one operation, that dedupes repeat lookups for the same id
4. D.Query complexity analysis — collapsing many individual same-type key lookups gathered in one event-loop tick into a single backend request

Answer + AI explanation with Pro

1. A.collapsing many individual same-type key lookups gathered in one event-loop tick into a single backend request
2. B.an optimization sending a hash instead of the full document, with the server caching the text after a first registration
3. C.scoring a document's cost before execution to reject overly expensive or deeply nested requests
4. D.the short-lived memoization of loaded keys, scoped to one operation, that dedupes repeat lookups for the same id

Answer + AI explanation with Pro

1. A.DataLoader
2. B.Per-request cache
3. C.Automatic persisted queries
4. D.N+1 problem

Answer + AI explanation with Pro

1. A.Automatic persisted queries — scoring a document's cost before execution to reject overly expensive or deeply nested requests
2. B.Automatic persisted queries — collapsing many individual same-type key lookups gathered in one event-loop tick into a single backend request
3. C.Automatic persisted queries — an optimization sending a hash instead of the full document, with the server caching the text after a first registration
4. D.Automatic persisted queries — the inefficiency where resolving a list triggers one backend call per item plus the initial list fetch

Answer + AI explanation with Pro