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A social media application stores all follower ID in an array field on each user document. A popular account has 500,000 followers, and the application is failing to update the document. What is the most likely cause?
The follower array is exceeding the 16-MB document size limit.
The database doesn't support arrays with more than 100,000 elements.
The unique index on the followers array is preventing duplicate entries.
A development team creates a separate collection for each of their 2,000 tenants. They notice that database startup is slow, cross-tenant reporting is impossible, and index maintenance takes hours. Which anti-pattern is the team experiencing?
The over-normalization anti-pattern, because tenant data should be embedded in a single document.
The collection sprawl anti-pattern, because 2,000 collections create excessive management overhead.
The unnecessary indexes anti-pattern, because each collection has duplicate indexes.
A products collection has three indexes: { category: 1 }, { category: 1, price: -1 }, and { category: 1, price: -1, name: 1 }. Write operations are slower than expected. Which indexes should the developer drop?
{ category: 1 }
{ category: 1, price: -1 }
{ category: 1, price: -1, name: 1 }
Drop { category: 1 } and { category: 1, price: -1 } because the compound index covers all three query patterns.
Drop { category: 1, price: -1, name: 1 } because compound indexes are slower than single-field indexes.
Keep all three indexes because they each serve different query patterns.
An order display page makes four separate database queries to show a customer's order: one for the order, one for customer details, one for product names, and one for the shipping address. Which anti-pattern is causing the extra queries?
The collection sprawl anti-pattern, because the data should be in a single collection.
The unbounded arrays anti-pattern, because the order is storing too many references.
The over-normalization anti-pattern, because display data should be embedded in the order document using the extended reference pattern.
Customers report that they can't sign in even though they're entering the correct email address. Investigation shows that the customer registered with "Haladhar@Contoso.com" but tries to sign in with "haladhar@contoso.com". What is the root cause?
"Haladhar@Contoso.com"
"haladhar@contoso.com"
The application has a bug in its authentication logic that rejects valid credentials.
Azure DocumentDB queries are case-sensitive by default, and the email field wasn't normalized to lowercase on write.
The unique index on the email field is blocking the sign in query from finding a match.
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