Consider this Firebase transaction on a document with initial field count: 5. What will be the final value of count after this transaction completes successfully?
const docRef = firestore.collection('counters').doc('counter1'); await firestore.runTransaction(async (transaction) => { const doc = await transaction.get(docRef); const newCount = (doc.data()?.count ?? 0) + 3; transaction.update(docRef, { count: newCount }); });
Think about how the transaction reads the current value and adds 3.
The transaction reads the current count value (5), adds 3, and updates it to 8.
Choose the correct statement about Firebase transactions.
Think about how Firebase handles concurrent updates inside transactions.
Firebase transactions automatically retry if the data they read changes before commit, ensuring atomicity.
What error will this Firebase transaction code raise when executed?
const docRef = firestore.collection('users').doc('user1'); await firestore.runTransaction(async (transaction) => { transaction.update(docRef, { score: 10 }); const doc = await transaction.get(docRef); console.log(doc.data()); });
Check the order of operations allowed in Firebase transactions.
Firebase transactions allow updates before reads; this code runs without error.
Given a Firestore collection orders, which security rule correctly prevents users from updating orders they do not own, even inside transactions?
Think about how to restrict updates to only the owner of the document.
Rule A allows updates only if the authenticated user ID matches the document's owner ID, securing transaction writes.
Firebase transactions retry automatically when data changes during the transaction. Why is this behavior important in distributed systems?
Consider how multiple users might update the same data at the same time.
Automatic retries help maintain data consistency by handling conflicts from concurrent updates in distributed environments.