Batch writes in Firebase - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ service_behavior

intermediate

Batch Write Atomicity Behavior

You perform a batch write in Firebase Firestore with 5 document updates. One update tries to write to a document that does not exist. What happens to the batch operation?

Firebase

const batch = db.batch();
const docRef1 = db.collection('users').doc('user1');
const docRef2 = db.collection('users').doc('user2');

batch.update(docRef1, {age: 30});
batch.update(docRef2, {age: 25});
// Assume docRef2 does not exist

await batch.commit();

A The entire batch fails and no document is updated.

B Only the update to the non-existent document fails; others succeed.

C The batch partially commits and skips the non-existent document update.

D The batch creates the non-existent document and updates it.

💡 Hint

Think about whether batch writes are atomic or not.

Batch writes in Firestore are atomic. If any write in the batch fails, the entire batch fails and no changes are applied.

❓ Configuration

intermediate

Maximum Operations in a Batch Write

What is the maximum number of write operations you can include in a single Firestore batch write?

A 1000

B 100

C 500

D 2000

💡 Hint

Check Firestore batch write limits.

Firestore limits batch writes to a maximum of 500 operations per batch.

❓ Architecture

advanced

Designing Efficient Batch Writes for High Throughput

You need to update 10,000 documents in Firestore as quickly as possible using batch writes. Which approach is best?

A Create one batch with all 10,000 writes and commit once.

B Create 20 batches with 500 writes each and commit them in parallel.

C Create 20 batches with 500 writes each and commit them sequentially.

D Update documents one by one without batching.

💡 Hint

Consider Firestore batch size limits and concurrency.

Firestore limits batch writes to 500 operations. Committing batches in parallel improves throughput compared to sequential commits.

❓ security

advanced

Security Rules Impact on Batch Writes

You have a batch write with 3 document updates. One document update violates Firestore security rules. What happens?

A The batch write ignores security rules and commits all updates.

B Only the document violating security rules is skipped; others succeed.

C The batch write partially commits and logs a warning.

D The entire batch write fails and no documents are updated.

💡 Hint

Think about how Firestore enforces security rules on batch writes.

Firestore enforces security rules atomically on batch writes. If any write violates rules, the entire batch fails.

✅ Best Practice

expert

Handling Large Batch Writes with Firestore Transaction Limits

You want to update 2000 documents atomically but Firestore batch writes limit is 500 operations. Which is the best approach?

A Use a cloud function to queue and process batches asynchronously with retries.

B Use Firestore transactions to update all 2000 documents in one transaction.

C Split updates into batches of 500 and chain them sequentially with error handling.

D Use multiple batch writes of 500 operations each and rely on eventual consistency.

💡 Hint

Consider Firestore limits and how to ensure reliability and atomicity at scale.

Firestore transactions and batch writes have limits. Using a cloud function to queue and process batches asynchronously with retries ensures reliability and handles large updates gracefully.