Firestore collections and documents in GCP - Time & Space Complexity

Time Complexity: Firestore collections and documents

O(n)

Understanding Time Complexity

When working with Firestore, it's important to understand how the time to access data grows as you add more collections and documents.

We want to know how the number of operations changes when we read or write many documents.

Scenario Under Consideration

Analyze the time complexity of reading multiple documents from a Firestore collection.

// Fetch all documents from a collection
const collectionRef = firestore.collection('users');
const snapshot = await collectionRef.get();
snapshot.forEach(doc => {
  console.log(doc.id, '=>', doc.data());
});
    

This code fetches all documents inside the 'users' collection and processes each one.

Identify Repeating Operations

Look at what repeats when fetching documents:

• Primary operation: Reading each document from the collection.
• How many times: Once per document in the collection.

How Execution Grows With Input

As the number of documents grows, the number of reads grows too.

Input Size (n)	Approx. API Calls/Operations
10	10 document reads
100	100 document reads
1000	1000 document reads

Pattern observation: The number of reads grows directly with the number of documents.

Final Time Complexity

Time Complexity: O(n)

This means the time to read documents grows linearly with how many documents you have.

Common Mistake

[X] Wrong: "Reading a collection is always a single fast operation regardless of size."

[OK] Correct: Firestore reads each document separately, so more documents mean more reads and more time.

Interview Connect

Understanding how Firestore scales with data size helps you design efficient queries and avoid slow operations in real projects.

Self-Check

"What if we added a filter to only read documents matching a condition? How would the time complexity change?"

Practice

1. What is the correct way to describe Firestore's data structure?

easy

A. Documents are the top-level containers holding collections.

B. Documents contain collections, and collections contain key-value pairs.

C. Collections contain key-value pairs directly without documents.

D. Collections contain documents, and documents contain key-value pairs.

Solution

1. Step 1: Understand Firestore data hierarchy

   Firestore organizes data with collections at the top level, which hold documents.

2. Step 2: Identify what documents contain

   Documents store data as key-value pairs, not collections directly.

3. Final Answer:

   Collections contain documents, and documents contain key-value pairs. -> Option D

4. Quick Check:

   Firestore data = collections > documents > key-value pairs [OK]

Hint: Remember: Collections hold documents, documents hold data [OK]

Common Mistakes:

• Thinking documents hold collections directly
• Assuming collections store key-value pairs without documents
• Confusing the order of collections and documents

2. Which of the following is the correct syntax to get a reference to a document named user123 inside a collection users in Firestore using Node.js?

easy

A. const docRef = firestore.doc('user123/users');

B. const docRef = firestore.collection('users').doc('user123');

C. const docRef = firestore.collection('user123').doc('users');

D. const docRef = firestore.doc('users').doc('user123');

Solution

1. Step 1: Identify correct method to access collection and document

   Use collection('users') to access the collection, then doc('user123') to get the document.

2. Step 2: Check path correctness

   Direct firestore.doc(full/path) works for existing paths, but incorrect paths, reversed order, or misusing doc() on document references fail. Chaining collection().doc() is recommended.

3. Final Answer:

   const docRef = firestore.collection('users').doc('user123'); -> Option B

4. Quick Check:

   Use collection().doc() chaining for document refs [OK]

Hint: Chain collection() then doc() for document reference [OK]

Common Mistakes:

• Swapping collection and document names
• Using firestore.doc() with incorrect path format
• Confusing collection() and doc() order

3. Given the following Firestore code snippet, what will be the output if the document user123 exists with fields {name: 'Alice', age: 30}?

const docRef = firestore.collection('users').doc('user123');
const docSnap = await docRef.get();
if (docSnap.exists) {
  console.log(docSnap.data());
} else {
  console.log('No such document!');
}

medium

A. 'No such document!'

B. undefined

C. { name: 'Alice', age: 30 }

D. Error: Document not found

Solution

1. Step 1: Check if document exists

   The code checks docSnap.exists, which is true if the document is present.

2. Step 2: Output document data

   If exists, docSnap.data() returns the document fields as an object.

3. Final Answer:

   { name: 'Alice', age: 30 } -> Option C

4. Quick Check:

   docSnap.exists true means data() returns fields [OK]

Hint: docSnap.exists true means data() returns document fields [OK]

Common Mistakes:

• Assuming data() returns undefined if document exists
• Confusing exists check with data presence
• Expecting error instead of 'No such document!' message

4. You wrote this Firestore code to get a document but docSnap.exists is false:

const docRef = firestore.collection('users').doc();
const docSnap = await docRef.get();

What is the problem?

medium

A. Missing document ID in doc() causes a reference to a non-existing document.

B. You cannot call get() on a document reference.

C. Collection name 'users' is invalid without quotes.

D. You must use firestore.doc() instead of collection().doc().

Solution

1. Step 1: Check doc() usage

   Calling doc() without an ID creates a reference to a new document with an auto-generated ID, but it does not exist yet.

2. Step 2: Understand get() on new doc reference

   Trying to get() returns a snapshot with exists=false because the document does not exist.

3. Final Answer:

   Missing document ID in doc() causes a reference to a non-existing document. -> Option A

4. Quick Check:

   doc() needs ID to get existing document [OK]

Hint: Always provide document ID in doc() to read existing document [OK]

Common Mistakes:

• Assuming doc() without ID points to existing document
• Thinking get() cannot be called on document references
• Confusing collection and document method usage

5. You want to store user profiles in Firestore where each user has multiple addresses. Which is the best Firestore structure to model this data?

hard

A. A collection 'users' with documents for each user, and each user document has a subcollection 'addresses' with address documents.

B. A single collection 'addresses' with documents containing user info and address fields combined.

C. A collection 'users' where each document stores all addresses as a large array field.

D. Multiple collections named after each user ID, each containing address documents.

Solution

1. Step 1: Understand Firestore best practice for one-to-many

   Use a main collection for users, and subcollections for related multiple items like addresses.

2. Step 2: Evaluate options

   A collection 'users' with documents for each user, and each user document has a subcollection 'addresses' with address documents. uses subcollections for addresses, which is scalable and organized. A single collection 'addresses' with documents containing user info and address fields combined. mixes user and address data in one collection, which is less clear. A collection 'users' where each document stores all addresses as a large array field. stores all addresses in one field, which can be inefficient. Multiple collections named after each user ID, each containing address documents. creates many collections dynamically, which is not recommended.

3. Final Answer:

   A collection 'users' with documents for each user, and each user document has a subcollection 'addresses' with address documents. -> Option A

4. Quick Check:

   Use subcollections for related multiple items [OK]

Hint: Use subcollections for multiple related documents per user [OK]

Common Mistakes:

• Storing multiple addresses in one array field causing size limits
• Creating dynamic collections per user causing management issues
• Mixing unrelated data in one collection