Document size and growth patterns in MongoDB - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the maximum size of a single document in MongoDB?

The maximum size of a single document in MongoDB is 16 megabytes (MB).

intermediate

Why should you avoid frequent growth of a document's size in MongoDB?

Frequent growth can cause document moves in storage, which slows down performance and increases fragmentation.

intermediate

How does MongoDB handle document growth internally?

MongoDB allocates extra space when a document grows to reduce the need for moving it frequently, but if growth exceeds this space, the document is moved to a new location.

beginner

What is a common strategy to manage large or growing data in MongoDB documents?

Use references or subdocuments to split large data into smaller parts instead of growing a single document too large.

beginner

How does document size affect MongoDB query performance?

Larger documents take more time to read and write, which can slow down queries and increase resource use.

What is the maximum size allowed for a MongoDB document?

A 1 MB

B 100 MB

C 16 MB

D 512 KB

MongoDB limits each document to 16 megabytes to ensure efficient storage and retrieval.

What happens if a document grows beyond its allocated space in MongoDB?

A It is moved to a new location with more space

B It is deleted automatically

C It causes the database to crash

D It stays in place and overwrites data

MongoDB moves the document to a new location with enough space to accommodate the growth.

Why is it better to split large data into smaller documents or references?

A To avoid hitting the document size limit and improve performance

B Because MongoDB does not support large documents

C To make queries slower

D To increase storage costs

Splitting data helps keep documents within size limits and improves read/write efficiency.

How does document size affect query speed in MongoDB?

A Document size has no effect

B Larger documents slow down queries

C Smaller documents slow down queries

D Queries are faster with larger documents

Larger documents require more time to read and write, slowing down queries.

What is a sign that a document is growing too frequently?

A Decreased storage use

B Faster query responses

C Automatic document compression

D Increased fragmentation and slower performance

Frequent growth causes fragmentation and slows down database operations.

Explain how MongoDB handles document size limits and what happens when a document grows beyond its allocated space.

Think about storage space and document relocation.

Describe strategies to manage document growth and maintain good performance in MongoDB.

Consider how to keep documents small and efficient.

Practice

1. What is the main reason to keep MongoDB documents reasonably small?

easy

A. To make documents harder to read

B. To avoid using indexes

C. To increase the number of collections

D. To improve database speed and reduce storage costs

Solution

1. Step 1: Understand document size impact

   Larger documents take more space and slow down database operations.

2. Step 2: Connect size with performance and cost

   Smaller documents improve speed and reduce storage needs, saving costs.

3. Final Answer:

   To improve database speed and reduce storage costs -> Option D

4. Quick Check:

   Small documents = faster and cheaper [OK]

Hint: Smaller documents mean faster queries and less storage [OK]

Common Mistakes:

• Thinking bigger documents are always better
• Confusing collections with document size
• Ignoring storage cost impact

2. Which MongoDB command shows statistics including average document size and storage size?

easy

A. db.collection.stats()

B. db.collection.insert()

C. db.collection.find()

D. db.collection.update()

Solution

1. Step 1: Identify command for collection stats

   The command db.collection.stats() returns detailed stats about the collection.

2. Step 2: Confirm it includes document size info

   This command shows average document size, storage size, and growth info.

3. Final Answer:

   db.collection.stats() -> Option A

4. Quick Check:

   Stats command = db.collection.stats() [OK]

Hint: Use .stats() to check collection size and growth info [OK]

Common Mistakes:

• Using find() which only queries documents
• Confusing insert() or update() with stats
• Not knowing stats() returns size info

3. Given a collection with documents growing in size over time, what will db.collection.stats() likely show?

medium

A. Increasing avgObjSize and storageSize values

B. Decreasing avgObjSize and storageSize values

C. No change in avgObjSize but increasing storageSize

D. Only the number of documents changes

Solution

1. Step 1: Understand document growth effect

   As documents grow, their average size (avgObjSize) increases.

2. Step 2: Connect growth to storage size

   More or bigger documents increase storageSize to hold data.

3. Final Answer:

   Increasing avgObjSize and storageSize values -> Option A

4. Quick Check:

   Growth means bigger avgObjSize and storageSize [OK]

Hint: Growth means both average document and storage sizes rise [OK]

Common Mistakes:

• Assuming storage size stays constant
• Thinking avgObjSize decreases with growth
• Ignoring storage size changes

4. You run db.collection.stats() but get an error. Which is a likely cause?

medium

A. You used find() instead of stats()

B. You misspelled the collection name

C. You forgot to connect to MongoDB

D. You ran stats() on a database instead of a collection

Solution

1. Step 1: Check command usage context

   A common error is misspelling the collection name, causing 'ns not found' error since the collection doesn't exist.

2. Step 2: Identify error cause

   db.collection.stats() requires an existing collection; misspelling prevents access.

3. Final Answer:

   You misspelled the collection name -> Option B

4. Quick Check:

   stats() works on existing collections only [OK]

Hint: Verify collection name spelling before running stats() [OK]

Common Mistakes:

• Misspelling the collection name
• Forgetting to connect to MongoDB
• Confusing find() with stats()

5. You have a collection where documents grow unpredictably. What is a good strategy to manage document size and growth?

hard

A. Ignore document size and rely on hardware upgrades

B. Keep all data in one large document to avoid joins

C. Split large documents into smaller related documents using references

D. Delete old documents frequently to reduce size

Solution

1. Step 1: Understand document growth challenges

   Unpredictable growth can cause documents to become too large and slow.

2. Step 2: Apply best practice for size management

   Splitting large documents into smaller ones with references keeps sizes manageable and improves performance.

3. Final Answer:

   Split large documents into smaller related documents using references -> Option C

4. Quick Check:

   Split documents to manage size and growth [OK]

Hint: Use references to split big documents for better growth control [OK]

Common Mistakes:

• Keeping all data in one big document
• Ignoring size issues hoping hardware helps
• Deleting data instead of managing structure