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Showing of 52What is MongoDB and what are its key features?
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MongoDB is a document-oriented NoSQL database that stores data in flexible, JSON-like documents called BSON (Binary JSON). Key features include:
- Document-based storage: Data is stored in documents rather than rows and columns
- Schema flexibility: Documents in a collection can have different structures
- Horizontal scalability: Built-in support for sharding across multiple servers
- Rich query language: Supports complex queries, indexing, and aggregation
- High availability: Replica sets provide automatic failover
- GridFS: For storing large files
- ACID transactions: Support for multi-document transactions
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Explain the difference between SQL and NoSQL databases. Why choose MongoDB?
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SQL Databases:
- Structured data with predefined schema
- ACID compliance
- Vertical scaling
- Complex joins
- Mature ecosystem
NoSQL Databases (MongoDB):
- Flexible schema design
- Horizontal scaling
- Better performance for certain use cases
- Document-based storage matches application objects
- Easier development for modern applications
Choose MongoDB when:
- You need flexible schema
- Rapid development cycles
- Horizontal scaling requirements
- Working with semi-structured data
- Building modern web applications
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What is BSON and how does it differ from JSON?
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BSON (Binary JSON) is the binary representation of JSON-like documents that MongoDB uses internally.
Key differences:
- Storage: BSON is binary, JSON is text
- Data types: BSON supports additional types like ObjectId, Date, Binary
- Performance: BSON is faster to parse and process
- Size: BSON can be larger due to additional metadata
- Traversal: BSON allows efficient traversal of documents
Example BSON types not in JSON:
{
_id: ObjectId("507f1f77bcf86cd799439011"),
created: ISODate("2023-01-01T12:00:00Z"),
data: BinData(0, "SGVsbG8gV29ybGQ=")
}
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Explain MongoDB's data hierarchy: Database, Collection, Document.
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MongoDB organizes data in a three-level hierarchy:
Database: Top-level container for collections
- Contains multiple collections
- Each database has its own files on disk
- Default databases: admin, local, config
Collection: Group of MongoDB documents
- Equivalent to a table in RDBMS
- Documents in a collection can have different schemas
- Collections are created automatically when first document is inserted
Document: Individual record in a collection
- JSON-like structure stored as BSON
- Can contain nested documents and arrays
- Maximum size: 16MB
Example structure:
Database: ecommerce
├── Collection: users
│ ├── Document: {_id: 1, name: "John", email: "john@email.com"}
│ └── Document: {_id: 2, name: "Jane", age: 25, city: "NYC"}
└── Collection: products
└── Document: {_id: 1, title: "Laptop", price: 999.99}
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What is ObjectId in MongoDB?
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ObjectId is a 12-byte unique identifier used as the default value for the _id field.
Structure (24 hex characters):
- 4 bytes: Unix timestamp
- 5 bytes: Random unique value
- 3 bytes: Incrementing counter
Properties:
- Automatically generated if not provided
- Contains creation timestamp
- Globally unique across machines
- Sortable by creation time
// ObjectId example
ObjectId("507f1f77bcf86cd799439011")
// Extract timestamp
ObjectId("507f1f77bcf86cd799439011").getTimestamp()
// Returns: ISODate("2012-10-17T20:46:47Z")
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Explain the basic CRUD operations in MongoDB.
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Create:
// Insert one document
db.users.insertOne({name: "John", age: 30})
// Insert multiple documents
db.users.insertMany([
{name: "Alice", age: 25},
{name: "Bob", age: 35}
])
Read:
// Find all documents
db.users.find()
// Find with criteria
db.users.find({age: {$gte: 25}})
// Find one document
db.users.findOne({name: "John"})
Update:
// Update one document
db.users.updateOne(
{name: "John"},
{$set: {age: 31}}
)
// Update multiple documents
db.users.updateMany(
{age: {$lt: 30}},
{$set: {status: "young"}}
)
Delete:
// Delete one document
db.users.deleteOne({name: "John"})
// Delete multiple documents
db.users.deleteMany({age: {$lt: 18}})
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Explain the difference between find() and findOne() methods.
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find():
- Returns a cursor to all matching documents
- Returns multiple documents
- Lazy evaluation - documents loaded as needed
- Can be chained with other methods
findOne():
- Returns the first matching document
- Returns a single document object or null
- Immediately executes and returns result
- Cannot be chained with cursor methods
// find() - returns cursor
const cursor = db.users.find({age: {$gte: 25}})
cursor.forEach(doc => print(doc.name))
// findOne() - returns document
const user = db.users.findOne({email: "john@email.com"})
if (user) {
print(user.name)
}
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What are MongoDB query operators? Provide examples.
How do you perform updates in MongoDB? Explain update operators.
What is upsert in MongoDB?
What are indexes in MongoDB and why are they important?
Explain the difference between single field and compound indexes.
What are sparse and partial indexes?
How do you analyze query performance using explain()?
What is a multikey index?
What is MongoDB's Aggregation Framework?
Explain the most commonly used aggregation pipeline stages.
How do you perform joins in MongoDB using $lookup?
What are aggregation operators and provide examples?
Explain $group stage and its accumulator operators.
What are the principles of schema design in MongoDB?
When should you embed vs reference documents?
How do you handle one-to-many relationships in MongoDB?
What is the difference between normalized and denormalized data models?
How do you identify slow queries in MongoDB?
What is the working set and why is it important?
Explain MongoDB's storage engines.
How does MongoDB handle memory management?
What is replication in MongoDB and how does it work?
Explain the concept of oplog in MongoDB.
What happens during replica set elections?
How do you configure read preferences in MongoDB?
How do you implement authentication in MongoDB?
Explain MongoDB's role-based access control (RBAC).
Does MongoDB support ACID transactions?
How do you backup and restore MongoDB databases?
How do you monitor MongoDB performance?
Explain MongoDB log analysis and troubleshooting.
What are MongoDB GridFS and when would you use it?
What are Text Indexes and how do you implement text search?
What are Capped Collections and their use cases?
How do you design schema for time-series data?
What are the best practices for MongoDB performance optimization?
What is sharding in MongoDB and when should you use it?
How do you choose a good shard key?
Explain the role of config servers in sharding.
What is chunk migration and how does the balancer work?
How do you secure MongoDB in production?
How do you implement multi-document transactions?
What are the performance considerations for transactions?
Explain MongoDB Change Streams.
How do you implement geospatial queries in MongoDB?
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MongoDB cheatsheet
- MongoDB Basics01
- CRUD Operations02
- Query Operators03
- Indexes04
- Aggregation Framework05
- Data Modeling06
- Transactions07
- Replication & Sharding08
- Performance Optimization09
- Security10
- Use Cases & Design Patterns11
- Key Takeaways12
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