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Expert-level MongoDB database design, aggregation pipelines, indexing, replication, and production operations
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基于 SOC 职业分类
| name | mongodb-expert |
| version | 1.0.0 |
| description | Expert-level MongoDB database design, aggregation pipelines, indexing, replication, and production operations |
| category | data |
| author | PCL Team |
| license | Apache-2.0 |
| tags | ["mongodb","nosql","database","aggregation","performance"] |
| allowed-tools | ["Read","Write","Edit","Bash(mongosh:*, mongo:*, mongod:*, mongodump:*, mongorestore:*)","Glob","Grep"] |
| requirements | {"mongodb":">=7.0"} |
You are an expert in MongoDB with deep knowledge of document modeling, aggregation pipelines, indexing strategies, replication, sharding, and production operations. You design and manage performant, scalable MongoDB databases following best practices.
Insert:
// Insert one document
db.users.insertOne({
name: "Alice",
email: "alice@example.com",
age: 30,
tags: ["admin", "developer"],
createdAt: new Date()
});
// Insert many documents
db.users.insertMany([
{ name: "Bob", email: "bob@example.com", age: 25 },
{ name: "Charlie", email: "charlie@example.com", age: 35 }
]);
Find:
// Find all
db.users.find();
// Find with filter
db.users.find({ age: { $gt: 25 } });
// Find one
db.users.findOne({ email: "alice@example.com" });
// Projection (select fields)
db..(
{ : { : } },
{ : , : , : }
);
db..()
.({ : - })
.()
.();
db..({ : { : } });
db..();
Update:
// Update one
db.users.updateOne(
{ email: "alice@example.com" },
{ $set: { age: 31, updatedAt: new Date() } }
);
// Update many
db.users.updateMany(
{ age: { $lt: 18 } },
{ $set: { isMinor: true } }
);
// Replace one
db.users.replaceOne(
{ email: "alice@example.com" },
{ name: "Alice Smith", email: "alice@example.com", age: 31 }
);
// Update operators
db.users.updateOne(
{ _id: ObjectId("...") },
{
$set: { name: "Alice" },
$inc: { loginCount: 1 },
$push: { tags: "moderator" },
$pull: { tags: "guest" },
$addToSet: { roles: "admin" }, // Add if not exists
$currentDate: { lastModified: true }
}
);
// Upsert
db.users.updateOne(
{ email: "dave@example.com" },
{ $set: { name: "Dave", age: 28 } },
{ upsert: true }
);
Delete:
// Delete one
db.users.deleteOne({ email: "alice@example.com" });
// Delete many
db.users.deleteMany({ age: { $lt: 18 } });
// Find and modify
db.users.findOneAndUpdate(
{ email: "alice@example.com" },
{ $inc: { age: 1 } },
{ returnDocument: "after" }
);
db.users.findOneAndDelete({ email: "alice@example.com" });
Comparison:
// $eq, $ne, $gt, $gte, $lt, $lte, $in, $nin
db.users.find({ age: { $eq: 30 } });
db.users.find({ age: { $ne: 30 } });
db.users.find({ age: { $gt: 25, $lt: 35 } });
db.users.find({ role: { $in: ["admin", "moderator"] } });
db.users.find({ role: { $nin: ["guest", "banned"] } });
Logical:
// $and, $or, $not, $nor
db.users.find({
$and: [
{ age: { $gt: 25 } },
{ role: "admin" }
]
});
db.users.find({
$or: [
{ age: { $lt: 18 } },
{ age: { $gt: 65 } }
]
});
db.users.find({
age: { $not: { $lt: 18 } }
});
Element:
// $exists, $type
db.users.find({ phone: { $exists: true } });
db.users.find({ age: { $type: "number" } });
db.users.find({ tags: { $type: "array" } });
Array:
// $all, $elemMatch, $size
db.users.find({ tags: { $all: ["admin", "developer"] } });
db.orders.find({
items: {
$elemMatch: {
price: { $gt: 100 },
quantity: { $gte: 2 }
}
}
});
db.users.find({ tags: { $size: 3 } });
Text Search:
// Create text index
db.articles.createIndex({ title: "text", content: "text" });
// Search
db.articles.find({ $text: { $search: "mongodb tutorial" } });
// Search with score
db.articles.find(
{ $text: { $search: "mongodb tutorial" } },
{ score: { $meta: "textScore" } }
).sort({ score: { $meta: "textScore" } });
Basic Pipeline:
db.orders.aggregate([
// Match documents
{ $match: { status: "completed" } },
// Group and calculate
{ $group: {
_id: "$userId",
totalSpent: { $sum: "$total" },
orderCount: { $sum: 1 },
avgOrder: { $avg: "$total" }
}},
// Sort results
{ $sort: { totalSpent: -1 } },
// Limit results
{ $limit: 10 },
// Project (select fields)
{ $project: {
_id: 0,
userId: "$_id",
totalSpent: 1,
orderCount: 1,
avgOrder: { $round: ["$avgOrder", 2] }
}}
]);
Advanced Stages:
// $lookup (join)
db.orders.aggregate([
{
$lookup: {
from: "users",
localField: "userId",
foreignField: "_id",
as: "user"
}
},
{ $unwind: "$user" },
{
$project: {
orderId: "$_id",
total: 1,
userName: "$user.name",
userEmail: "$user.email"
}
}
]);
// $unwind (flatten arrays)
db.posts.aggregate([
{ $unwind: "$tags" },
{ $group: {
_id: "$tags",
count: { $sum: 1 }
}}
]);
// $facet (multiple pipelines)
db.products.aggregate([
{
$facet: {
byCategory: [
{ $group: { _id: "$category", count: { $sum: 1 } }},
{ $sort: { count: -1 } }
],
priceRanges: [
{ $bucket: {
groupBy: "$price",
boundaries: [0, 50, 100, 200, 500],
default: "500+",
output: { count: { $sum: 1 } }
}}
],
totalStats: [
{ $group: {
_id: null,
total: { $sum: 1 },
avgPrice: { $avg: "$price" },
maxPrice: { $max: "$price" }
}}
]
}
}
]);
// $addFields
db.users.aggregate([
{
$addFields: {
fullName: { $concat: ["$firstName", " ", "$lastName"] },
isAdult: { $gte: ["$age", 18] }
}
}
]);
// $replaceRoot
db.orders.aggregate([
{ $match: { status: "completed" } },
{ $replaceRoot: { newRoot: "$billing" } }
]);
Aggregation Operators:
db.orders.aggregate([
{
$project: {
// Arithmetic
totalWithTax: { $multiply: ["$total", 1.1] },
discount: { $divide: ["$total", 10] },
// String
upperName: { $toUpper: "$customerName" },
emailDomain: { $substr: ["$email", { $indexOfCP: ["$email", "@"] }, -1] },
// Date
year: { $year: "$createdAt" },
month: { $month: "$createdAt" },
dayOfWeek: { $dayOfWeek: "$createdAt" },
// Conditional
status: {
$cond: {
if: { $gte: ["$total", 100] },
then: "high-value",
else: "normal"
}
},
// Array
itemCount: { $size: "$items" },
firstItem: { $arrayElemAt: ["$items", 0] },
itemNames: { $map: {
input: "$items",
as: "item",
in: "$$item.name"
}}
}
}
]);
Index Types:
// Single field index
db.users.createIndex({ email: 1 }); // Ascending
db.users.createIndex({ age: -1 }); // Descending
// Compound index
db.users.createIndex({ age: 1, name: 1 });
// Multikey index (for arrays)
db.users.createIndex({ tags: 1 });
// Text index
db.articles.createIndex({ title: "text", content: "text" });
// Geospatial index
db.locations.createIndex({ coordinates: "2dsphere" });
// Hashed index (for sharding)
db.users.createIndex({ userId: "hashed" });
// TTL index (auto-delete documents)
db.sessions.createIndex(
{ createdAt: 1 },
{ expireAfterSeconds: 3600 }
);
// Unique index
db.users.createIndex(
{ email: 1 },
{ unique: true }
);
// Partial index
db.users.createIndex(
{ email: 1 },
{ partialFilterExpression: { age: { $gte: 18 } } }
);
// Sparse index
db.users.createIndex(
{ phone: 1 },
{ sparse: true }
);
Index Management:
// List indexes
db.users.getIndexes();
// Drop index
db.users.dropIndex("email_1");
db.users.dropIndex({ email: 1 });
// Rebuild indexes
db.users.reIndex();
// Index stats
db.users.aggregate([{ $indexStats: {} }]);
// Explain query plan
db.users.find({ email: "alice@example.com" }).explain("executionStats");
Embedded Documents:
// One-to-Few: Embed
{
_id: ObjectId("..."),
name: "Alice",
email: "alice@example.com",
address: {
street: "123 Main St",
city: "New York",
zip: "10001"
},
phones: [
{ type: "home", number: "555-1234" },
{ type: "work", number: "555-5678" }
]
}
References:
// One-to-Many: Reference
// User document
{
_id: ObjectId("user123"),
name: "Alice",
email: "alice@example.com"
}
// Order documents
{
_id: ObjectId("order1"),
userId: ObjectId("user123"),
total: 99.99,
items: [...]
}
// Query with $lookup
db.users.aggregate([
{
$lookup: {
from: "orders",
localField: "_id",
foreignField: "userId",
as: "orders"
}
}
]);
Denormalization:
// Duplicate frequently accessed data
{
_id: ObjectId("order1"),
userId: ObjectId("user123"),
user: { // Denormalized
name: "Alice",
email: "alice@example.com"
},
total: 99.99,
items: [...]
}
Multi-Document Transactions:
const session = db.getMongo().startSession();
try {
session.startTransaction();
const accountsCol = session.getDatabase("mydb").getCollection("accounts");
// Transfer money
accountsCol.updateOne(
{ _id: "account1" },
{ $inc: { balance: -100 } },
{ session }
);
accountsCol.updateOne(
{ _id: "account2" },
{ $inc: { balance: 100 } },
{ session }
);
session.commitTransaction();
} catch (error) {
session.abortTransaction();
throw error;
} finally {
session.endSession();
}
Replica Set Setup:
// Initialize replica set
rs.initiate({
_id: "rs0",
members: [
{ _id: 0, host: "mongo1:27017", priority: 2 },
{ _id: 1, host: "mongo2:27017", priority: 1 },
{ _id: 2, host: "mongo3:27017", priority: 1, arbiterOnly: true }
]
});
// Check replica set status
rs.status();
// Add member
rs.add("mongo4:27017");
// Remove member
rs.remove("mongo4:27017");
// Step down primary
rs.stepDown();
Read Preferences:
// Primary (default)
db.users.find().readPref("primary");
// Secondary
db.users.find().readPref("secondary");
// Nearest
db.users.find().readPref("nearest");
Write Concerns:
db.users.insertOne(
{ name: "Alice" },
{ writeConcern: { w: "majority", wtimeout: 5000 } }
);
Profiling:
// Enable profiling
db.setProfilingLevel(2); // Profile all operations
db.setProfilingLevel(1, { slowms: 100 }); // Profile slow operations
// View profile data
db.system.profile.find().sort({ ts: -1 }).limit(10);
// Disable profiling
db.setProfilingLevel(0);
Explain:
db.users.find({ age: { $gt: 25 } }).explain("executionStats");
// Look for:
// - totalDocsExamined vs totalDocsReturned
// - executionTimeMillis
// - Index usage (IXSCAN vs COLLSCAN)
Hints:
// Force index usage
db.users.find({ age: 25, name: "Alice" })
.hint({ age: 1, name: 1 });
// Embed when:
// - One-to-few relationship
// - Data doesn't change often
// - Need atomic updates
// Reference when:
// - One-to-many or many-to-many
// - Data changes frequently
// - Documents would exceed 16MB
// Index fields used in:
// - Queries ($match, find)
// - Sorts ($sort)
// - Joins ($lookup)
// Avoid:
// - Too many indexes (slows writes)
// - Indexes on fields with low cardinality
// Put $match early in pipeline
// Use $limit after $sort
// Use indexes with $match and $sort
// Choose shard key carefully
// High cardinality
// Good distribution
// Query isolation
// Use connection pools
// Don't create new connections for each operation
const client = new MongoClient(uri, {
maxPoolSize: 10,
minPoolSize: 2
});
When working with MongoDB:
Always design MongoDB databases that are performant, scalable, and maintainable.