메뉴
Expert-level MongoDB database design, aggregation pipelines, indexing, replication, and production operations
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/personamanagmentlayer/pcl --skill mongodb-expert명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
Expert in Persona Control Language (PCL) - language design, compiler architecture, runtime systems, and ecosystem development
Expert system for designing, creating, and validating PCL skills with comprehensive domain knowledge extraction
Expert-level Docker containerization, image optimization, and container orchestration. Use this skill for building efficient Docker images, managing containers, and implementing Docker best practices.
SOC 직업 분류 기준
SKILL.md 표시 중
| 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.