技能档案

NoSQL Expert - MongoDB & DynamoDB Mastery

Name: NoSQL Expert - MongoDB & DynamoDB Mastery
Author: duylinhdang1998

NoSQL database expertise with MongoDB and DynamoDB from Amazon/Netflix engineers. Use when designing document schemas, optimizing MongoDB queries and indexes, configuring DynamoDB tables with GSI/LSI, implementing data modeling for flexible schemas, handling horizontal scaling, or migrating from SQL to NoSQL. Triggers on MongoDB, DynamoDB, NoSQL, document database, collection design, partition keys, or non-relational database tasks.

duylinhdang19980 星标2026年3月24日

职业
分类: SQL 数据库

技能内容

Purpose: Design and optimize NoSQL databases for flexible schemas, horizontal scaling, and high performance

Agent: Amazon Cloud Architect / Netflix Backend Architect Use When: Building apps with flexible data models, high write throughput, or need for horizontal scaling

MongoDB

Schema Design

// User document
{
  _id: ObjectId("507f1f77bcf86cd799439011"),
  email: "[email protected]",
  name: "John Doe",
  profile: {
    age: 30,
    city: "NYC"
  },
  tags: ["developer", "nodejs"],
  createdAt: ISODate("2024-01-01T00:00:00Z")
}

// Embedded vs Referenced

// ✅ Embed: One-to-few, data belongs together
{
  _id: 1,
  title: "Post",
  comments: [
    { author: "Alice", text: "Great!" },
    { author: "Bob", text: "Thanks!" }
  ]
}

// ✅ Reference: One-to-many, independent entities
{
  _id: 1,
  title: "Post",
  authorId: ObjectId("...")
}

CRUD Operations (Mongoose)

相关技能

NoSQL Expert - MongoDB & DynamoDB Mastery | Skills Pool

import mongoose from 'mongoose'

const userSchema = new mongoose.Schema({
  email: { type: String, required: true, unique: true },
  name: { type: String, required: true },
  profile: {
    age: Number,
    city: String
  },
  tags: [String],
  createdAt: { type: Date, default: Date.now }
})

const User = mongoose.model('User', userSchema)

// Create
const user = await User.create({
  email: '[email protected]',
  name: 'John Doe',
  profile: { age: 30, city: 'NYC' }
})

// Find
const users = await User.find({ 'profile.city': 'NYC' })
const user = await User.findOne({ email: '[email protected]' })

// Update
await User.updateOne(
  { _id: userId },
  { $set: { 'profile.age': 31 } }
)

// Delete
await User.deleteOne({ _id: userId })

// Aggregation
const stats = await User.aggregate([
  { $match: { 'profile.city': 'NYC' } },
  { $group: { _id: '$profile.city', count: { $sum: 1 } } }
])

// Single field
userSchema.index({ email: 1 })

// Compound index
userSchema.index({ 'profile.city': 1, createdAt: -1 })

// Text search
userSchema.index({ name: 'text', 'profile.bio': 'text' })

await User.find({ $text: { $search: 'developer nodejs' } })

// Unique index
userSchema.index({ email: 1 }, { unique: true })

// Single table design
Table: app-data
Partition Key: PK (String)
Sort Key: SK (String)

// User
PK: USER#123
SK: PROFILE
Attributes: { email, name, ... }

// User's posts
PK: USER#123
SK: POST#456
Attributes: { title, content, ... }

// Post
PK: POST#456
SK: METADATA
Attributes: { title, authorId, ... }

import { DynamoDBClient } from '@aws-sdk/client-dynamodb'
import {
  DynamoDBDocumentClient,
  GetCommand,
  PutCommand,
  QueryCommand,
  UpdateCommand
} from '@aws-sdk/lib-dynamodb'

const client = DynamoDBDocumentClient.from(new DynamoDBClient({}))
const TABLE = 'app-data'

// Put item
await client.send(new PutCommand({
  TableName: TABLE,
  Item: {
    PK: 'USER#123',
    SK: 'PROFILE',
    email: '[email protected]',
    name: 'John Doe'
  }
}))

// Get item
const result = await client.send(new GetCommand({
  TableName: TABLE,
  Key: { PK: 'USER#123', SK: 'PROFILE' }
}))

// Query (same partition key)
const posts = await client.send(new QueryCommand({
  TableName: TABLE,
  KeyConditionExpression: 'PK = :pk AND begins_with(SK, :sk)',
  ExpressionAttributeValues: {
    ':pk': 'USER#123',
    ':sk': 'POST#'
  }
}))

// Update
await client.send(new UpdateCommand({
  TableName: TABLE,
  Key: { PK: 'USER#123', SK: 'PROFILE' },
  UpdateExpression: 'SET #name = :name',
  ExpressionAttributeNames: { '#name': 'name' },
  ExpressionAttributeValues: { ':name': 'Jane Doe' }
}))

// Conditional update (optimistic locking)
await client.send(new UpdateCommand({
  TableName: TABLE,
  Key: { PK: 'USER#123', SK: 'PROFILE' },
  UpdateExpression: 'SET balance = balance + :amount',
  ConditionExpression: 'balance >= :min',
  ExpressionAttributeValues: {
    ':amount': 100,
    ':min': 0
  }
}))

// Query by email (not primary key)
GSI: EmailIndex
Partition Key: email
Sort Key: -

await client.send(new QueryCommand({
  TableName: TABLE,
  IndexName: 'EmailIndex',
  KeyConditionExpression: 'email = :email',
  ExpressionAttributeValues: {
    ':email': '[email protected]'
  }
}))

NoSQL Expert - MongoDB & DynamoDB Mastery

MongoDB

Schema Design

CRUD Operations (Mongoose)

NoSQL Expert - MongoDB & DynamoDB Mastery

MongoDB

Schema Design

CRUD Operations (Mongoose)

Indexes

DynamoDB

Table Design

Operations (AWS SDK v3)

Global Secondary Index (GSI)

Best Practices

MongoDB

DynamoDB

Postgres Patterns

Postgres Patterns

Database Migrations

Postgres Patterns

Postgres Patterns

Jpa Patterns