cloudflare-d1

Cloudflare D1 数据库

状态：已可用于生产环境 ✅ 最后更新：2025-10-21 依赖项：cloudflare-worker-base（用于 Worker 设置） 最新版本：[email protected]、@cloudflare/[email protected]

---

快速入门（5 分钟）

1. 创建 D1 数据库

# Create a new D1 database
npx wrangler d1 create my-database

# Output includes database_id - save this!
# ✅ Successfully created DB 'my-database'
#
# [[d1_databases]]
# binding = "DB"
# database_name = "my-database"
# database_id = "<UUID>"

2. 配置绑定

在 wrangler.jsonc 中添加：

{
  "name": "my-worker",
  "main": "src/index.ts",
  "compatibility_date": "2025-10-11",
  "d1_databases": [
    {
      "binding": "DB",                    // Available as env.DB in your Worker
      "database_name": "my-database",      // Name from wrangler d1 create
      "database_id": "<UUID>",             // ID from wrangler d1 create
      "preview_database_id": "local-db"    // For local development
    }
  ]
}

重要：

• binding 是你在代码中访问数据库的方式（env.DB）
• database_id 是生产数据库 UUID
• preview_database_id 用于本地开发（可以是任意字符串）
• 切勿将真实的 database_id 值提交到公开仓库——请使用环境变量或密钥

3. 创建第一个迁移

# Create migration file
npx wrangler d1 migrations create my-database create_users_table

# This creates: migrations/0001_create_users_table.sql

编辑迁移文件：

-- migrations/0001_create_users_table.sql
DROP TABLE IF EXISTS users;
CREATE TABLE IF NOT EXISTS users (
  user_id INTEGER PRIMARY KEY AUTOINCREMENT,
  email TEXT NOT NULL UNIQUE,
  username TEXT NOT NULL,
  created_at INTEGER NOT NULL,
  updated_at INTEGER
);

-- Create index for common queries
CREATE INDEX IF NOT EXISTS idx_users_email ON users(email);

-- Optimize database
PRAGMA optimize;

4. 应用迁移

# Apply locally first (for testing)
npx wrangler d1 migrations apply my-database --local

# Apply to production when ready
npx wrangler d1 migrations apply my-database --remote

5. 从 Worker 查询

// src/index.ts
import { Hono } from 'hono';

type Bindings = {
  DB: D1Database;
};

const app = new Hono<{ Bindings: Bindings }>();

app.get('/api/users/:email', async (c) => {
  const email = c.req.param('email');

  try {
    // ALWAYS use prepared statements with bind()
    const result = await c.env.DB.prepare(
      'SELECT * FROM users WHERE email = ?'
    )
    .bind(email)
    .first();

    if (!result) {
      return c.json({ error: 'User not found' }, 404);
    }

    return c.json(result);
  } catch (error: any) {
    console.error('D1 Error:', error.message);
    return c.json({ error: 'Database error' }, 500);
  }
});

export default app;

---

D1 迁移系统

迁移工作流

# 1. Create migration
npx wrangler d1 migrations create <DATABASE_NAME> <MIGRATION_NAME>

# 2. List unapplied migrations
npx wrangler d1 migrations list <DATABASE_NAME> --local
npx wrangler d1 migrations list <DATABASE_NAME> --remote

# 3. Apply migrations
npx wrangler d1 migrations apply <DATABASE_NAME> --local   # Test locally
npx wrangler d1 migrations apply <DATABASE_NAME> --remote  # Deploy to production

迁移文件命名

迁移会自动进行版本管理：

migrations/
├── 0000_initial_schema.sql
├── 0001_add_users_table.sql
├── 0002_add_posts_table.sql
└── 0003_add_indexes.sql

规则：

• 文件按顺序依次执行
• 每个迁移只运行一次（记录在 d1_migrations 表中）
• 迁移失败时会回滚（事务性）
• 无法修改或删除已应用的迁移

自定义迁移配置

{
  "d1_databases": [
    {
      "binding": "DB",
      "database_name": "my-database",
      "database_id": "<UUID>",
      "migrations_dir": "db/migrations",        // Custom directory (default: migrations/)
      "migrations_table": "schema_migrations"   // Custom tracking table (default: d1_migrations)
    }
  ]
}

迁移最佳实践

✅ 务必执行：

-- Use IF NOT EXISTS to make migrations idempotent
CREATE TABLE IF NOT EXISTS users (...);
CREATE INDEX IF NOT EXISTS idx_users_email ON users(email);

-- Run PRAGMA optimize after schema changes
PRAGMA optimize;

-- Use transactions for data migrations
BEGIN TRANSACTION;
UPDATE users SET updated_at = unixepoch() WHERE updated_at IS NULL;
COMMIT;

❌ 切勿执行：

-- DON'T include BEGIN TRANSACTION at start (D1 handles this)
BEGIN TRANSACTION;  -- ❌ Remove this

-- DON'T use MySQL/PostgreSQL syntax
ALTER TABLE users MODIFY COLUMN email VARCHAR(255);  -- ❌ Not SQLite

-- DON'T create tables without IF NOT EXISTS
CREATE TABLE users (...);  -- ❌ Fails if table exists

在迁移中处理外键

-- Temporarily disable foreign key checks during schema changes
PRAGMA defer_foreign_keys = true;

-- Make schema changes that would violate foreign keys
ALTER TABLE posts DROP COLUMN author_id;
ALTER TABLE posts ADD COLUMN user_id INTEGER REFERENCES users(user_id);

-- Foreign keys re-enabled automatically at end of migration

---

D1 Workers API

类型定义

// Add to env.d.ts or worker-configuration.d.ts
interface Env {
  DB: D1Database;
  // ... other bindings
}

// For Hono
type Bindings = {
  DB: D1Database;
};

const app = new Hono<{ Bindings: Bindings }>();

prepare() - 预处理语句（主要方法）

对于包含用户输入的查询，务必使用预处理语句。

// Basic prepared statement
const stmt = env.DB.prepare('SELECT * FROM users WHERE user_id = ?');
const bound = stmt.bind(userId);
const result = await bound.first();

// Chained (most common pattern)
const user = await env.DB.prepare('SELECT * FROM users WHERE email = ?')
  .bind(email)
  .first();

使用 prepare() 的原因：

• ✅ 防止 SQL 注入
• ✅ 可使用不同参数重复执行
• ✅ 性能更好（查询计划缓存）
• ✅ 与 TypeScript 配合时具备类型安全性

查询结果方法

.all() - 获取所有行

const { results, meta } = await env.DB.prepare(
  'SELECT * FROM users WHERE created_at > ?'
)
.bind(timestamp)
.all();

console.log(results);  // Array of rows
console.log(meta);     // { duration, rows_read, rows_written }

.first() - 获取第一行

// Returns first row or null
const user = await env.DB.prepare('SELECT * FROM users WHERE email = ?')
  .bind('[email protected]')
  .first();

if (!user) {
  return c.json({ error: 'Not found' }, 404);
}

.first(column) - 获取单列值

// Returns the value of a specific column from first row
const count = await env.DB.prepare('SELECT COUNT(*) as total FROM users')
  .first('total');

console.log(count);  // 42 (just the number, not an object)

.run() - 执行但不返回结果

// For INSERT, UPDATE, DELETE
const { success, meta } = await env.DB.prepare(
  'INSERT INTO users (email, username, created_at) VALUES (?, ?, ?)'
)
.bind(email, username, Date.now())
.run();

console.log(meta);  // { duration, rows_read, rows_written, last_row_id }

batch() - 执行多个查询

对性能至关重要：使用 batch() 降低延迟。

// Prepare multiple statements
const stmt1 = env.DB.prepare('SELECT * FROM users WHERE user_id = ?').bind(1);
const stmt2 = env.DB.prepare('SELECT * FROM users WHERE user_id = ?').bind(2);
const stmt3 = env.DB.prepare('SELECT * FROM posts WHERE user_id = ?').bind(1);

// Execute all in one round trip
const results = await env.DB.batch([stmt1, stmt2, stmt3]);

console.log(results[0].results);  // Users query 1
console.log(results[1].results);  // Users query 2
console.log(results[2].results);  // Posts query

批处理行为：

• 按顺序依次执行
• 每条语句单独提交（自动提交模式）
• 如果某条语句失败，后续语句不会执行
• 比单独执行查询快得多（只需一次网络往返）

批处理的使用场景：

// ✅ Insert multiple rows efficiently
const inserts = users.map(user =>
  env.DB.prepare('INSERT INTO users (email, username) VALUES (?, ?)')
    .bind(user.email, user.username)
);
await env.DB.batch(inserts);

// ✅ Fetch related data in parallel
const [user, posts, comments] = await env.DB.batch([
  env.DB.prepare('SELECT * FROM users WHERE user_id = ?').bind(userId),
  env.DB.prepare('SELECT * FROM posts WHERE user_id = ?').bind(userId),
  env.DB.prepare('SELECT * FROM comments WHERE user_id = ?').bind(userId)
]);

exec() - 执行原始 SQL（生产环境中避免使用）

// Only for migrations, maintenance, and one-off tasks
const result = await env.DB.exec(`
  SELECT * FROM users;
  SELECT * FROM posts;
`);

console.log(result);  // { count: 2, duration: 5 }

切勿在以下情况使用 exec()：

• ❌ 包含用户输入的查询（有 SQL 注入风险）
• ❌ 生产环境查询（性能较差）
• ❌ 需要结果的查询（exec 不会返回数据）

仅在以下情况使用 exec()：

• ✅ 在本地运行迁移 SQL 文件
• ✅ 一次性维护任务
• ✅ 数据库初始化脚本

---

查询模式

基本 CRUD 操作

创建（INSERT）

// Single insert
const { meta } = await env.DB.prepare(
  'INSERT INTO users (email, username, created_at) VALUES (?, ?, ?)'
)
.bind(email, username, Date.now())
.run();

const newUserId = meta.last_row_id;

// Bulk insert with batch()
const users = [
  { email: '[email protected]', username: 'user1' },
  { email: '[email protected]', username: 'user2' }
];

const inserts = users.map(u =>
  env.DB.prepare('INSERT INTO users (email, username, created_at) VALUES (?, ?, ?)')
    .bind(u.email, u.username, Date.now())
);

await env.DB.batch(inserts);

读取（SELECT）

// Single row
const user = await env.DB.prepare('SELECT * FROM users WHERE user_id = ?')
  .bind(userId)
  .first();

// Multiple rows
const { results } = await env.DB.prepare(
  'SELECT * FROM users WHERE created_at > ? ORDER BY created_at DESC LIMIT ?'
)
.bind(timestamp, 10)
.all();

// Count
const count = await env.DB.prepare('SELECT COUNT(*) as total FROM users')
  .first('total');

// Exists check
const exists = await env.DB.prepare('SELECT 1 FROM users WHERE email = ? LIMIT 1')
  .bind(email)
  .first();

if (exists) {
  // Email already registered
}

更新（UPDATE）

const { meta } = await env.DB.prepare(
  'UPDATE users SET username = ?, updated_at = ? WHERE user_id = ?'
)
.bind(newUsername, Date.now(), userId)
.run();

const rowsAffected = meta.rows_written;

if (rowsAffected === 0) {
  // User not found
}

删除（DELETE）

const { meta } = await env.DB.prepare('DELETE FROM users WHERE user_id = ?')
  .bind(userId)
  .run();

const rowsDeleted = meta.rows_written;

高级查询

分页

app.get('/api/users', async (c) => {
  const page = parseInt(c.req.query('page') || '1');
  const limit = parseInt(c.req.query('limit') || '20');
  const offset = (page - 1) * limit;

  const [countResult, usersResult] = await c.env.DB.batch([
    c.env.DB.prepare('SELECT COUNT(*) as total FROM users'),
    c.env.DB.prepare('SELECT * FROM users ORDER BY created_at DESC LIMIT ? OFFSET ?')
      .bind(limit, offset)
  ]);

  const total = countResult.results[0].total as number;
  const users = usersResult.results;

  return c.json({
    users,
    pagination: {
      page,
      limit,
      total,
      pages: Math.ceil(total / limit)
    }
  });
});

联接

const { results } = await env.DB.prepare(`
  SELECT
    posts.*,
    users.username as author_name,
    users.email as author_email
  FROM posts
  INNER JOIN users ON posts.user_id = users.user_id
  WHERE posts.published = ?
  ORDER BY posts.created_at DESC
  LIMIT ?
`)
.bind(1, 10)
.all();

事务（批处理模式）

D1 不支持多语句事务，但 batch() 可按顺序执行：

// Transfer credits between users (pseudo-transaction)
await env.DB.batch([
  env.DB.prepare('UPDATE users SET credits = credits - ? WHERE user_id = ?')
    .bind(amount, fromUserId),
  env.DB.prepare('UPDATE users SET credits = credits + ? WHERE user_id = ?')
    .bind(amount, toUserId),
  env.DB.prepare('INSERT INTO transactions (from_user, to_user, amount) VALUES (?, ?, ?)')
    .bind(fromUserId, toUserId, amount)
]);

注意：如果任意语句失败，批处理就会停止。这提供了某种类似事务的行为。

---

错误处理

错误类型

try {
  const result = await env.DB.prepare('SELECT * FROM users WHERE user_id = ?')
    .bind(userId)
    .first();
} catch (error: any) {
  // D1 errors have a message property
  const errorMessage = error.message;

  if (errorMessage.includes('D1_ERROR')) {
    // D1-specific error
  } else if (errorMessage.includes('D1_EXEC_ERROR')) {
    // SQL syntax error
  } else if (errorMessage.includes('D1_TYPE_ERROR')) {
    // Type mismatch (e.g., undefined instead of null)
  } else if (errorMessage.includes('D1_COLUMN_NOTFOUND')) {
    // Column doesn't exist
  }

  console.error('Database error:', errorMessage);
  return c.json({ error: 'Database operation failed' }, 500);
}

常见错误及修复方法

“Statement too long”

// ❌ DON'T: Single massive INSERT
await env.DB.exec(`
  INSERT INTO users (email) VALUES
    ('[email protected]'),
    ('[email protected]'),
    ... // 1000 more rows
`);

// ✅ DO: Break into batches
const batchSize = 100;
for (let i = 0; i < users.length; i += batchSize) {
  const batch = users.slice(i, i + batchSize);
  const inserts = batch.map(u =>
    env.DB.prepare('INSERT INTO users (email) VALUES (?)').bind(u.email)
  );
  await env.DB.batch(inserts);
}

“Too many requests queued”

// ❌ DON'T: Fire off many individual queries
for (const user of users) {
  await env.DB.prepare('INSERT INTO users (email) VALUES (?)').bind(user.email).run();
}

// ✅ DO: Use batch()
const inserts = users.map(u =>
  env.DB.prepare('INSERT INTO users (email) VALUES (?)').bind(u.email)
);
await env.DB.batch(inserts);

“D1_TYPE_ERROR”（undefined 与 null）

// ❌ DON'T: Use undefined
await env.DB.prepare('INSERT INTO users (email, bio) VALUES (?, ?)')
  .bind(email, undefined);  // ❌ D1 doesn't support undefined

// ✅ DO: Use null for optional values
await env.DB.prepare('INSERT INTO users (email, bio) VALUES (?, ?)')
  .bind(email, bio || null);

重试逻辑

async function queryWithRetry<T>(
  queryFn: () => Promise<T>,
  maxRetries = 3
): Promise<T> {
  for (let attempt = 0; attempt < maxRetries; attempt++) {
    try {
      return await queryFn();
    } catch (error: any) {
      const message = error.message;

      // Retry on transient errors
      const isRetryable =
        message.includes('Network connection lost') ||
        message.includes('storage caused object to be reset') ||
        message.includes('reset because its code was updated');

      if (!isRetryable || attempt === maxRetries - 1) {
        throw error;
      }

      // Exponential backoff
      const delay = Math.min(1000 * Math.pow(2, attempt), 5000);
      await new Promise(resolve => setTimeout(resolve, delay));
    }
  }

  throw new Error('Retry logic failed');
}

// Usage
const user = await queryWithRetry(() =>
  env.DB.prepare('SELECT * FROM users WHERE user_id = ?')
    .bind(userId)
    .first()
);

---

性能优化

索引

索引可大幅提升筛选列的查询性能。

何时创建索引

// ✅ Index columns used in WHERE clauses
CREATE INDEX idx_users_email ON users(email);

// ✅ Index foreign keys
CREATE INDEX idx_posts_user_id ON posts(user_id);

// ✅ Index columns used for sorting
CREATE INDEX idx_posts_created_at ON posts(created_at DESC);

// ✅ Multi-column indexes for complex queries
CREATE INDEX idx_posts_user_published ON posts(user_id, published);

测试索引使用情况

-- Check if index is being used
EXPLAIN QUERY PLAN SELECT * FROM users WHERE email = '[email protected]';

-- Should see: SEARCH users USING INDEX idx_users_email

部分索引

-- Index only non-deleted records
CREATE INDEX idx_users_active ON users(email) WHERE deleted = 0;

-- Index only published posts
CREATE INDEX idx_posts_published ON posts(created_at DESC) WHERE published = 1;

PRAGMA optimize

创建索引或更改架构后运行：

-- In your migration file
CREATE INDEX idx_users_email ON users(email);
PRAGMA optimize;

或从 Worker 中运行：

await env.DB.exec('PRAGMA optimize');

查询优化提示

// ✅ Use specific columns instead of SELECT *
const users = await env.DB.prepare(
  'SELECT user_id, email, username FROM users'
).all();

// ✅ Use LIMIT to prevent scanning entire table
const latest = await env.DB.prepare(
  'SELECT * FROM posts ORDER BY created_at DESC LIMIT 10'
).all();

// ✅ Use indexes for WHERE conditions
// Create index first: CREATE INDEX idx_users_email ON users(email)
const user = await env.DB.prepare('SELECT * FROM users WHERE email = ?')
  .bind(email)
  .first();

// ❌ Avoid functions in WHERE (can't use indexes)
// Bad: WHERE LOWER(email) = '[email protected]'
// Good: WHERE email = '[email protected]' (store email lowercase)

---

本地开发

本地数据库与远程数据库

# Create local database (automatic on first --local command)
npx wrangler d1 migrations apply my-database --local

# Query local database
npx wrangler d1 execute my-database --local --command "SELECT * FROM users"

# Query remote database
npx wrangler d1 execute my-database --remote --command "SELECT * FROM users"

本地数据库位置

本地 D1 数据库存储在：

.wrangler/state/v3/d1/miniflare-D1DatabaseObject/<database_id>.sqlite

为本地数据库填充种子数据

# Create seed file
cat > seed.sql << 'EOF'
INSERT INTO users (email, username, created_at) VALUES
  ('[email protected]', 'alice', 1698000000),
  ('[email protected]', 'bob', 1698000060);
EOF

# Apply seed
npx wrangler d1 execute my-database --local --file=seed.sql

---

Drizzle ORM（可选）

虽然 D1 使用原始 SQL 效果很好，但有些开发者更喜欢 ORM。Drizzle ORM 支持 D1：

npm install drizzle-orm
npm install -D drizzle-kit

注意：Drizzle 会增加复杂性，也需要额外学习一层。对于大多数 D1 用例，使用 wrangler 编写原始 SQL 更简单直接。只有在以下情况下，才考虑使用 Drizzle：

• 更喜欢使用 TypeScript 定义架构，而不是 SQL
• 希望查询支持自动补全
• 正在构建架构复杂的大型应用

Drizzle D1 官方文档：https://orm.drizzle.team/docs/get-started-sqlite#cloudflare-d1

---

最佳实践总结

✅ 始终要做：

1. 对用户输入使用预处理语句和 .bind()
2. 多个查询使用 .batch()（可降低延迟）
3. 为经常查询的列创建索引
4. 更改架构后运行 PRAGMA optimize
5. 在迁移中使用 IF NOT EXISTS，确保幂等性
6. 应用到生产环境前在本地测试迁移
7. 使用 try/catch 妥善处理错误
8. 对可选值使用 null，而不是 undefined
9. 绑定到查询之前验证输入
10. 执行 UPDATE/DELETE 后检查 meta.rows_written

❌ 绝不要做：

1. 绝不要在用户输入上使用 .exec()（有 SQL 注入风险）
2. 绝不要在公开代码仓库中硬编码 database_id
3. 绝不要在绑定参数中使用 undefined（会导致 D1_TYPE_ERROR）
4. 绝不要在循环中逐条执行查询（改用 batch）
5. 对可能返回大量结果的查询，绝不要忘记 LIMIT
6. 在生产环境中绝不要使用 SELECT *（应指定列）
7. 绝不要在迁移文件中包含 BEGIN TRANSACTION
8. 绝不要修改已应用的迁移（应创建新的迁移）
9. 绝不要跳过数据库操作的错误处理
10. 绝不要假设查询会成功（始终检查结果）

---

已避免的已知问题

问题	描述	避免方法
语句过长	大型 INSERT 语句超出 D1 限制	拆分为每批 100-250 行
事务冲突	迁移文件中包含 BEGIN TRANSACTION	移除 BEGIN/COMMIT（D1 会处理）
外键约束违规	架构变更破坏外键约束	使用 PRAGMA defer_foreign_keys = true
速率限制 / 队列过载	单独执行的查询过多	使用 batch()，不要使用循环
超出内存限制	查询将过多数据加载到内存中	添加 LIMIT、分页获取结果、拆分查询
类型不匹配错误	使用 undefined 而不是 null	可选值始终使用 null

---

Wrangler 命令参考

# Database management
wrangler d1 create <DATABASE_NAME>
wrangler d1 list
wrangler d1 delete <DATABASE_NAME>
wrangler d1 info <DATABASE_NAME>

# Migrations
wrangler d1 migrations create <DATABASE_NAME> <MIGRATION_NAME>
wrangler d1 migrations list <DATABASE_NAME> --local|--remote
wrangler d1 migrations apply <DATABASE_NAME> --local|--remote

# Execute queries
wrangler d1 execute <DATABASE_NAME> --local|--remote --command "SELECT * FROM users"
wrangler d1 execute <DATABASE_NAME> --local|--remote --file=./query.sql

# Time Travel (view historical data)
wrangler d1 time-travel info <DATABASE_NAME> --timestamp "2025-10-20"
wrangler d1 time-travel restore <DATABASE_NAME> --timestamp "2025-10-20"

---

官方文档

• D1 概览：https://developers.cloudflare.com/d1/
• 入门指南：https://developers.cloudflare.com/d1/get-started/
• 迁移：https://developers.cloudflare.com/d1/reference/migrations/
• Workers API：https://developers.cloudflare.com/d1/worker-api/
• 最佳实践：https://developers.cloudflare.com/d1/best-practices/
• Wrangler 命令：https://developers.cloudflare.com/workers/wrangler/commands/#d1

---

准备好使用 D1 开始构建了！ 🚀