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ChineseAmazon Aurora DSQL Skill
Amazon Aurora DSQL 技能
Aurora DSQL is a serverless, PostgreSQL-compatible distributed SQL database. This skill provides direct database interaction via MCP tools, schema management, migration support, and multi-tenant patterns.
Key capabilities:
- Direct query execution via MCP tools
- Schema management with DSQL constraints
- Migration support and safe schema evolution
- Multi-tenant isolation patterns
- IAM-based authentication
Aurora DSQL是一款无服务器、兼容PostgreSQL的分布式SQL数据库。本技能提供通过MCP工具直接与数据库交互、模式管理、迁移支持以及多租户模式等功能。
核心功能:
- 通过MCP工具直接执行查询
- 遵循DSQL约束的模式管理
- 迁移支持与安全的模式演进
- 多租户隔离模式
- 基于IAM的身份验证
Reference Files
参考文件
Load these files as needed for detailed guidance:
根据需要加载以下文件获取详细指导:
development-guide.md
development-guide.md
When: ALWAYS load before implementing schema changes or database operations
Contains: DDL rules, connection patterns, transaction limits, security best practices
适用场景: 在实施模式变更或数据库操作前必须加载
包含内容: DDL规则、连接模式、事务限制、安全最佳实践
MCP:
MCP相关:
mcp-setup.md
mcp-setup.md
When: Always load for guidance using or updating the DSQL MCP server
Contains: Instructions for setting up the DSQL MCP server with 2 configuration options as
sampled in .mcp.json
- Documentation-Tools Only
- Database Operations (requires a cluster endpoint)
适用场景: 使用或更新DSQL MCP服务器时必须加载
包含内容: 配置DSQL MCP服务器的两种选项说明,示例见.mcp.json
- 仅文档工具模式
- 数据库操作模式(需要集群端点)
mcp-tools.md
mcp-tools.md
When: Load when you need detailed MCP tool syntax and examples
Contains: Tool parameters, detailed examples, usage patterns
适用场景: 需要详细MCP工具语法和示例时加载
包含内容: 工具参数、详细示例、使用模式
language.md
language.md
When: MUST load when making language-specific implementation choices
Contains: Driver selection, framework patterns, connection code for Python/JS/Go/Java/Rust
适用场景: 进行语言相关实现选择时必须加载
包含内容: 驱动选择、框架模式、Python/JS/Go/Java/Rust的连接代码
dsql-examples.md
dsql-examples.md
When: Load when looking for specific implementation examples
Contains: Code examples, repository patterns, multi-tenant implementations
适用场景: 查找特定实现示例时加载
包含内容: 代码示例、仓库模式、多租户实现方案
troubleshooting.md
troubleshooting.md
When: Load when debugging errors or unexpected behavior
Contains: Common pitfalls, error messages, solutions
适用场景: 调试错误或异常行为时加载
包含内容: 常见问题、错误信息、解决方案
onboarding.md
onboarding.md
When: User explicitly requests to "Get started with DSQL" or similar phrase
Contains: Interactive step-by-step guide for new users
适用场景: 用户明确请求“开始使用DSQL”或类似表述时加载
包含内容: 面向新用户的交互式分步指南
ddl-migrations.md
ddl-migrations.md
When: MUST load when trying to perform DROP COLUMN, RENAME COLUMN, ALTER COLUMN TYPE, or DROP CONSTRAINT functionality
Contains: Table recreation patterns, batched migration for large tables, data validation
适用场景: 执行DROP COLUMN、RENAME COLUMN、ALTER COLUMN TYPE或DROP CONSTRAINT操作时必须加载
包含内容: 表重建模式、大表分批迁移方案、数据验证方法
MCP Tools Available
可用的MCP工具
The MCP server provides these tools:
aurora-dsqlDatabase Operations:
- readonly_query - Execute SELECT queries (returns list of dicts)
- transact - Execute DDL/DML statements in transaction (takes list of SQL statements)
- get_schema - Get table structure for a specific table
Documentation & Knowledge:
4. dsql_search_documentation - Search Aurora DSQL documentation
5. dsql_read_documentation - Read specific documentation pages
6. dsql_recommend - Get DSQL best practice recommendations
Note: There is no tool. Use with information_schema.
list_tablesreadonly_querySee mcp-setup.md for detailed setup instructions.
See mcp-tools.md for detailed usage and examples.
aurora-dsql数据库操作类:
- readonly_query - 执行SELECT查询(返回字典列表)
- transact - 在事务中执行DDL/DML语句(接收SQL语句列表)
- get_schema - 获取指定表的结构
文档与知识类:
4. dsql_search_documentation - 搜索Aurora DSQL文档
5. dsql_read_documentation - 读取特定文档页面
6. dsql_recommend - 获取DSQL最佳实践建议
注意: 没有工具,可使用查询information_schema获取表列表。
list_tablesreadonly_query查看mcp-setup.md获取详细配置说明。
查看mcp-tools.md获取详细用法和示例。
CLI Scripts Available
可用的CLI脚本
Bash scripts for cluster management and direct psql connections. All scripts are located in scripts/.
Cluster Management:
- create-cluster.sh - Create new DSQL cluster with optional tags
- delete-cluster.sh - Delete cluster with confirmation prompt
- list-clusters.sh - List all clusters in a region
- cluster-info.sh - Get detailed cluster information
Database Connection:
- psql-connect.sh - Connect to DSQL using psql with automatic IAM auth token generation
Quick example:
bash
./scripts/create-cluster.sh --region us-east-1
export CLUSTER=abc123def456
./scripts/psql-connect.shSee scripts/README.md for detailed usage.
用于集群管理和直接psql连接的Bash脚本,所有脚本位于scripts/目录。
集群管理:
- create-cluster.sh - 创建带有可选标签的新DSQL集群
- delete-cluster.sh - 删除集群(带确认提示)
- list-clusters.sh - 列出指定区域的所有集群
- cluster-info.sh - 获取集群详细信息
数据库连接:
- psql-connect.sh - 使用psql连接DSQL,自动生成IAM认证令牌
快速示例:
bash
./scripts/create-cluster.sh --region us-east-1
export CLUSTER=abc123def456
./scripts/psql-connect.sh查看scripts/README.md获取详细用法。
Quick Start
快速开始
1. List tables and explore schema
1. 列出表并探索模式
Use readonly_query with information_schema to list tables
Use get_schema to understand table structure使用readonly_query查询information_schema列出表
使用get_schema了解表结构2. Query data
2. 查询数据
Use readonly_query for SELECT queries
Always include tenant_id in WHERE clause for multi-tenant apps
Validate inputs carefully (no parameterized queries available)使用readonly_query执行SELECT查询
多租户应用中必须在WHERE子句中包含tenant_id
仔细验证输入(不支持参数化查询)3. Execute schema changes
3. 执行模式变更
Use transact tool with list of SQL statements
Follow one-DDL-per-transaction rule
Always use CREATE INDEX ASYNC in separate transaction使用transact工具执行SQL语句列表
遵循“每个事务仅一条DDL”规则
必须在单独事务中使用CREATE INDEX ASYNCCommon Workflows
常见工作流
Workflow 1: Create Multi-Tenant Schema
工作流1:创建多租户模式
Goal: Create a new table with proper tenant isolation
Steps:
- Create main table with tenant_id column using transact
- Create async index on tenant_id in separate transact call
- Create composite indexes for common query patterns (separate transact calls)
- Verify schema with get_schema
Critical rules:
- Include tenant_id in all tables
- Use CREATE INDEX ASYNC (never synchronous)
- Each DDL in its own transact call:
transact(["CREATE TABLE ..."]) - Store arrays/JSON as TEXT
目标: 创建带有正确租户隔离的新表
步骤:
- 使用transact创建包含tenant_id列的主表
- 在单独的transact调用中为tenant_id创建异步索引
- 为常见查询模式创建复合索引(单独transact调用)
- 使用get_schema验证模式
关键规则:
- 所有表必须包含tenant_id
- 使用CREATE INDEX ASYNC(禁止同步创建)
- 每条DDL单独放在transact调用中:
transact(["CREATE TABLE ..."]) - 数组/JSON以TEXT类型存储
Workflow 2: Safe Data Migration
工作流2:安全数据迁移
Goal: Add a new column with defaults safely
Steps:
- Add column using transact:
transact(["ALTER TABLE ... ADD COLUMN ..."]) - Populate existing rows with UPDATE in separate transact calls (batched under 3,000 rows)
- Verify migration with readonly_query using COUNT
- Create async index for new column using transact if needed
Critical rules:
- Add column first, populate later
- Never add DEFAULT in ALTER TABLE
- Batch updates under 3,000 rows in separate transact calls
- Each ALTER TABLE in its own transaction
目标: 安全添加带默认值的新列
步骤:
- 使用transact添加列:
transact(["ALTER TABLE ... ADD COLUMN ..."]) - 在单独的transact调用中分批更新现有行(每批不超过3000行)
- 使用readonly_query的COUNT验证迁移结果
- 如有需要,使用transact为新列创建异步索引
关键规则:
- 先添加列,再填充数据
- 禁止在ALTER TABLE中添加DEFAULT
- 分批更新每批不超过3000行,使用单独transact调用
- 每条ALTER TABLE单独放在一个事务中
Workflow 3: Application-Layer Referential Integrity
工作流3:应用层引用完整性
Goal: Safely insert/delete records with parent-child relationships
Steps for INSERT:
- Validate parent exists with readonly_query
- Throw error if parent not found
- Insert child record using transact with parent reference
Steps for DELETE:
- Check for dependent records with readonly_query (COUNT)
- Return error if dependents exist
- Delete record using transact if safe
目标: 安全插入/删除具有父子关系的记录
插入步骤:
- 使用readonly_query验证父记录存在
- 如父记录不存在则抛出错误
- 使用transact插入包含父引用的子记录
删除步骤:
- 使用readonly_query(COUNT)检查是否存在依赖记录
- 如存在依赖记录则返回错误
- 确认安全后使用transact删除记录
Workflow 4: Query with Tenant Isolation
工作流4:租户隔离查询
Goal: Retrieve data scoped to a specific tenant
Steps:
- Always include tenant_id in WHERE clause
- Validate and sanitize tenant_id input (no parameterized queries available!)
- Use readonly_query with validated tenant_id
- Never allow cross-tenant data access
Critical rules:
- Validate ALL inputs before building SQL (SQL injection risk!)
- ALL queries include WHERE tenant_id = 'validated-value'
- Reject cross-tenant access at application layer
- Use allowlists or regex validation for tenant IDs
目标: 检索特定租户范围内的数据
步骤:
- 必须在WHERE子句中包含tenant_id
- 验证并清洗tenant_id输入(不支持参数化查询!)
- 使用已验证的tenant_id调用readonly_query
- 禁止跨租户数据访问
关键规则:
- 构建SQL前必须验证所有输入(存在SQL注入风险!)
- 所有查询必须包含WHERE tenant_id = '已验证值'
- 在应用层拒绝跨租户访问
- 对租户ID使用白名单或正则验证
Workflow 5: Table Recreation DDL Migration
工作流5:表重建式DDL迁移
Goal: Perform DROP COLUMN, RENAME COLUMN, ALTER COLUMN TYPE, or DROP CONSTRAINT using the table recreation pattern.
MUST load ddl-migrations.md for detailed guidance.
Steps:
- MUST validate table exists and get row count with
readonly_query - MUST get current schema with
get_schema - MUST create new table with desired structure using
transact - MUST migrate data (batched in 500-1,000 row chunks for tables > 3,000 rows)
- MUST verify row counts match before proceeding
- MUST swap tables: drop original, rename new
- MUST recreate indexes using
CREATE INDEX ASYNC
Rules:
- MUST use batching for tables exceeding 3,000 rows
- PREFER batches of 500-1,000 rows for optimal throughput
- MUST validate data compatibility before type changes (abort if incompatible)
- MUST NOT drop original table until new table is verified
- MUST recreate all indexes after table swap using ASYNC
目标: 使用表重建模式执行DROP COLUMN、RENAME COLUMN、ALTER COLUMN TYPE或DROP CONSTRAINT操作。
必须加载ddl-migrations.md获取详细指导。
步骤:
- 必须使用验证表存在并获取行数
readonly_query - 必须使用获取当前模式
get_schema - 必须使用创建具有目标结构的新表
transact - 必须迁移数据(表行数>3000时,分批500-1000行)
- 必须在继续前验证行数匹配
- 必须交换表:删除原表,重命名新表
- 必须使用CREATE INDEX ASYNC重建所有索引
规则:
- 表行数超过3000时必须使用分批处理
- 优先选择500-1000行的批次以获得最佳吞吐量
- 类型变更前必须验证数据兼容性(不兼容则终止)
- 新表验证完成前禁止删除原表
- 表交换后必须使用ASYNC重建所有索引
Best Practices
最佳实践
- SHOULD read guidelines first - Check development_guide.md before making schema changes
- SHOULD use preferred language patterns - Check language.md
- SHOULD Execute queries directly - PREFER MCP tools for ad-hoc queries
- REQUIRED: Follow DDL Guidelines - Refer to DDL Rules
- SHALL repeatedly generate fresh tokens - Refer to Connection Limits
- ALWAYS use ASYNC indexes - is mandatory
CREATE INDEX ASYNC - MUST Serialize arrays/JSON as TEXT - Store arrays/JSON as TEXT (comma separated, JSON.stringify)
- ALWAYS Batch under 3,000 rows - maintain transaction limits
- REQUIRED: Use parameterized queries - Prevent SQL injection with $1, $2 placeholders
- MUST follow correct Application Layer Patterns - when multi-tenant isolation or application referential itegrity are required; refer to Application Layer Patterns
- REQUIRED use DELETE for truncation - DELETE is the only supported operation for truncation
- SHOULD test any migrations - Verify DDL on dev clusters before production
- Plan for Horizontal Scale - DSQL is designed to optimize for massive scales without latency drops; refer to Horizontal Scaling
- SHOULD use connection pooling in production applications - Refer to Connection Pooling
- SHOULD debug with the troubleshooting guide: - Always refer to the resources and guidelines in troubleshooting.md
- 应先阅读指南 - 进行模式变更前查看development_guide.md
- 应使用推荐语言模式 - 查看language.md
- 应直接执行查询 - 优先使用MCP工具执行临时查询
- 必须遵循DDL指南 - 参考DDL规则
- 必须定期生成新令牌 - 参考连接限制
- 必须使用异步索引 - 为强制要求
CREATE INDEX ASYNC - 必须将数组/JSON序列化为TEXT - 数组/JSON以TEXT类型存储(逗号分隔,JSON.stringify)
- 必须控制批次不超过3000行 - 遵守事务限制
- 必须使用参数化查询 - 使用$1、$2占位符防止SQL注入
- 必须遵循正确的应用层模式 - 当需要多租户隔离或应用层引用完整性时,参考应用层模式
- 必须使用DELETE进行截断 - DELETE是唯一支持的截断操作
- 应对所有迁移进行测试 - 在生产环境前先在开发集群验证DDL
- 规划水平扩展 - DSQL专为大规模扩展设计,可避免延迟上升;参考水平扩展
- 生产应用应使用连接池 - 参考连接池
- 应使用故障排除指南调试 - 始终参考troubleshooting.md中的资源和指南