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spanner-basics

Plan and manage Cloud Spanner databases on Google Cloud, design tables and primary keys, write SQL and client code, and investigate slow queries using database statistics to identify resource-intensive operations.

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원문원문 설명 보기

Assists in provisioning instances and databases, designing performant schemas, and querying data in Cloud Spanner on Google Cloud. Use when designing primary keys, writing SQL queries or client library code, or diagnosing performance issues.

설치 방법 보기

이럴 때 유용합니다

  • Create Cloud Spanner instances and databases
  • Design primary keys and related tables
  • Write SQL queries and client library code
  • Investigate slow or CPU-intensive queries

포함된 파일(10)

  • SKILL.md3.4 KB
  • references/cli-usage.md1.3 KB
  • references/client-library-usage.md3.5 KB
  • references/core-concepts.md1.1 KB
  • references/iam-security.md1.2 KB
  • references/mcp-usage.md1.5 KB
  • references/postgresql-dialect.md951 B
  • references/queues-usage.md10.8 KB
  • references/schema-design.md3.4 KB
  • references/terraform-usage.md928 B

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Spanner Basics

This skill provides core workflows and guidance for administering and developing with Cloud Spanner on Google Cloud, a fully managed, mission-critical database service offering global transactional consistency and automatic, synchronous replication for high availability.

Core Principles

  • Performance First: Spanner scales horizontally. Efficiency is tied to Primary Key design. Always warn against using monotonically increasing/decreasing values (like sequential timestamps) as the first part of a primary key to avoid hotspots.
  • Schema Design: Prefer interleaved tables for strongly related parent-child data that is frequently accessed together.

Safety

[!CAUTION] CRITICAL INSTRUCTION: You MUST obtain explicit user confirmation before making any non-emulator database changes (DML or DDL) or destructive operations (such as dropping tables, indexes, or any other Spanner resources). Do not execute them automatically; instead, output the command (e.g., gcloud spanner databases ddl update) and ask for explicit user approval. When database access is unavailable or authentication fails, do not block on trying to verify the existence of the instance, database, or table. Assume the provided resources exist and directly generate the DDL commands.

Common Workflows

Schema Evolution & DDL

  1. Use gcloud spanner databases ddl update to apply schema updates (such as CREATE, ALTER, or DROP tables and indexes).
  2. Reference schema-design.md for guidelines on primary key selection and interleaved tables.

Diagnosing Performance Issues

  1. Use SPANNER_SYS tables to identify slow or resource-intensive queries.
  2. For example, query SPANNER_SYS.QUERY_STATS_TOP_HOUR to find queries with the highest CPU usage.

Reference Directory

  • Core Concepts: Explanation of Spanner internals, architecture, and design.
  • CLI Usage: Essential gcloud spanner command-line operations for managing instances and databases.
  • IAM Security: Roles, permissions, and data governance best practices for Spanner.
  • Client Library Usage: Using Google Cloud client libraries for Spanner (Java, Go, Python, Node.js).
  • Terraform Usage: Infrastructure as Code examples for provisioning Spanner instances and databases.
  • MCP Usage: Using the Spanner remote MCP server.
  • PostgreSQL Dialect: Best practices and examples for using the PostgreSQL interface in Spanner.
  • Queues Usage: Cloud Spanner Queues: mental model, design constraints, and links related to transactional message queues.
  • Schema Design: Guidelines on primary key selection and interleaved tables for performance.

If you need product information that's not found in these references, use the search_documents tool of the Developer Knowledge MCP server.

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