'postgresql' 검색 결과

Develop time-series and event-data solutions with TimescaleDB, an extension for PostgreSQL. The skill provides organized references for installation, time-based tables, ongoing aggregate calculations, compression, and performance troubleshooting.

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• Learn how to install and use TimescaleDB
• Design tables for time-series and event data
• Implement time-bucket and continuous aggregates

Improve PostgreSQL queries and database design by examining execution plans and choosing indexes for actual access patterns. Get guidance on large tables, JSONB data, connection pooling, and maintenance while accounting for write overhead and memory use.

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• Investigating slow queries with execution plans
• Choosing indexes for search patterns
• Designing partitions for time-series data

Analyze and tune PostgreSQL databases using query execution plans, which show how queries run. This skill guides index design, JSONB searches, replication setup, maintenance, and monitoring, with checks to compare behavior before and after changes.

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• Investigate slow queries with EXPLAIN
• Design indexes for JSONB searches
• Configure replication and monitor lag

Investigate slow PostgreSQL and MySQL queries using execution plans, which show how the database runs a query. Develop index, SQL, and configuration changes, then compare measurements before and after each change to validate the results.

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• Investigating slow SQL queries
• Reviewing database index design
• Tuning memory and database configuration

Amazon Aurora PostgreSQL — creates, modifies, and advises on Aurora PostgreSQL clusters specifically (PostgreSQL-compatible engine, Aurora serverless, express configuration, pgvector, Babelfish). Trigger for Aurora PostgreSQL cluster operations, express-configuration quick-start, ACU sizing, I/O-Optimized storage, commitment pricing, or PostgreSQL upgrade planning. For Aurora MySQL, use amazon-aurora-mysql instead. Contains safety guardrails, express-first routing, and response templates that override defaults.

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Use this skill for general PostgreSQL table design. **Trigger when user asks to:** - Design PostgreSQL tables, schemas, or data models when creating new tables and when modifying existing ones. - Choose data types, constraints, or indexes for PostgreSQL - Create user tables, order tables, reference tables, or JSONB schemas - Understand PostgreSQL best practices for normalization, constraints, or indexing - Design update-heavy, upsert-heavy, or OLTP-style tables **Keywords:** PostgreSQL schema, table design, data types, PRIMARY KEY, FOREIGN KEY, indexes, B-tree, GIN, JSONB, constraints, normalization, identity columns, partitioning, row-level security Comprehensive reference covering data types, indexing strategies, constraints, JSONB patterns, partitioning, and PostgreSQL-specific best practices.

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Set up reproducible development environments with Flox on macOS and Linux. Define tools, package versions, setup steps, and local services in one configuration, then share it with teammates or add project-specific tools for AI agents.

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• Sharing a consistent development setup across a team
• Combining language tools and system dependencies
• Running local PostgreSQL and Redis services

운영 데이터베이스의 열, 인덱스와 데이터 변경을 설계합니다. 대규모 테이블의 분할 갱신, 단계적 구조 전환과 복구 계획을 포함해 마이그레이션 절차를 정리합니다.

• 대규모 테이블에 열과 인덱스 추가
• 중단을 피하는 단계적 열 이름 변경
• 기존 데이터의 분할 보완

Provision and manage Amazon RDS relational databases on AWS. Follow guidance for backups, recovery, security, monitoring, multi-zone redundancy, and read replicas—database copies that handle read traffic—with AWS CLI commands and a Terraform configuration example.

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• Deploy a managed PostgreSQL or MySQL database
• Configure multi-zone redundancy and read replicas
• Set up backups and restore to a specific point in time

Helps you start an Open SaaS project by checking Wasp installation and guiding setup for your operating system. Using the Getting Started guide, it assists with database startup, database migrations, and running the development server.

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• Checking whether Wasp is installed and viewing its version
• Installing Wasp for the current operating system
• Starting PostgreSQL and applying database migrations

Connect to Azure Database for PostgreSQL Flexible Server from Node.js/TypeScript using the pg (node-postgres) package. Use for PostgreSQL queries, connection pooling, transactions, and Microsoft Entra ID (passwordless) authentication. Triggers: "PostgreSQL", "postgres", "pg client", "node-postgres", "Azure PostgreSQL connection", "PostgreSQL TypeScript", "pg Pool", "passwordless postgres".

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PostgreSQL-specific development assistant focusing on unique PostgreSQL features, advanced data types, and PostgreSQL-exclusive capabilities. Covers JSONB operations, array types, custom types, range/geometric types, full-text search, window functions, and PostgreSQL extensions ecosystem.

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PostgreSQL-specific code review assistant focusing on PostgreSQL best practices, anti-patterns, and unique quality standards. Covers JSONB operations, array usage, custom types, schema design, function optimization, and PostgreSQL-exclusive security features like Row Level Security (RLS). Use when reviewing SQL, schema, or functions written for PostgreSQL.

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Quality gates determinísticos para PostgreSQL. Use quando o usuário pedir "quality gate PostgreSQL", "quality gate Postgres", migrations ou schema drift PostgreSQL, constraints ou índices PostgreSQL, EXPLAIN, plano de consulta ou baseline para PostgreSQL.

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PostgreSQL-specific development assistant focusing on unique PostgreSQL features, advanced data types, and PostgreSQL-exclusive capabilities. Covers JSONB operations, array types, custom types, range/geometric types, full-text search, window functions, and PostgreSQL extensions ecosystem.

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Assess database security within an authorized scope by reviewing network exposure, authentication, access permissions, risky features, audit logs, and backup access. Distinguish configuration weaknesses from issues that can be demonstrated through safe validation.

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• Reviewing database exposure and TLS settings
• Checking account privileges and sensitive table access
• Assessing dangerous features and configuration weaknesses

Investigate slow SQL using execution plans, which show how a database processes a query. Review indexes, filters, joins, and maintenance practices through PostgreSQL examples to identify bottlenecks and plan changes to queries or database structure.

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• Investigating slow SQL queries
• Reviewing index choices and column order
• Reading EXPLAIN execution plans

Create a Spring Boot Java project skeleton with Maven, database connection settings, and Docker Compose services. Adds dependencies for API documentation and architecture tests, then checks the generated project with a Maven test command.

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• Start a Java 21 Spring Boot project
• Prepare local PostgreSQL, Redis, and MongoDB services
• Add API documentation and architecture test dependencies

Helps design ClickHouse tables, write analytical queries, and build data ingestion workflows. Covers batch inserts, precomputed summaries, and performance monitoring for teams working with large datasets and time-based activity analysis.

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• Designing tables for large analytical datasets
• Improving slow aggregation queries
• Analyzing user retention and conversion steps

Use this skill for any PostgreSQL database work — table design, indexing, data types, constraints, extensions (pgvector, PostGIS, TimescaleDB), search, and migrations. **Trigger when user asks to:** - Explore an existing PostgreSQL database to understand its objects and relationships - Design or modify PostgreSQL tables, schemas, or data models - Choose data types, constraints, indexes, or partitioning strategies - Work with pgvector embeddings, semantic search, or RAG - Set up full-text search, hybrid search, or BM25 ranking - Use PostGIS for spatial/geographic data - Set up TimescaleDB hypertables for time-series data - Migrate tables to hypertables or evaluate migration candidates - Plan or execute safe schema migrations with zero downtime **Keywords:** PostgreSQL, Postgres, SQL, schema, table design, indexes, constraints, pgvector, PostGIS, TimescaleDB, hypertable, semantic search, hybrid search, BM25, time-series, migration

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[Deprecated] Optional advanced tool for complex data modeling. For simple MySQL table creation, use relational-database-tool directly; for PostgreSQL / CloudBase PG schema work, use postgresql-development. New environments should use PostgreSQL DDL via queryPgDatabase/managePgDatabase — see postgresql-development skill instead.

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使用火山引擎 RDS PostgreSQL，帮助用户完成 RDS PostgreSQL 相关的实例管理、数据库操作、账号管理和运维任务，可直接调用 uv run ./scripts/call_rds_postgresql.py 脚本获取实时结果。

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PostgreSQL-specific code review assistant focusing on PostgreSQL best practices, anti-patterns, and unique quality standards. Covers JSONB operations, array usage, custom types, schema design, function optimization, and PostgreSQL-exclusive security features like Row Level Security (RLS).

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使用 AACT (Aggregate Analysis of ClinicalTrials.gov) PostgreSQL 数据仓库进行批量、历史、聚合性临床试验数据挖掘。Use this skill when the user requests bulk SQL analysis over the full clinical trials data warehouse — historical trial trends, disease landscapes, similar-design matching, or multi-year aggregations across hundreds of thousands of NCT records. 触发场景包括：AACT 查询、临床试验批量分析、PostgreSQL 试验数据、全量 NCT 检索、试验数据挖掘、历史试验分析、clinical trials data warehouse、SQL trials、bulk trial analysis、disease landscape、试验设计相似性匹配、跨年度聚合、sponsor/phase/country 多维统计。**与 clinical-trials-v2 差异**：本 skill 走批量 SQL · 离线大数据（PostgreSQL）；v2 走实时 API · 单查询。两者互补：单条 NCT 实时状态用 v2，百万级历史挖掘用本 skill。支持云端公共 PostgreSQL（aact-db.ctti-clinicaltrials.org · 零部署）和每日 dump 本地还原（高性能 · 离线）两种连接方式，自动检测优先用本地。跨平台（macOS/Linux/Windows）参数化 SQL 防注入，read-only 强制保护。

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