'mysql' 검색 결과

SQL database migrations with zero-downtime strategies for PostgreSQL, MySQL, SQL Server

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onboarding workflow for creating datasets and applications in Viking AI Search. Supports one-time import from local files (JSON, JSONL, CSV) and MySQL databases, plus scheduled incremental sync for append-only JSONL files and MySQL. All sources are first exported to a bootstrap JSONL file; backend-driven schema inference handles detection, and optional background sync keeps the dataset up to date as new data arrives.

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Expert knowledge for Azure Database for PostgreSQL development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using Flexible Server, pgvector/Apache AGE, Private Link/TLS, replicas/PITR, or Azure AI/ML integrations, and other Azure Database for PostgreSQL related development tasks. Not for Azure SQL Database (use azure-sql-database), Azure SQL Managed Instance (use azure-sql-managed-instance), SQL Server on Azure Virtual Machines (use azure-sql-virtual-machines), Azure Database for MySQL (use azure-database-mysql).

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You are an expert in Drizzle ORM, the lightweight TypeScript ORM that maps directly to SQL. You help developers write type-safe database queries that look like SQL (not a new query language), generate migrations from schema changes, and deploy to serverless environments with zero overhead — supporting Postgres, MySQL, SQLite, Turso, Neon, PlanetScale, and Cloudflare D1.

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Multi-backend database security auditor. Audits Supabase, Firebase (Firestore/RTDB/Storage/Functions/Remote Config), MongoDB (self-hosted + Atlas), self-hosted PostgreSQL, and self-hosted MySQL for RLS/rules misconfigurations, exposed credentials, auth bypasses, MongoBleed (CVE-2025-14847), pgBouncer CVE-2025-12819, mysql_native_password drift, ghost auth, and storage exposures. Use this skill whenever the user mentions database security, RLS or rule audits, security review, penetration testing a vibe-coded app, checking if their DB is exposed, hardening a backend, fixing security rules, or auditing apps built with Lovable/Bolt/Replit/Cursor/Claude Code on any of these backends. Trigger on phrases like 'is my app secure', 'check my database', 'audit my Firebase', 'audit my MongoDB', 'audit my Postgres', 'audit my Supabase', 'is my DB exposed', or any cross-backend variant ('audit my full stack').

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Use when the user wants to run SQL - especially analytical SQL - on local files (parquet/csv/json), URLs, S3 paths, or remote databases (Postgres, MySQL, MongoDB, ClickHouse Cloud, Iceberg, Delta Lake) without setting up a server. Provides chDB - embedded ClickHouse SQL in Python with 1000+ functions, Session for stateful multi-step pipelines, parametrized queries, and cross-source joins via `s3()`, `mysql()`, `postgresql()`, `iceberg()`, `deltaLake()`, `remoteSecure()` table functions. TRIGGER when: user wants SQL on parquet/csv/files or across remote analytical sources; uses ClickHouse SQL features (window functions, windowFunnel, geoToH3, JSON path ops, Session, parametrized queries); imports `chdb` or calls `chdb.query()`. SKIP this skill for pandas-style DataFrame method-chaining (use chdb-datastore instead) or ClickHouse server administration.

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Expert en bases de données (PostgreSQL, MySQL, MongoDB, Redis, query optimization, replication)

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阿里云 AnalyticDB (ADB) for MySQL 只读数据分析。 多维分析（计数/聚合/时间序列）、交叉验证、Schema 文档生成、多 Profile。

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Guides for configuring Prisma with different database providers (PostgreSQL, MySQL, SQLite, MongoDB, etc.). Use when setting up a new project, changing databases, or troubleshooting connection issues. Triggers on "configure postgres", "connect to mysql", "setup mongodb", "sqlite setup".

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PostgreSQL、MySQL、および一般的なORM（Prisma、Drizzle、Kysely、Django、TypeORM、golang-migrate）にわたるスキーマ変更、データマイグレーション、ロールバック、ゼロダウンタイムデプロイメントのためのデータベースマイグレーションベストプラクティス。

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Specialized skill for containerized database testing using Testcontainers. Use when testing real database behavior, using SQL Server/PostgreSQL/MySQL containers, testing EF Core/Dapper. Covers container startup, database migrations, test isolation, container sharing. Keywords: testcontainers, container testing, database testing, MsSqlContainer, PostgreSqlContainer, MySqlContainer, EF Core testing, Dapper testing, Testcontainers.MsSql, Testcontainers.PostgreSql, GetConnectionString, IAsyncLifetime, CollectionFixture

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벵골어 검색과 AI 처리를 위한 문자 표현 통일, 단어 분리, 숫자 변환, 결합 문자를 보존하는 표시 방법을 정리합니다. 학습 데이터 정비와 텍스트 저장에도 활용할 수 있습니다.

• 벵골어 검색과 입력 기능을 구현합니다
• 벵골어 학습 데이터를 정리합니다
• 벵골어와 영어 대화를 지원합니다

운영 데이터베이스의 구조 변경과 기존 데이터 이전을 계획합니다. 열과 인덱스 추가, 단계적 전환, 복구 절차를 정리하고 중단 시간과 잠금을 고려한 변경을 돕습니다.

• 운영 테이블에 열이나 인덱스 추가
• 대량 데이터의 분할 갱신
• 앱을 중단하지 않고 열 교체

Helps design ClickHouse tables, write analytical queries, and improve slow queries. Covers loading data in batches, preparing reusable summaries, and monitoring performance for large datasets, real-time dashboards, and time-series analysis.

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• Designing tables for large-scale analytics
• Improving slow aggregation queries
• Loading large datasets in batches

Build Python APIs with FastAPI using clear routes, validated inputs, and consistent error handling. It guides asynchronous database and API calls, reusable dependencies, caching, and code organization to support readable implementations and responsive services.

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• Designing API routes and input validation
• Reviewing asynchronous database and API calls
• Organizing error handling and logging

Investigate database slowdowns and plan measurable improvements to queries, indexes, caching, and scaling. The skill covers SQL and NoSQL systems, with guidance on monitoring, load testing, migrations, and balancing performance against cost.

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• Analyze slow SQL queries and execution plans
• Resolve repeated database calls in APIs
• Plan indexes and caching for high traffic

Design a database layer from business requirements, access patterns, and expected growth. Compare database technologies, define tables and relationships, and plan indexes, caching, scaling, migrations, backups, and recovery with clear reasons and trade-offs.

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• Choosing a database for a new service
• Designing tables, relationships, and indexes
• Planning database migrations and rollback procedures

Turn a plain-language data request into SQL tailored to your database. Build queries that combine tables, filter records, and calculate summaries, with explanations of each step, performance considerations, and suggestions for adjusting dates or other conditions.

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• Create SQL for order counts by status
• Analyze retention by signup month
• Query large tables with date-based partitions

Verify OpenWork changes by running the real product and following user or client actions. Choose suitable tests, capture screenshots and reports, and demonstrate that the check fails on dev but passes on the changed branch.

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• Verifying real product behavior before opening a PR
• Preparing screenshots and test evidence for a reviewer
• Checking a fix against dev and the changed branch

Set up and troubleshoot Daytona sandbox environments, which provide isolated spaces for running applications. The skill covers CLI authentication, persistent desktop and server sandboxes, diagnostic logs, shared secrets storage, snapshot refreshes, and environment deletion.

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• Troubleshooting Daytona authentication and organization selection
• Keeping an Electron or server sandbox available for debugging
• Preparing shared secrets storage for sandboxes

Manage OpenWork feature releases with feature flags, switches that control access to new behavior. Register features before coding, release them by organization and deployment, prepare a global shutdown option, and remove temporary flags after rollout.

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• Registering a feature before implementation
• Releasing a feature to selected organizations
• Separating cloud and self-hosted availability

Run Openwork end-to-end tests, which verify complete user journeys, locally or on Daytona. Check the exact commit and runtime, investigate failures or skipped tests, and report results with commands, counts, and an explicit overall verdict.

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• Running a single end-to-end test
• Verifying the exact commit intended for a PR
• Investigating skipped tests and missing prerequisites

Set up the iPolloWork server in Daytona, connect an Electron desktop client through public preview URLs, and check service health and logs. Supports cloud feature validation with separate server and desktop test environments.

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• Start a Daytona server test environment
• Connect Electron to cloud services
• Validate marketplace and organization policy flows

Set up an iPolloWork development environment in a Daytona cloud sandbox and access the real Electron app through a browser. Follow procedures for connection URLs, logs, restarts, code updates, and common startup problems.

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• Launch a cloud development environment for iPolloWork
• Operate the Electron app through a browser
• Check logs and troubleshoot startup problems