spark-optimization
Optimize Apache Spark jobs with partitioning strategies, memory management, shuffle tuning, and data skew mitigation for high-performance data processing pipelines.
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177 skills found
Optimize Apache Spark jobs with partitioning strategies, memory management, shuffle tuning, and data skew mitigation for high-performance data processing pipelines.
Guide for implementing features using architecture-first design, TDD, rich domain models, and Swift 6.2 patterns, ensuring a clean separation between Domain, Infrastructure, and App layers.
Rust language server (rust-analyzer) providing code intelligence, real-time diagnostics, and refactoring support for .rs projects.
Build, optimize, and maintain production-ready backend systems using Node.js, Python, Go, and Rust. Includes API design, database management, security, and DevOps best practices.
High-performance in-memory DataFrame library for Python and Rust. Features lazy evaluation, parallel execution, and an Apache Arrow backend for efficient ETL, data processing, and faster pandas alternatives.
Expert assistant for designing and optimizing production-grade Trigger.dev background jobs, AI workflows, and resilient asynchronous task architectures in TypeScript.
Guidance on React Server Components (RSC) in Next.js, covering server/client component boundaries, data fetching, and composition patterns.
Private skill distribution system for managing agentics across devices and teams. Install, sync, add, and update your agents, skills, and prompts via a central library catalog.
Implement Schema.org structured data to enhance SERP visibility, improve rich result eligibility, and validate content metadata.
Design modular TypeScript libraries using HexDI principles: compile-time dependency validation, feature-first organization, and clean API boundaries.
Statistical visualization library for Python. Create publication-quality graphics like box plots, heatmaps, and violin plots with pandas integration and automatic statistical estimation.
Structured, template-driven workflow for end-to-end feature development including coding, automated testing, verification, and session-based improvement.