3 个仓库
Tools for accessing and scanning datasets from remote repositories.
Distinguishing note: Focuses on remote URI-based data access rather than local file systems.
Explore 3 awesome GitHub repositories matching data & databases · Remote Data Loaders. Refine with filters or upvote what's useful.
Polars is a high-performance columnar data processing library designed for efficient analytical workflows. It functions as a structured data library that organizes information into typed columns, utilizing the Apache Arrow memory format to enable zero-copy data sharing and cache-friendly, vectorized operations. The engine is built to handle large-scale tabular datasets, providing both local and distributed analytical runtimes that scale from single-machine environments to multi-node clusters. The project distinguishes itself through a sophisticated lazy query engine that constructs abstract e
Loads and scans datasets directly from remote repositories using specialized URI paths.
Hydra is a cross-platform desktop application designed to serve as a centralized game library manager. It consolidates video games from multiple sources and platforms into a single, searchable interface, allowing users to organize their collections and manage installations through a unified dashboard. The application distinguishes itself through extensive support for interface personalization and data portability. Users can modify the visual appearance and notification sounds of the launcher by creating or installing community-shared themes. Furthermore, the tool includes integrated cloud syn
Parses external structured files to dynamically link game titles with remote installation assets.
Dask 是一个并行计算框架和分布式任务调度器,旨在将 Python 数据科学工作流从单机扩展到大型集群。它作为一个集群资源管理器,通过将任务及其依赖项表示为有向无环图来编排计算逻辑。这种架构允许系统在管理复杂执行要求的同时,自动将工作负载分配到可用硬件上。 该项目通过一个延迟评估引擎脱颖而出,该引擎将数据操作推迟到明确请求时才执行,从而实现全局图优化和高效的资源分配。它结合了内存感知数据溢出功能,以防止在处理超过可用内存的数据集时系统崩溃,并利用任务图融合将操作序列组合成单个执行步骤,从而最大限度地减少调度开销和节点间通信。 该平台为大规模数据分析提供了全面的功能面,包括对分布式机器学习、高性能计算集成和并行数据处理的支持。它提供了用于集群生命周期管理、性能分析和任务执行实时监控的广泛工具。用户可以在各种基础设施上部署这些环境,包括本地硬件、云提供商、容器化系统和高性能计算集群。
Accesses data from remote cloud or distributed file systems by specifying protocol-prefixed URLs.