3 个仓库
Techniques for reducing memory footprint by mapping repeated values to numeric identifiers.
Distinguishing note: Focuses on memory-efficient storage representations rather than general data compression.
Explore 3 awesome GitHub repositories matching data & databases · Data Encoding Optimizations. 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
Optimizes memory usage by representing repeated string data as numeric placeholders.
node-qrcode is a JavaScript library and command-line tool for generating scannable QR codes from text or binary data. It functions as both a generator library for Node.js and web browser environments and a standalone command-line interface. The project supports producing QR codes in multiple formats, including raster images and scalable vector graphics. It can also render barcodes as text representations directly within a terminal for rapid visual verification. The generator includes capabilities for configuring error correction levels and optimizing data density through various encoding mod
Reduces QR code size by automatically selecting the most efficient encoding modes for different text segments.
Velox 是一个高性能 C++ 查询执行引擎和列式数据处理库。它作为一个用于实现分析型查询引擎的可组合框架,提供了向量化表达式评估器和数据管理系统工具包。 该项目以使用向量化列式执行和基于 Arena 的内存分配来处理大规模数据集而著称。它具有专门的优化功能,如广播连接表缓存、动态过滤器下推和字典编码,以减少内存开销并加速分析读取。 该引擎涵盖了广泛的分析能力,包括实现哈希连接、合并连接和半连接,以及多阶段并行聚合和窗口函数计算。它提供了用于列式内存存储、Parquet 数据解码以及与云存储集成的原语。 通过用于自定义标量和聚合函数的函数注册系统提供可扩展性,并提供高级绑定以将 C++ 逻辑连接到 Python。
Reduces memory footprint for duplicate values by mapping indices to a base vector without data copying.