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Awesome GitHub RepositoriesApache Arrow-Based Formats

Storage standards specifically leveraging the Apache Arrow memory layout for disk persistence.

Distinct from Columnar Formats: More specific than general columnar formats, focusing on the Arrow-based interoperability standard.

Explore 2 awesome GitHub repositories matching data & databases · Apache Arrow-Based Formats. Refine with filters or upvote what's useful.

Awesome Apache Arrow-Based Formats GitHub Repositories

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  • lance-format/lanceL

    lance-format/lance

    6,699在 GitHub 上查看↗

    Lance is a columnar data format and storage layer designed for high-performance random access and the persistence of multimodal data. It functions as a vector database storage system, a multimodal data store, and a versioned dataset manager. The project distinguishes itself as a hybrid search engine that combines vector similarity search and full-text indexing on a single dataset. It provides unified storage for diverse data types including images, audio, and video, utilizing a system that lazy-loads large binary objects only when requested. The system manages dataset evolution through schem

    Provides a storage standard based on Apache Arrow for high-performance random access.

    Rust
    在 GitHub 上查看↗6,699
  • awslabs/gluontsawslabs 的头像

    awslabs/gluonts

    5,199在 GitHub 上查看↗

    GluonTS 是一个概率时间序列库和深度学习预测框架。它提供了一套工具包,用于构建、训练和评估神经网络架构,通过将未来值预测为概率分布来量化不确定性。 该项目的独特之处在于支持零样本(zero-shot)预测,并集成了多种建模方法,包括深度概率神经网络以及对 Prophet 和 R forecast 等外部统计库的封装。它实现了因果卷积和可逆残差网络等专门的架构原语,以防止信息泄露并将潜在表示映射为有效的概率分布。 该框架涵盖了全面的数据工程功能,包括时间序列缩放、双射变换和分层建模。它利用 Apache Arrow 和 Parquet 进行高性能数据集流式传输和随机访问管理。在模型评估方面,它包含一套评估套件,使用分位数损失(quantile loss)和连续排名概率分数(CRPS)等指标来衡量预测准确性和概率覆盖率。 该库支持通过集成 Amazon SageMaker 进行模型部署。

    Converts encoded Apache Arrow data batches into time series formats using predefined schemas.

    Pythonartificial-intelligenceawsdata-science
    在 GitHub 上查看↗5,199
  1. Home
  2. Data & Databases
  3. In-Memory Data Stores
  4. Columnar Formats
  5. Apache Arrow-Based Formats

探索子标签

  • Dataset DecodingConverting encoded columnar data batches into structured object formats based on a specific schema. **Distinct from Apache Arrow-Based Formats:** Focuses on the decoding process from Arrow memory layout to model-ready formats, not just the storage standard.