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7 repositorios

Awesome GitHub RepositoriesData Layout Optimizers

Systems that arrange table data during write operations using specific sort orders to improve search efficiency.

Distinct from Query Optimizations: Distinct from general query optimizations: focuses on physical data layout and sorting during write operations.

Explore 7 awesome GitHub repositories matching data & databases · Data Layout Optimizers. Refine with filters or upvote what's useful.

Awesome Data Layout Optimizers GitHub Repositories

Encuentra los mejores repositorios con IA.Buscaremos los repositorios que mejor coincidan usando IA.
  • prestodb/prestoAvatar de prestodb

    prestodb/presto

    16,711Ver en GitHub↗

    Presto is a distributed SQL query engine designed for high-performance analytical processing across heterogeneous data sources. It functions as a data federation platform and massively parallel processing engine, allowing users to execute interactive queries against diverse storage systems without requiring data migration. By mapping remote metadata and structures to a unified relational namespace, it enables seamless cross-platform analysis through a standard SQL interface. The engine distinguishes itself through a pluggable connector architecture and a shared-nothing distributed processing

    Arranges table data during write operations using specific sort orders to make filtering and searching more efficient.

    Javabig-datadatahadoop
    Ver en GitHub↗16,711
  • fastai/numerical-linear-algebraAvatar de fastai

    fastai/numerical-linear-algebra

    10,703Ver en GitHub↗

    This project is a comprehensive library for numerical linear algebra and scientific computing, designed to provide optimized routines for matrix decomposition, statistical modeling, and high-performance data analysis. It serves as both a toolkit for solving complex linear systems and an educational resource for understanding the fundamental algorithms behind matrix factorizations and numerical solvers. The library distinguishes itself through a focus on randomized numerical linear algebra, utilizing probabilistic algorithms and approximate methods to perform dimensionality reduction and matri

    Structures computations to minimize data movement between memory hierarchies for quicker retrieval.

    Jupyter Notebookalgorithmsdata-sciencedeep-learning
    Ver en GitHub↗10,703
  • boto/boto3Avatar de boto

    boto/boto3

    9,834Ver en GitHub↗

    Boto3 is the AWS SDK for Python, providing a programmatic interface for managing and automating AWS cloud infrastructure and services. It serves as a cloud management API client and resource manager for provisioning, configuring, and scaling virtual servers, databases, and storage. The library enables the implementation of infrastructure-as-code through declarative templates and scripts, allowing for the deployment of identical resource stacks across multiple accounts and geographic regions. It also provides a framework for coordinating distributed workflows, serverless functions, and contain

    Organizes transferred data into partitions to optimize search efficiency and query performance.

    Pythonawsaws-sdkcloud
    Ver en GitHub↗9,834
  • odin-lang/odinAvatar de odin-lang

    odin-lang/Odin

    9,806Ver en GitHub↗

    Odin is a compiled, statically typed systems programming language designed for high-performance software development. It focuses on pragmatic low-level memory control, providing a toolset for manual memory management and precise control over hardware utilization. The language is distinguished by its flexible memory model, which includes custom allocators and precise data layout capabilities to optimize resource usage. It features a comprehensive foreign function interface for importing assembly files and linking with external libraries using configurable calling conventions. The type system

    Supports organizing records as arrays of structures or structures of arrays to maximize hardware acceleration.

    Odincompilerlanguageodin
    Ver en GitHub↗9,806
  • delta-io/deltaAvatar de delta-io

    delta-io/delta

    8,596Ver en GitHub↗

    Delta is a lakehouse table format that brings ACID transactions and data warehouse consistency to large scale data lakes on cloud object storage. It serves as an ACID transaction manager, coordinating atomic commits and serializable isolation for concurrent reads and writes across distributed compute engines. The project provides a multi-engine interoperability layer that uses format translation to allow diverse SQL engines and processing frameworks to read and write the same tables. It functions as a data versioning system, utilizing a transaction log to enable time travel, historical snapsh

    Applies advanced sorting and data skipping techniques to reduce the volume of scanned data.

    Scalaacidanalyticsbig-data
    Ver en GitHub↗8,596
  • alex313031/thoriumAvatar de Alex313031

    Alex313031/thorium

    6,803Ver en GitHub↗

    Thorium is a web browser built from the Chromium project, designed for high performance and expanded compatibility. It utilizes aggressive compiler optimizations and CPU-specific instruction sets, such as AVX2 and SIMD, to increase page rendering and JavaScript execution speeds. The project distinguishes itself by providing custom builds that enable modern web browsing on legacy versions of Windows and Linux. It further diverges from standard browser implementations by integrating Widevine DRM and native support for high-efficiency media formats, including HEVC and JPEG XL. Broad capabilitie

    Implements strategies to reduce execution overhead by enhancing data locality within software loops.

    C++aesavxavx-instructions
    Ver en GitHub↗6,803
  • kvcache-ai/mooncakeAvatar de kvcache-ai

    kvcache-ai/Mooncake

    5,594Ver en GitHub↗

    Mooncake es una plataforma de servicio de modelos de lenguaje grandes (LLM) desagregados y un almacén distribuido de clave-valor diseñado para infraestructura de inferencia de alto rendimiento. Funciona como un orquestador de memoria GPU y un sistema de gestión de caché KV que agrupa y transfiere cachés de clave-valor a través de clústeres para acelerar la inferencia. El sistema se distingue por separar las fases de prellenado (prefill) y decodificación (decode) de la inferencia en clústeres de hardware distintos para optimizar la utilización de recursos. Utiliza una caché distribuida RDMA de alto rendimiento con transferencias de copia cero para mover datos entre nodos de cómputo, evitando la CPU para reducir la latencia y la sobrecarga. La plataforma cubre áreas de capacidad amplias, incluyendo agrupación de memoria distribuida, enrutamiento de memoria de aceleradores mediante CXL y descarga de almacenamiento multinivel a SSDs. Gestiona el estado del clúster a través de servicios de coordinación de metadatos e implementa gobernanza de recursos mediante protección de objetos basada en arrendamiento y desalojo de caché basado en marcas de agua. El software está empaquetado para despliegue en contenedores con soporte para redes de host y mapeo de dispositivos de hardware.

    Assigns preferred storage segments for object allocation to minimize network overhead and increase speed.

    C++
    Ver en GitHub↗5,594
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  2. Data & Databases
  3. Query Optimizations
  4. Data Layout Optimizers

Explorar subetiquetas

  • Data Locality OptimizersStrategies for structuring computations to minimize data movement between memory hierarchies. **Distinct from Data Layout Optimizers:** Distinct from query layout: focuses on cache-aware memory access for numerical algorithms.