SeaweedFS 是一个用于对象存储(S3)、文件系统和 Iceberg 表的分布式存储系统,旨在以 O(1) 磁盘访问和轻松的横向扩展处理数十亿个文件。
hadoop-hdfs 开源项目推荐(362 个)
hadoop-hdfs 话题在 GitHub 上没有填写简介,这里按 Star 数汇总最相关的热门仓库。
热门项目 前 20
按 Star 数排序展示前 20 个 · GitHub 共 362 个仓库超过2000个数据工程师面试问题。
MorphL Community Edition uses big data and machine learning to predict user behaviors in digital products and services with the end goal of increasing KPIs (click-through rates, conversion rates, etc.) through personalization
A tool for scale and performance testing of HDFS with a specific focus on the NameNode.
使用 Hadoop HDFS 和 Kafka 的数据工程项目
大数据必备:Hadoop、MapReduce、Spark。探索Jupyter笔记本中的教程和演示——大多数都是独立且实时的,随时可点击运行。
Learn how to use Spark SQL and HSpark connector package to create / query data tables that reside in HBase region servers
Simplified ETL process in Hadoop using Apache Spark. Has complete ETL pipeline for datalake. SparkSession extensions, DataFrame validation, Column extensions, SQL functions, and DataFrame transformations
Big data projects implemented by Maniram yadav
旅游网站(携程网部分数据)大数据分析-hadoop课程设计(本科课设级别)
By Smart Shaped s.r.l. (https://www.smartshaped.com/)
HokStack - Run Hadoop Stack on Kubernetes
A fully-functional Hadoop Yarn cluster as docker-compose deployment.
Ansible Playbook For Setup Hadoop HDFS
Open source data infrastructure platform. Designed for developers, built for speed.
Helm chart for Apache Hadoop using multi-arch docker images
λFS: an elastic, high-performance, serverless-function-based metadata service for large-scale distributed file systems (ACM ASPLOS'23)
This project builds a scalable log analytics pipeline use Lambda architecture for real-time and batch processing of NASA server logs.
Marathon on yarn
Twitter + Flume + Hadoop (HDFS, MapReduce) + Neo4j + Pyhton
关于这个话题
- 清单取自 GitHub 话题页并按 Star 数排序,每次展示前 20 个项目;原始页面见 https://github.com/topics/hadoop-hdfs。
- 该话题在 GitHub 上共有 362 个仓库, 本站收录的是其中最热门的 20 个,不是全量列表。
- Star / Fork 每日自动刷新一次,实时数据以 GitHub 为准。
- 当前 20 个项目累计 3.9 万 Star,覆盖 10 种主要语言,数据更新于 2026-11-08。
- 中文介绍来自 GitHub 官方话题说明(github/explore)的机器翻译,可点「查看原文」对照;译文缺失时会先展示原文。