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mall项目是一套电商系统,包括前台商城系统及后台管理系统,基于Spring Boot+MyBatis实现,采用Docker容器化部署。 前台商城系统包含首页门户、商品推荐、商品搜索、商品展示、购物车、订单流程、会员中心、客户服务、帮助中心等模块。 后台管理系统包含商品管理、订单管理、会员管理、促销管理、运营管理、内容管理、统计报表、财务管理、权限管理、设置等模块。

Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.

  • batch-processing
  • kafka
  • pathway
  • python

Apache Spark - A unified analytics engine for large-scale data processing

  • python
  • scala
  • r
  • java

📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

🏆 Real-Time no-code, powerful and secure ORM 🚀 providing APIs and Docs without coding by Backend, and Frontend(Client) can customize response JSONs 🏆 实时 零代码、全功能、强安全 ORM 库 🚀 后端接口和文档零代码,前端(客户端) 定制返回 JSON 的数据和结构

flink learning blog. http://www.54tianzhisheng.cn/ 含 Flink 入门、概念、原理、实战、性能调优、源码解析等内容。涉及 Flink Connector、Metrics、Library、DataStream API、Table API & SQL 等内容的学习案例,还有 Flink 落地应用的大型项目案例(PVUV、日志存储、百亿数据实时去重、监控告警)分享。欢迎大家支持我的专栏《大数据实时计算引擎 Flink 实战与性能优化》

dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.

  • dbt-viewpoint
  • slack
  • pypa
  • data-modeling

mall学习教程,架构、业务、技术要点全方位解析。mall项目(60k+star)是一套电商系统,使用现阶段主流技术实现。涵盖了SpringBoot、MyBatis、Elasticsearch、RabbitMQ、Redis、MongoDB、MySQL等技术,采用Docker容器化部署。

Official repository of Trino, the distributed SQL query engine for big data, formerly known as PrestoSQL (https://trino.io)

mall-swarm是一套微服务商城系统,采用了 Spring Cloud Alibaba、Spring Boot 3.5、Sa-Token、MyBatis、Elasticsearch、Docker、Kubernetes等核心技术,同时提供了基于Vue的管理后台方便快速搭建系统。mall-swarm在电商业务的基础集成了注册中心、配置中心、监控中心、网关等系统功能。

  • springcloud
  • springboot
  • docker
  • java

The world's fastest open query engine for sub-second analytics both on and off the data lakehouse. With the flexibility to support nearly any scenario, StarRocks provides best-in-class performance for multi-dimensional analytics, real-time analytics, and ad-hoc queries. A Linux Foundation project.

An open-source storage framework that enables building a Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Trino, and Hive and APIs