caosuwenwu,charry,github

airflow

Apache Airflow - A platform to programmatically author, schedule, and monitor workflows

chronus

Chronus是360金融技术团队基于阿里开源项目-TBSchedule重写的分布式调度生产版本开源项目。

cloudshuffleservice

Cloud Shuffle Service(CSS) is a general purpose remote shuffle solution for compute engines, including Spark/Flink/MapReduce.

datax-distribute

datax 分布式服务：主要将job 和 taskGroup分拆在两个进程，采用rpc实现通信，就能达到分布式能力，避免单进程资源局限。

针对datax进行2次开发，实现data 以rpc的方式传递json配置调用推数服务，同时修复datax多处bug。项目中也引入nacos作为服务的配置中心和注册中心；同时项目内扩展了kafkawriter，rabbitmqwriter，esreader，hivereader。增强了hdfs插件，支持分区表推送，支持动态参数传递（例如时间实现自增式抽取）。具体使用方式可以参照example模块。目前该服务已经稳定服务某上市公司半年，累计总任务数100+ ，日推送数据过10亿。具体如何使用，如何做插件开发以及datax底层原理，请关注https://blog.csdn.net/xiaoyao1999hn

datax-web

DataX集成可视化页面，选择数据源即可一键生成数据同步任务，支持RDBMS、Hive、HBase、ClickHouse、MongoDB等数据源，批量创建RDBMS数据同步任务，集成开源调度系统，支持分布式、增量同步数据、实时查看运行日志、监控执行器资源、KILL运行进程、数据源信息加密等。

dubbo-rest-example

dubbo rest filter

dubbo-study

手写dubbo框架

flink

Apache Flink

flink-streaming-platform-web

基于flink-sql的实时流计算web平台

flinksql

仿照阿里blink使用sql开发flink的实时程序

god-of-bigdata

学习之路

hera

hera 分布式任务调度系统（数据部门专用）

hugegraph

HugeGraph Database core component, including graph engine, API, and built-in backends

incubator-dolphinscheduler

Dolphin Scheduler is a distributed and easy-to-expand visual DAG workflow scheduling system, dedicated to solving the complex dependencies in data processing, making the scheduling system out of the box for data processing.(分布式易扩展的可视化工作流任务调度)

mybatis-3

MyBatis SQL mapper framework for Java

mysql-connector-j

MySQL Connector/J

netty

Netty project - an event-driven asynchronous network application framework

netty-to-dubbo

基于Netty手写Dubbo框架

orc

Mirror of Apache Orc

spark_study

spark源码学习

springboot-simple-demo

开发模板：开发环境 IntelliJ IDEA JDK8 Maven 3.5.x lombok 1.16.18 使用框架 Spring Boot Swagger2 Druid Log4j2 MyBatis MyBatis Plus MySQL H2 Thymeleaf

streamx

Make stream processing easier! Flink & Spark development scaffold, The original intention of StreamX is to make the development of Flink easier. StreamX focuses on the management of development phases and tasks. Our ultimate goal is to build a one-stop big data solution integrating stream processing, batch processing, data warehouse and data laker.

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