apache/shardingsphere-elasticjob
apache/shardingsphere-elasticjob has 8,198 GitHub stars and 3,248 forks. GitHot measured 0 stars in 24 hours and +1 in 7 days. Last checked 2026-11-12 20:29 UTC. Last push 2026-10-27.
Distributed scheduled job
What you can do
- Support job sharding and high availability in distributed system
- Scale out for throughput and efficiency improvement
- Job processing capacity is flexible and scalable with the allocation of resources
- Execute job on suitable time and assigned resources
Crecimiento de estrellas medido
- in 24h
- 0
- in 7 days
- +1
- in 15 days
- Recopilando historial
- in 1 month
- Recopilando historial
Cambios netos en períodos que se solapan, no totales diarios. Los datos no disponibles se dejan en blanco. Las estrellas indican interés, no calidad.
README.md
OriginalElasticJob - Distributed scheduled job
Official website: https://shardingsphere.apache.org/elasticjob/
Through the functions of flexible scheduling, resource management and job management, it creates a distributed scheduling solution suitable for Internet scenarios, and provides a diversified job ecosystem through open architecture design. It uses a unified job API for each project. Developers only need code one time and can deploy at will.
ElasticJob became an Apache ShardingSphere Sub-project on May 28 2020.
You are welcome to communicate with the community via the mailing list.
Introduction
Using ElasticJob developers can no longer worry about the non functional requirements such as job scale out, so that they can focus more on business coding. At the same time, it can release operators too, so that they do not have to worry about high availability and management, and can automatically operate by simply adding servers.
It is a lightweight, decentralized solution that provides distributed task sharding services.

Features
Elastic Schedule
- Support job sharding and high availability in distributed system
- Scale out for throughput and efficiency improvement
- Job processing capacity is flexible and scalable with the allocation of resources
Resource Assign
- Execute job on suitable time and assigned resources
- Aggregation same job to same job executor
- Append resources to newly assigned jobs dynamically
Job Governance
- Failover
- Misfired
- Self diagnose and recover when distribute environment unstable
Job Dependency (TODO)
- DAG based job dependency
- DAG based job item dependency
Job Open Ecosystem
- Unify job api for extension
- Support rich job type lib, such as dataflow, script, HTTP, file, big data
- Focus business SDK, can work with Spring IOC
-
- Job administration
- Job event trace query
- Registry center management
Environment Required
Java
Java 8 or above required.
Maven
Maven 3.5.0 or above required.
ZooKeeper
ZooKeeper 3.6.0 or above required. See details
Explorar proyectos relacionados
Asabeneh/30-Days-Of-Python
El reto de programación 30 Days of Python es una guía paso a paso para aprender el lenguaje de programación Python en 30 días. Este reto puede llevar más de 100 días. Sigue tu propio ritmo. Estos vídeos también pueden ayudarte: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw
78,618 estrellasgrafana/grafana
Plataforma abierta y componible de observabilidad y visualización de datos. Visualiza métricas, registros y trazas de múltiples fuentes, como Prometheus, Loki, Elasticsearch, InfluxDB, Postgres y muchas más.
77,859 estrellasredis/redis
Para los desarrolladores que crean aplicaciones en tiempo real basadas en datos, Redis es la opción preferida, la más rápida y la de más funciones como caché, servidor de estructuras de datos y motor de consultas de documentos y vectores.
77,472 estrellasapache/superset
Apache Superset es una plataforma de visualización y exploración de datos.
75,495 estrellas