1 Quartz
2 spring-task
3 Elastic-Job Dangdang open source project, distributed task scheduling, can process data in shards
4 XXL-JOB, assign tasks to a server for execution, so as to achieve the purpose of distribution, refer to the document https://www.cnblogs.com/xuxueli/p/5021979.html
If it is a distributed system, or a cluster, the task solution:
1 Using Quartz and spring-task, through the configuration file, the A server only runs the a task, and the B server only runs the b task (not recommended)
2 Use Quartz and spring-task to filter the data when running batches. For example, you can set the task A of server A to only process the cardinality (or data marked with ip, only process the data marked by its own ip), and server B to process The task A only handles even numbers (or data that has its own ip tag)
3 Elastic-Job (recommended, especially when the requirements for task performance and fault tolerance are high, the official website http://elasticjob.io/index_zh.html, you can refer to the official documentation)
4 XXL-JOB (recommended, the advantages are simple, easy to use. Reference document https://www.cnblogs.com/xuxueli/p/5021979.html)