Quartz Enterprise Job Scheduler
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Project Release infomations and Project Resources. Note that these informations are from this projects Freecode.com page and the downloads themselves may not be hosted with SourceForge.JP.
 Project Release Information2011-03-31 10:38 Released on Tuesday, March 29, 2011. This is the most significant revision since the project began over a decade ago. The most obvious differences with version 2.0 are the significant changes to the API. These changes aim to: modernize the API to use collections and generics, remove ambiguities and redundancies, hide/remove methods that should not be public to client code, improve separation of concerns, and introduce a Domain Specific Language (DSL) for working with the core entities (jobs and triggers). 2005-09-25 23:09 This release contains several new features and changes, as well as a good number of bugfixes. The first phase of a significant rework of the documentation is complete. 2005-02-13 00:50 2004-06-11 20:09 Thos release contains a number of new features and bugfixes. The most notable additions/changes are performance improvements, improved XML initialization, more convenient interruption of executing jobs, new "interceptor" behavior for job/trigger listeners, new scheduling options for triggers, and a new mechanism for jobs to report the results of their operation. 2004-01-14 20:09 There is a new plugin for creating jobs/triggers with an XML file during initialization. Load balancing with clusters has been improved. Auto-assignment of instance IDs with clusters has been added. RMI-connected clients now auto-reconnect if the scheduler is "bounced". There are various bugfixes, most notably with Container-Managed Transactions. The Quartz management Web application is now distributed separately. Project Resources
Project Description Quartz is an enterprise-class job scheduler for integration with stand-alone Java applications and full-scale J2EE applications. Advanced features include clustering and participation in container managed transactions. It is highly scalable, very lightweight, and supports very complex scheduling. |  |
