I know you hate that answer, so here’s some information about what it depends "on".

First off, the JobStore that you use plays a significant factor. The RAM-based JobStore is MUCH (1000x) faster than the JDBC-based JobStore. The speed of JDBC-JobStore depends almost entirely on the speed of the connection to your database, which data base system that you use, and what hardware the database is running on. Quartz actually does very little processing itself, nearly all of the time is spent in the database. Of course RAMJobStore has a more finite limit on how many Jobs and Triggers can be stored, as you’re sure to have less RAM than hard-drive space for a database. You may also look at the FAQ "How do I improve the performance of JDBC-JobStore?"

So, the limiting factor of the number of Triggers and Jobs Quartz can "store" and monitor is really the amount of storage space available to the JobStore (either the amount of RAM or the amount of disk space).

Now, aside from "how many can I store?" is the question of "how many jobs can Quartz be running at the same moment in time?"

One thing that CAN slow down quartz itself is using a lot of listeners (TriggerListeners, JobListeners, and SchedulerListeners). The time spent in each listener obviously adds into the time spent "processing" a job’s execution, outside of actual execution of the job. This doesn’t mean that you should be terrified of using listeners, it just means that you should use them judiciously - don’t create a bunch of "global" listeners if you can really make more specialized ones. Also don’t do "expensive" things in the listeners, unless you really need to. Also be mindful that many plug-ins (such as the "history" plugin) are actually listeners.

The actual number of jobs that can be running at any moment in time is limited by the size of the thread pool. If there are five threads in the pool, no more than five jobs can run at a time. Be careful of making a lot of threads though, as the JVM, Operating System, and CPU all have a hard time juggling lots of threads, and performance degrades as the system spends time managing threads. In most cases performance starts to tank as you get into the several hundreds of threads (or fewer if the code being executed on the threads is intensive). Be mindful that if you’re running within an application server, it probably has created at least a few dozen threads of its own!

Aside from those factors, it really comes down to what your jobs DO. If your jobs take a long time to complete their work, and/or their work is very CPU-intensive, then you’re obviously not going to be able to run very many jobs at once, nor very many in a given span of time.

Finally, if you just can’t get enough horse-power out of one Quartz instance, you can always load-balance many Quartz instances (on separate machines). Each will run the jobs out of the shared database on a first-come first-serve basis, as quickly as the triggers need fired.

The clustering feature works best for scaling out long-running and/or cpu-intensive jobs (distributing the work-load over multiple nodes). If you need to scale out to support thousands of short-running (e.g 1 second) jobs, consider partitioning the set of jobs by using multiple distinct schedulers. Using one scheduler forces the use of a cluster-wide lock, a pattern that degrades performance as you add more clients.

So here you are this far into the answer of "how many", and I still haven’t given you an actual number. And I really hate to, because of all of the variables mentioned above. So let me just say, there are installments of Quartz out there that are managing hundreds-of-thousands of Jobs and Triggers, and that are, at any given moment in time executing several dozens of jobs – without even utilizing Quartz’s load-balancing capabilities. With this in mind, most people should feel confident that they can get the performance out of Quartz that they need.

An excellent description of RMI and codebase: http://www.kedwards.com/jini/codebase.html. One of the important points is to realize that "codebase" is used by the client!

Quick info about security managers: http://gethelp.devx.com/techtips/java_pro/10MinuteSolutions/10min0500.asp.

The important 'take away' of the Java API is:

Set the property JobDetail.setDurability(true) - which instructs Quartz not to delete the Job when it becomes an "orphan" (when the Job not longer has a Trigger referencing it).

One way is to use a listener (i.e. a TriggerListener, JobListener or SchedulerListener) that can notice the completion of a job/trigger and then immediately schedule a new trigger to fire. This approach can get a bit involved, since you’ll have to inform the listener which job follows which - and you may need to worry about persistence of this information. See the listener org.quartz.listeners.JobChainingJobListener which ships with Quartz - as it already has some of this functionality.

Another way is to build a Job that contains within its JobDataMap the name of the next job to fire, and as the job completes (the last step in its execute() method) have the job schedule the next job. Several people are doing this and have had good luck. Most have made a base (abstract) class that is a Job that knows how to get the job name and group out of the JobDataMap using pre-defined keys (constants) and contains code to schedule the identified job. This abstract Job’s implementation of execute() delegates to an abstract template method such as "doWork()" (where the extending Job class’s real work goes) and then it contains the code for scheduling the follow-up job. Then they simply make extensions of this class that included the work the job should do. The usage of 'durable' jobs, or the overloaded addJob(JobDetail, boolean, boolean) method (added in Quartz 2.2) helps the application define all the jobs at once with their proper data, without yet creating triggers to fire them (other than one trigger to fire the first job in the chain).

In the future, Quartz will provide a much cleaner way to do this, but until then, you’ll have to use one of the above approaches, or think of yet another that works better for you.

The second most common reason is that the trigger or trigger group has been paused. Daylight Saving Time and Triggers

CronTrigger and SimpleTrigger each handle daylight savings time in their own way - each in the way that is intuitive to the trigger type.

First, as a review of what daylight savings time is, please read this resource: https://secure.wikimedia.org/wikipedia/en/wiki/Daylight_saving_time_around_the_world. Some readers may be unaware that the rules are different for different nations/contents. For example, the 2005 daylight savings time started in the United States on April 3, but in Egypt on April 29. It is also important to know that not only the dates are different for different locals, but the time of the shift is different as well. Many places shift at 2:00 am, but others shift time at 1:00 am, others at 3:00 am, and still others right at midnight.

SimpleTrigger allows you to schedule jobs to fire every N milliseconds. As such, it has to do nothing in particular with respect to daylight savings time in order to "stay on schedule" - it simply keeps firing every N milliseconds. Regardless your SimpleTrigger is firing every 10 seconds, or every 15 minutes, or every hour or every 24 hours it will continue to do so. However the implication of this which confuses some users is that if your SimpleTrigger is firing say every 12 hours, before daylight savings switches it may be firing at what appears to be 3:00 am and 3:00 pm, but after daylight savings 4:00 am and 4:00 pm. This is not a bug - the trigger has kept firing exactly every N milliseconds, it just that the "name" of that time that humans impose on that moment has changed.

CronTrigger allows you to schedule jobs to fire at certain moments with respect to a "Gregorian calendar". Hence, if you create a trigger to fire every day at 10:00 am, before and after daylight savings time switches it will continue to do so. However, depending on whether it was the Spring or Autumn daylight savings event, for that particular Sunday, the actual time interval between the firing of the trigger on Sunday morning at 10:00 am since its firing on Saturday morning at 10:00 am will not be 24 hours, but will instead be 23 or 25 hours respectively.

There is one additional point users must understand about CronTrigger with respect to daylight savings. This is that you should take careful thought about creating schedules that fire between midnight and 3:00 am (the critical window of time depends on your trigger’s locale, as explained above). The reason is that depending on your trigger’s schedule, and the particular daylight event, the trigger may be skipped or may appear to not fire for an hour or two. As examples, say you are in the United States, where daylight savings events occur at 2:00 am. If you have a CronTrigger that fires every day at 2:15 am, then on the day of the beginning of daylight savings time the trigger will be skipped, since, 2:15 am never occurs that day. If you have a CronTrigger that fires every 15 minutes of every hour of every day, then on the day daylight savings time ends you will have an hour of time for which no triggerings occur, because when 2:00 am arrives, it will become 1:00 am again, however all of the firings during the one o’clock hour have already occurred, and the trigger’s next fire time was set to 2:00 am - hence for the next hour no triggerings will occur.

In summary, all of this makes perfect sense, and should be easy to remember if you keep these two rules in mind:

Other trigger types that are based on sliding along a calendar (rather than exact amounts of time), such as CalenderIntervalTrigger, will be similarly affected - but rather than missing a firing, or firing twice, may end up having it’s fire time shifted by an hour.

First, the obvious, but not-so-practical:

Now for something simple, but effective: Build indexes on the Quartz tables.

Most database systems will automatically put indexes on the primary-key fields, many will also automatically do it for the foreign-key field. Make sure yours does this, or make the indexes on all key fields of every table manually.

Next, manually add some additional indexes: most important to index are the TRIGGER table’s "next_fire_time" and "state" fields. Last (but not as important), add indexes to every column on the FIRED_TRIGGERS table.

The clustering feature works best for scaling out long-running and/or cpu-intensive jobs (distributing the work-load over multiple nodes). If you need to scale out to support thousands of short-running (e.g 1 second) jobs, consider partitioning the set of jobs by using multiple distinct schedulers (and hence multiple sets of tables (with distinct prefixes)). Using one scheduler forces the use of a cluster-wide lock, a pattern that degrades performance as you add more clients.

This particular query is extremely efficient for Oracle. For other databases, you’ll need to think of an efficient query that always works as long as the connection is good.

If you’re datasource is managed by your application server, make sure the datasource is configured in such a way that it can detect failed connections.

Some databases falsely detect deadlocks when a tx takes a long time.

If your Jobs' execute() methods use the Scheduler, make sure a transaction is in progress by using a UserTransaction or by setting the Quartz config property "org.quartz.scheduler.wrapJobExecutionInUserTransaction=true".

Quartz ships with well-proven clustering capabilities that offer scaling and high availability features. You can read about these features in the Quartz Configuration Reference.

Additional clustering features that do not rely upon a backing database are available (free of cost) from Terracotta.