refer to : http://www.quartz-scheduler.org/documentation/2.3.1-SNAPSHOT/tutorials/index.html
Using Quartz
refer to : http://www.quartz-scheduler.org/documentation/2.3.1-SNAPSHOT/tutorials/tutorial-lesson-01.html
Before you can use the scheduler, it needs to be instantiated (who’d have guessed?). To do this, you use a SchedulerFactory. Some users of Quartz may keep an instance of a factory in a JNDI store, others may find it just as easy (or easier) to instantiate and use a factory instance directly (such as in the example below).
Once a scheduler is instantiated, it can be started, placed in stand-by mode, and shutdown. Note that once a scheduler is shutdown, it cannot be restarted without being re-instantiated. Triggers do not fire (jobs do not execute) until the scheduler has been started, nor while it is in the paused state.
Here’s a quick snippet of code, that instantiates and starts a scheduler, and schedules a job for execution:
SchedulerFactory schedFact = new org.quartz.impl.StdSchedulerFactory();
Scheduler sched = schedFact.getScheduler();
sched.start();
// define the job and tie it to our HelloJob class
JobDetail job = newJob(HelloJob.class)
.withIdentity("myJob", "group1")
.build();
// Trigger the job to run now, and then every 40 seconds
Trigger trigger = newTrigger()
.withIdentity("myTrigger", "group1")
.startNow()
.withSchedule(simpleSchedule()
.withIntervalInSeconds(40)
.repeatForever())
.build();
// Tell quartz to schedule the job using our trigger
sched.scheduleJob(job, trigger);
As you can see, working with quartz is rather simple. In Lesson 2 we’ll give a quick overview of Jobs and Triggers, and Quartz’s API so that you can more fully understand this example.
The Quartz API, Jobs And Triggers
refer to : http://www.quartz-scheduler.org/documentation/2.3.1-SNAPSHOT/tutorials/tutorial-lesson-02.html
The Quartz API
The key interfaces of the Quartz API are:
- Scheduler - the main API for interacting with the scheduler.
- Job - an interface to be implemented by components that you wish to have executed by the scheduler.
- JobDetail - used to define instances of Jobs.
- Trigger - a component that defines the schedule upon which a given Job will be executed.
- JobBuilder - used to define/build JobDetail instances, which define instances of Jobs.
- TriggerBuilder - used to define/build Trigger instances.
A Scheduler’s life-cycle is bounded by it’s creation, via a SchedulerFactory and a call to its shutdown() method. Once created the Scheduler interface can be used add, remove, and list Jobs and Triggers, and perform other scheduling-related operations (such as pausing a trigger). However, the Scheduler will not actually act on any triggers (execute jobs) until it has been started with the start() method, as shown in Lesson 1.
Quartz provides “builder” classes that define a Domain Specific Language (or DSL, also sometimes referred to as a “fluent interface”). In the previous lesson you saw an example of it, which we present a portion of here again:
// define the job and tie it to our HelloJob class
JobDetail job = newJob(HelloJob.class)
.withIdentity("myJob", "group1") // name "myJob", group "group1"
.build();
// Trigger the job to run now, and then every 40 seconds
Trigger trigger = newTrigger()
.withIdentity("myTrigger", "group1")
.startNow()
.withSchedule(simpleSchedule()
.withIntervalInSeconds(40)
.repeatForever())
.build();
// Tell quartz to schedule the job using our trigger
sched.scheduleJob(job, trigger);
The block of code that builds the job definition is using methods that were statically imported from the JobBuilder class. Likewise, the block of code that builds the trigger is using methods imported from the TriggerBuilder class - as well as from the SimpleScheduleBuilder class.
The static imports of the DSL can be achieved through import statements such as these:
import static org.quartz.JobBuilder.*;
import static org.quartz.SimpleScheduleBuilder.*;
import static org.quartz.CronScheduleBuilder.*;
import static org.quartz.CalendarIntervalScheduleBuilder.*;
import static org.quartz.TriggerBuilder.*;
import static org.quartz.DateBuilder.*;
The various “ScheduleBuilder” classes have methods relating to defining different types of schedules.
The DateBuilder class contains various methods for easily constructing java.util.Date instances for particular points in time (such as a date that represents the next even hour - or in other words 10:00:00 if it is currently 9:43:27).
Jobs and Triggers
A Job is a class that implements the Job interface, which has only one simple method:
The Job Interface
package org.quartz;
public interface Job {
public void execute(JobExecutionContext context)
throws JobExecutionException;
}
When the Job’s trigger fires (more on that in a moment), the execute(…) method is invoked by one of the scheduler’s worker threads. The JobExecutionContext object that is passed to this method provides the job instance with information about its “run-time” environment - a handle to the Scheduler that executed it, a handle to the Trigger that triggered the execution, the job’s JobDetail object, and a few other items.
The JobDetail object is created by the Quartz client (your program) at the time the Job is added to the scheduler. It contains various property settings for the Job, as well as a JobDataMap, which can be used to store state information for a given instance of your job class. It is essentially the definition of the job instance, and is discussed in further detail in the next lesson.
Trigger objects are used to trigger the execution (or ‘firing’) of jobs. When you wish to schedule a job, you instantiate a trigger and ‘tune’ its properties to provide the scheduling you wish to have. Triggers may also have a JobDataMap associated with them - this is useful to passing parameters to a Job that are specific to the firings of the trigger. Quartz ships with a handful of different trigger types, but the most commonly used types are SimpleTrigger and CronTrigger.
SimpleTrigger is handy if you need ‘one-shot’ execution (just single execution of a job at a given moment in time), or if you need to fire a job at a given time, and have it repeat N times, with a delay of T between executions. CronTrigger is useful if you wish to have triggering based on calendar-like schedules - such as “every Friday, at noon” or “at 10:15 on the 10th day of every month.”
Why Jobs AND Triggers? Many job schedulers do not have separate notions of jobs and triggers. Some define a ‘job’ as simply an execution time (or schedule) along with some small job identifier. Others are much like the union of Quartz’s job and trigger objects. While developing Quartz, we decided that it made sense to create a separation between the schedule and the work to be performed on that schedule. This has (in our opinion) many benefits.
For example, Jobs can be created and stored in the job scheduler independent of a trigger, and many triggers can be associated with the same job. Another benefit of this loose-coupling is the ability to configure jobs that remain in the scheduler after their associated triggers have expired, so that that it can be rescheduled later, without having to re-define it. It also allows you to modify or replace a trigger without having to re-define its associated job.
Identities
Jobs and Triggers are given identifying keys as they are registered with the Quartz scheduler. The keys of Jobs and Triggers (JobKey and TriggerKey) allow them to be placed into ‘groups’ which can be useful for organizing your jobs and triggers into categories such as “reporting jobs” and “maintenance jobs”. The name portion of the key of a job or trigger must be unique within the group - or in other words, the complete key (or identifier) of a job or trigger is the compound of the name and group.
You now have a general idea about what Jobs and Triggers are, you can learn more about them in Lesson 3: More About Jobs & JobDetails and Lesson 4: More About Triggers.
More About Jobs and Job Details
refer to : http://www.quartz-scheduler.org/documentation/2.3.1-SNAPSHOT/tutorials/tutorial-lesson-03.html
As you saw in Lesson 2, Jobs are rather easy to implement, having just a single ‘execute’ method in the interface. There are just a few more things that you need to understand about the nature of jobs, about the execute(…) method of the Job interface, and about JobDetails.
While a job class that you implement has the code that knows how to do the actual work of the particular type of job, Quartz needs to be informed about various attributes that you may wish an instance of that job to have. This is done via the JobDetail class, which was mentioned briefly in the previous section.
JobDetail instances are built using the JobBuilder class. You will typically want to use a static import of all of its methods, in order to have the DSL-feel within your code.
import static org.quartz.JobBuilder.*;
Let’s take a moment now to discuss a bit about the ‘nature’ of Jobs and the life-cycle of job instances within Quartz. First lets take a look back at some of that snippet of code we saw in Lesson 1:
// define the job and tie it to our HelloJob class
JobDetail job = newJob(HelloJob.class)
.withIdentity("myJob", "group1") // name "myJob", group "group1"
.build();
// Trigger the job to run now, and then every 40 seconds
Trigger trigger = newTrigger()
.withIdentity("myTrigger", "group1")
.startNow()
.withSchedule(simpleSchedule()
.withIntervalInSeconds(40)
.repeatForever())
.build();
// Tell quartz to schedule the job using our trigger
sched.scheduleJob(job, trigger);
Now consider the job class “HelloJob” defined as such:
public class HelloJob implements Job {
public HelloJob() {
}
public void execute(JobExecutionContext context)
throws JobExecutionException
{
System.err.println("Hello! HelloJob is executing.");
}
}
Notice that we give the scheduler a JobDetail instance, and that it knows the type of job to be executed by simply providing the job’s class as we build the JobDetail. Each (and every) time the scheduler executes the job, it creates a new instance of the class before calling its execute(…) method. When the execution is complete, references to the job class instance are dropped, and the instance is then garbage collected. One of the ramifications of this behavior is the fact that jobs must have a no-argument constructor (when using the default JobFactory implementation). Another ramification is that it does not make sense to have state data-fields defined on the job class - as their values would not be preserved between job executions.
You may now be wanting to ask “how can I provide properties/configuration for a Job instance?” and “how can I keep track of a job’s state between executions?” The answer to these questions are the same: the key is the JobDataMap, which is part of the JobDetail object.
JobDataMap
The JobDataMap can be used to hold any amount of (serializable) data objects which you wish to have made available to the job instance when it executes. JobDataMap is an implementation of the Java Map interface, and has some added convenience methods for storing and retrieving data of primitive types.
Here’s some quick snippets of putting data into the JobDataMap while defining/building the JobDetail, prior to adding the job to the scheduler:
// define the job and tie it to our DumbJob class
JobDetail job = newJob(DumbJob.class)
.withIdentity("myJob", "group1") // name "myJob", group "group1"
.usingJobData("jobSays", "Hello World!")
.usingJobData("myFloatValue", 3.141f)
.build();
Here’s a quick example of getting data from the JobDataMap during the job’s execution:
public class DumbJob implements Job {
public DumbJob() {
}
public void execute(JobExecutionContext context)
throws JobExecutionException
{
JobKey key = context.getJobDetail().getKey();
JobDataMap dataMap = context.getJobDetail().getJobDataMap();
String jobSays = dataMap.getString("jobSays");
float myFloatValue = dataMap.getFloat("myFloatValue");
System.err.println("Instance " + key + " of DumbJob says: " + jobSays + ", and val is: " + myFloatValue);
}
}
If you use a persistent JobStore (discussed in the JobStore section of this tutorial) you should use some care in deciding what you place in the JobDataMap, because the object in it will be serialized, and they therefore become prone to class-versioning problems. Obviously standard Java types should be very safe, but beyond that, any time someone changes the definition of a class for which you have serialized instances, care has to be taken not to break compatibility. Optionally, you can put JDBC-JobStore and JobDataMap into a mode where only primitives and strings are allowed to be stored in the map, thus eliminating any possibility of later serialization problems.
If you add setter methods to your job class that correspond to the names of keys in the JobDataMap (such as a setJobSays(String val) method for the data in the example above), then Quartz’s default JobFactory implementation will automatically call those setters when the job is instantiated, thus preventing the need to explicitly get the values out of the map within your execute method.
Triggers can also have JobDataMaps associated with them. This can be useful in the case where you have a Job that is stored in the scheduler for regular/repeated use by multiple Triggers, yet with each independent triggering, you want to supply the Job with different data inputs.
The JobDataMap that is found on the JobExecutionContext during Job execution serves as a convenience. It is a merge of the JobDataMap found on the JobDetail and the one found on the Trigger, with the values in the latter overriding any same-named values in the former.
Here’s a quick example of getting data from the JobExecutionContext’s merged JobDataMap during the job’s execution:
public class DumbJob implements Job {
public DumbJob() {
}
public void execute(JobExecutionContext context)
throws JobExecutionException
{
JobKey key = context.getJobDetail().getKey();
JobDataMap dataMap = context.getMergedJobDataMap(); // Note the difference from the previous example
String jobSays = dataMap.getString("jobSays");
float myFloatValue = dataMap.getFloat("myFloatValue");
ArrayList state = (ArrayList)dataMap.get("myStateData");
state.add(new Date());
System.err.println("Instance " + key + " of DumbJob says: " + jobSays + ", and val is: " + myFloatValue);
}
}
Or if you wish to rely on the JobFactory “injecting” the data map values onto your class, it might look like this instead:
public class DumbJob implements Job {
String jobSays;
float myFloatValue;
ArrayList state;
public DumbJob() {
}
public void execute(JobExecutionContext context)
throws JobExecutionException
{
JobKey key = context.getJobDetail().getKey();
JobDataMap dataMap = context.getMergedJobDataMap(); // Note the difference from the previous example
state.add(new Date());
System.err.println("Instance " + key + " of DumbJob says: " + jobSays + ", and val is: " + myFloatValue);
}
public void setJobSays(String jobSays) {
this.jobSays = jobSays;
}
public void setMyFloatValue(float myFloatValue) {
myFloatValue = myFloatValue;
}
public void setState(ArrayList state) {
state = state;
}
}
You’ll notice that the overall code of the class is longer, but the code in the execute() method is cleaner. One could also argue that although the code is longer, that it actually took less coding, if the programmer’s IDE was used to auto-generate the setter methods, rather than having to hand-code the individual calls to retrieve the values from the JobDataMap. The choice is yours.
Job “Instances”
Many users spend time being confused about what exactly constitutes a “job instance”. We’ll try to clear that up here and in the section below about job state and concurrency.
You can create a single job class, and store many ‘instance definitions’ of it within the scheduler by creating multiple instances of JobDetails - each with its own set of properties and JobDataMap - and adding them all to the scheduler.
For example, you can create a class that implements the Job interface called “SalesReportJob”. The job might be coded to expect parameters sent to it (via the JobDataMap) to specify the name of the sales person that the sales report should be based on. They may then create multiple definitions (JobDetails) of the job, such as “SalesReportForJoe” and “SalesReportForMike” which have “joe” and “mike” specified in the corresponding JobDataMaps as input to the respective jobs.
When a trigger fires, the JobDetail (instance definition) it is associated to is loaded, and the job class it refers to is instantiated via the JobFactory configured on the Scheduler. The default JobFactory simply calls newInstance() on the job class, then attempts to call setter methods on the class that match the names of keys within the JobDataMap. You may want to create your own implementation of JobFactory to accomplish things such as having your application’s IoC or DI container produce/initialize the job instance.
In “Quartz speak”, we refer to each stored JobDetail as a “job definition” or “JobDetail instance”, and we refer to a each executing job as a “job instance” or “instance of a job definition”. Usually if we just use the word “job” we are referring to a named definition, or JobDetail. When we are referring to the class implementing the job interface, we usually use the term “job class”.
Job State and Concurrency
Now, some additional notes about a job’s state data (aka JobDataMap) and concurrency. There are a couple annotations that can be added to your Job class that affect Quartz’s behavior with respect to these aspects.
@DisallowConcurrentExecution is an annotation that can be added to the Job class that tells Quartz not to execute multiple instances of a given job definition (that refers to the given job class) concurrently.
Notice the wording there, as it was chosen very carefully. In the example from the previous section, if “SalesReportJob” has this annotation, then only one instance of “SalesReportForJoe” can execute at a given time, but it can execute concurrently with an instance of “SalesReportForMike”. The constraint is based upon an instance definition (JobDetail), not on instances of the job class. However, it was decided (during the design of Quartz) to have the annotation carried on the class itself, because it does often make a difference to how the class is coded.
@PersistJobDataAfterExecution is an annotation that can be added to the Job class that tells Quartz to update the stored copy of the JobDetail’s JobDataMap after the execute() method completes successfully (without throwing an exception), such that the next execution of the same job (JobDetail) receives the updated values rather than the originally stored values. Like the @DisallowConcurrentExecution annotation, this applies to a job definition instance, not a job class instance, though it was decided to have the job class carry the attribute because it does often make a difference to how the class is coded (e.g. the ‘statefulness’ will need to be explicitly ‘understood’ by the code within the execute method).
If you use the @PersistJobDataAfterExecution annotation, you should strongly consider also using the @DisallowConcurrentExecution annotation, in order to avoid possible confusion (race conditions) of what data was left stored when two instances of the same job (JobDetail) executed concurrently.
Other Attributes Of Jobs
Here’s a quick summary of the other properties which can be defined for a job instance via the JobDetail object:
-
Durability - if a job is non-durable, it is automatically deleted from the scheduler once there are no longer any active triggers associated with it. In other words, non-durable jobs have a life span bounded by the existence of its triggers.
-
RequestsRecovery - if a job “requests recovery”, and it is executing during the time of a ‘hard shutdown’ of the scheduler (i.e. the process it is running within crashes, or the machine is shut off), then it is re-executed when the scheduler is started again. In this case, the JobExecutionContext.isRecovering() method will return true.
JobExecutionException
Finally, we need to inform you of a few details of the Job.execute(…) method. The only type of exception (including RuntimeExceptions) that you are allowed to throw from the execute method is the JobExecutionException. Because of this, you should generally wrap the entire contents of the execute method with a ‘try-catch’ block. You should also spend some time looking at the documentation for the JobExecutionException, as your job can use it to provide the scheduler various directives as to how you want the exception to be handled.