(Code Dissection) Akka Quartz Scheduler Scala’s way of scheduling(Part -2)

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I hope you guys are doing good, and had a fresh breath. Put your mask again if you find the previous topic smelly, as we are going to finish up the dissection for Akka Quartz Scheduler. I am going to refer the every Quartz-Scheduler things prefixed with java. So when I say Java-Quartz-Scheduler, I mean the the quartz library which is made through java, and which is wrapped by the Akka Quartz Scheduler. And one more thing to noticed is that QuartzSchedules and QuartzSchedule are different.

Alright, so let’s start then. First let’s revisit some of the parts of Akka-quartz which will help us to do the dissection part easily. If you check the repo, you will find that the class that we interact with is the QuartzSchedulerExtension. First we initialize it and then schedule it. When we initializes it, we have some states(immutable) for itself, then the schedule function is called. So let’s revisit this two parts. It initializes like this –

1. config – gets the config from the configuration file for the key “akka.quartz”
2. defaultConfig – hard coded strings parsed for configuration
3. threadCount – reads from the config(point 1) as Int for the key “threadPool.threadCount”
4. threadPriority – reads from the config(point 1) as Int for the key “threadPool.daemonThreads”
5. daemonThreads_? – reads from the config(point 1) as boolean for the key “threadPool.daemonThreads”
6. defaultTimeZone – reads from the config(point 1) as Timezone for the key “defaultTimeZone”
7. schedules – builds through the QuartzSchedules by passing config(point 1) and defaultTimezone(point 6) which returns a immutable map of string and QuartzSchedule.
8. runningJobs – just a declaration of mutable map with String and JobKey.

Lazy Declarations

9. threadPool – a new SimpleThreadPool with the help of threadCount(point 3), threadPriority(point 4) and daemonThreads_?(point 5).

10. jobStore – a new RAMJobStore

11. scheduler – here a lot of stuffs happen. It loads the java-Quartz-Scheduler using scheduler name, system name(from the Akka system passed to the QuartzSchedulerExtension) , threadPool(Point 9) and jobStore(point 10). Then it creates a scheduler from the java-Quartz’s DirectSchedulerFactory. Using this scheduler object, the schedule jobs are being shutted down by calling shutdown function, which is hooked into registerOnTermination of Akka system. Then finally the scheduler is being returned.

After this declarations comes the schedule function of QuartzScheduleExtension, where it receives the schedule name, actor reference, the message which will be needed to send to the actor and the QuartzSchedule object fetches from the schedules(point 7). In this function for the right case it sends the parameters to scheduleJob function. In the scheduleJob function it does the following tasks.

F1. creates a jobDataMap having key value types as String and AnyRef for logBus, receiver which is the ActoRef passed to it and the message which is again passed to it.

F2. creates a java-Quartz JobDataMap object through java-Quartz JobDataMapSupport object by converting scala jobDataMap to java jobDataMap and stored it in val called jobData.

F3. creates a java-Quartz Job through the jobData(point F2), SimpleActorMessageJob and description from schedule(QuartzSchedule) and stored it in a val called job

F4. add a key value pair in the runningJobs(point 8) of key name(from the parameter) and key from the job(point F3).

F5. creates a trigger from the schedule(QuartzSchedule object passed to the function) by calling buildTrigger.

F6. schedule the the job using the job(point F3) and trigger(point F5) using the scheduler(point 11)

You must have noticed by now that we have these terms which we need to dissect
i. QuartzSchedule
ii. QuartzSchedules
iii. SimpleActorMessageJob

And of course the java terms which needs that came up like JobDataMapSupport, Job, Trigger. Well let’s first see how java quartz scheduler works and don’t worry we’re not going deep down into java quartz library. We need this stuffs to understand java Quartz scheduler – The Scheduler, Job, jobDataMap and trigger.

java-quartz-shceduler (1)

In short a Scheduler schedules a job with the help of jobMapData and run when it’s being triggered. Job has a method called execute which takes the JobExecutionContext from where we can fetch the jobDataMap. So now the question is how Akka-Quartz-Scheduler wraps them? Well if you go through the points F1 to F6 you would have already know, how it works. At point F2 it creates the jobDataMap, SimpleActorMessageJob is the job, at F5 it creates the Trigger through the scheduler and at F6 . So the answer is Job is wrapped by SimpleActorMessageJob, Trigger is wrapped by QuartzSchedule and jobDataMap is created by java- JobDataMapSupport from the values jobData at (point F2). By now I hope you have fair idea how the scheduler(point 11) and jobDataMap (point F2) are being created. So what we have dissect now is the Job that is SimpleActorMessageJob and the Trigger i.e. QuartzSchedule.

Let’s first go through SimpleActorMessageJob as it is shorter than QuartzSchdule to explain :P. SimpleActionMessageJob extends java-Quartz’s Job, and when you extends a Job you have to override the execute function. The execute function takes JobExecutionContext as parameter and through this JobExecutionContext we can fetch the jobDataMap which in our case is sent from the QuartzSchedulerExtentsion (point F2). So basically this class has three functions as, getAs and execute where getAs is not being used anywhere :\. However as function is used inside the execute function to convert the objects get from jobDataMap. So the only question is what happens inside the execute method. And the answer is simple it gets the actorRef from the jobDataMap through the key receiver, the message through the key message the logBus to logs the stuffs through the key logBus(point F1). and then it just use the Akka’s tell function to send the message to the actor receiver ! msg.

Okay, so next thing left is QuartzSchedule. Well when we find the QuartzSchedule we find two more things QuartzSchedules(which we have named earlier) and QuartzCronSchedule. Well QuartzSchedule is sealed trait in the QuartzSchedules.scala file. QuartzCronSchedule implements it and QuartzSchedules creates the instances of QuartzCronSchedule.

Well it goes like this. If you see point 7 in the declaration, you will find that it sends config and defaultTimezone to QuartzSchedules to get a map of String and QuartzSchedule. Below are the tasks done through the QuartzSchedules.


QS1. In the apply function get the ConfigObject for “schedules”, and pass it to parseSchedule with name. Here the name is the key.

QS2. In parseSchedule fetch the timeZone using the key timeZone, calendar, description and sends it to parseCronSchedule.

QS3. In the parseCronSchedule it fetch the cron expression for the key expression, creates QuartzCronSchedule and returns.

The QuartzCronSchedule extends the QuartzSchedule and takes parameters name, description, expression timezone and calendar(points QS1 to QS3). it declares an object called schedule which creates a CronScheduleBuilder using expression and timezone. Where in QuartzSchedule there are declaration for name, description, schedule, calendar and an implemented function buildTrigger, which creates a java-Quartz’s TriggerBuilder using name, description and schedule. And here schedule is override in QuartzCronSchedule for CronScheduleBuilder.So if you revisit points F1 to F6 you will find that all these QuartzSchedule and QuartzCronSchedule are being called there. It would be wrong to say that Akka-Quartz-Scheduler works like the below diagram, but just to make similarity with java-Quartz it looks like this.

AkkaQuartzFlow (1).png

Now you may unmask and tell me if you like it ;).

Written by 

Pranjut Gogoi is the enthusiast of Machine Learning and AI with 8+ years of experience. He is been implementing different machine learning projects in Knoldus. He started an initiative called MachineX through which they share knowledge with the world. With this initiative, he broadcasts different free webinars, write different blogs and contributes to open source communities on machine learning and AI.

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