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Hello there, students, in this lesson, we are going to learn with your fork join framework, we'll

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start from the high level overview of your framework and understanding of its basic principles.

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One will understand the theory of Forkin and Journey.

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We would jump straight to the source code to learn first joint pool class.

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I've explained what works to an algorithm is after that we are going to have practical code examples

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and I will show you how to submit tasks for execution with the help of furniture and pool will review

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recursive action and recursive type tasks.

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And at the end of the lesson we are going to discuss drawbacks of Thorbjoern framework that we need

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to be aware of for making a decision about its usage.

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Let's start from understanding what Furbies during the framework is.

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The first time it was presented in Java version seven.

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Why it was needed.

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The framework helps to speed up parallel processing by using all available course.

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It is designed for work that can be broken into smaller pieces recursively.

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The goal is to use all the available processing power to enhance the performance of your application.

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Why it is called for joins and it is named after the way how it works.

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The Framework X recursively breaking the task into smaller independent subtasks until they're simple

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enough to be executed asynchronously.

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And after that result of all subtasks, I recursively journey into a single result.

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This is due in part.

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That's why the framework is called for.

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Join the Fork.

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Join Framework distributes tasks to various threads in the thread.

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Pull workers that are sleeping or waiting, not actually sleeping and waiting.

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They're working on other smaller tasks for joint users work stealing algorithm workers.

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Threads that run out of things to do can steal tasks from other threats that are still busy.

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For example, doesn't create a separate thread for every single subtask.

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Instead, each threatened ZAPU has its own double ended.

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Q Modak, which stauss tasks.

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Let's talk a little bit more about work.

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Stulen algorithm.

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If I could add a simple thread that if we try to steal work from decks of business threats by default,

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every threat gets tasks from the head of its own deck.

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When it is empty, the threat takes that task from the tail of the deck of another business threat or

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from the global entry queue.

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Since this is who has the biggest pieces of work are likely to be located today, we're going to review

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a lot of JDK source code and code examples.

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So let me start screen sharing.

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The center of Fergin framework is, for example, Class I open source code of this class similar to

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Oza Executor's.

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It extends abasic executive service class that in turn implements executer service allsorts in the CPU

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attempt to find and execute tasks submitted to the CPU and or created by other active tasks that that

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a blocked or waiting.

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At the moment.

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This enables efficient processing when most tasks spawn other subtasks, as well as when many small

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tasks are submitted to the CPU from external clients.

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Let me open now.

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For example, demo class I created IT.

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Infrastructure and package done for you will be able to find the reference to the source code in attachments

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to the lesson.

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I am going to walk you through each line in this demo file.

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The first thing that we do here is create an offer of joint pull object.

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We can do this in different ways.

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The first one is to use Static Masset Common Pool.

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This will provide a reference to the common pool.

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This pool and any ongoing process are automatically terminated upon program termination in case we'll

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call X method of system class, for example.

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Another way to create an instance of, for example, is just call upon the constructor.

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The int parameter describes parallelism level.

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This level indicates how many threads or CPUs you want to work concurrently on tasks past the function

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pool.

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In this case we have parallel is level of four.

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We can create four adjourned without passing in value.

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In this case, parallelism is equal to the end value that is returned by available processers.

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Masset they remember in previous lesson I showed you a verbal processor that we can call on the runtime

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object to define the number of processing, of course, we have on the machine.

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Basically, if you don't have any specific reasons to set specific level of parallelism, you may use

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default constructor.

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Also, there is another constructor that allows it to pass to the constructor, sweat factory and error

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handler.

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Well, would you review similar example?

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Also, sweat factory in previous lesson and another argument of type, unquote, exception handler is

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a functional interface that requires you to implement logic of handling exceptional cases during the

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execution.

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It will depend on how you would like to address the exception.

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Now we can proceed with submitting a task to our executer, similar to Oprah as examples with Runnable

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and Kobel, we can submit two types of tasks actions and tasks.

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Action.

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This is something one doesn't return any value after execution.

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Just set of instructions that needs to be executed in a separate sweat and task.

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It is a type that will change the result of the execution similar to callable type.

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Recursive action is a type that will not return as a result of the execution and objects of recursive

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task type will return result of execution.

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Most of them has an absolute mass compute in which the task logic is defined also.

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Most of these types extends for the joint task.

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Let's review examples with each of these types.

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But before we jump to review code example, let me share a basic template for our tasks.

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On the slide.

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You can see pseudocode.

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If my portion of the work is small enough, does it work directly or else split my work into two pieces

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in one of the two pieces and wait for the results?

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That is how we should implement compute method.

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There should be some conditions that will tell us whether we can proceed with the execution directly

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or we should create some.

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Now let's look at the good example.

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So as you may already understand, recursive action is just a set of instructions that are needed to

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be done.

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And recursive action may still need to break up its work into smaller chunks, which can be executed

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by independent threads or CPU's.

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Recursive action is an absolute class that extends for joint task.

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So to create an object of this type, we need to have concrete implementation of this type in a separate

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file of default recursive action clause that extends recursive action.

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This is not a very meaningful example, but I decided to keep it super simple in order you would understand

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how it works.

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We have private in the field with named workload.

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We would initialize it with some value during the default recursive action object instantiation.

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And here is implementation of our compute method like you saw in template implementation.

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On the slide.

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We start with definition of a condition that should describe what we are going to proceed with.

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Action.

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Execution was a threat and one we should split our action into multiple subtasks.

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In this case, we check if the workload value is less than 18, 18 in this case is a random threshold.

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Just for the sake of example, when workload is less than 18, we just pursued action execution in the

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same thread.

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But in case it is equal to itchin or more, then we jump to our section where we create subtasks and

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call for massive.

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Here you can see two alternative ways how to achieve the same result.

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We can create subtasks and call for method for each subtask like you can see in the foreach loop.

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Or alternatively, we can use for a joint task class and call invoke all method and pass all subtasks

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that the result would be the same.

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I decided to keep for each loop here because the visualization is better in this case.

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Let's understand how we create subtasks basically for our template.

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We split my work into two pieces here.

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You can see that I create two objects of the same action type and in constructor I pass workload divided

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by two.

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I add all subtasks to the release and return it from the method.

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We use this list and for each loop or in invoke all Masset to submit this action for execution.

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Let's get back to the, for example, demo class.

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I just create an instance of my default recursive action and I pass it to the constructor.

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I call invoke method and pass the reference to my action object.

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Let's run this program and you can see that I split the workload and created two subtasks.

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To sum it up, in your action task, you need to find a way to reflect the total amount of work.

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Also, you need to define suitable thresholds that will be used to split action in subtasks.

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Like another example.

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This can be separate Masset that knows how to divide the work.

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And in implementation of compute method, you should describe the conditions that would define what

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it is time to split work into subtasks or proceed with execution.

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Hope that it is clear.

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Now let's look at the second type of tasks that we can submit into.

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For example, now we are going to recursive task, recursive task is also APSA class that extends for

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a joint task.

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We want to submit a recursive task when we want to get the result of the calculation and the response.

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The logic of interaction with objects of this type is similar was on the one difference.

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We have to join the results of computation from different set tasks.

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Let me open default recursive task class that extends recursive tasks and that implements compute method.

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As you can see, we have similar constructor and the same field as we had in recursive action.

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In case our condition tells us that we shouldn't split activity in different tasks, we just return

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the result.

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In this example, we just want to get values that twice the original value in the case.

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We need to split our work into subtasks.

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We do this, but also we need to join the results of all subtasks.

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I call Gern Masset on each subtask that's supposed to return the result of computation.

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I aggregate result in one variable and after that I return the result to them.

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This case I have, for example, demo two class.

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I create an instance of, for example, and call invoke method.

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I pass an instance of the false recursive task with workload 40.

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I run the program and Incans so output.

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You can see that I get 80 as a result.

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That is exactly what my task is supposed to do.

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Great.

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Is it clear for you how the recursive action and recursive task work?

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If yes, then we are good to proceed in case the things that are still not clear.

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Please leave your question under the switch and I will be happy to answer.

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Now we are going to learn more about such factory method from executor's class as new for stealing pool

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pull.

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This method is overloaded and has versions within parameter and without parameters in the source code

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of executor's class.

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You can see that this is nothing more than, for example, instantiate that with a specific level of

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parallelism or with the default level of parallelism that is equal to the number of available processors

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and how to work with.

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For example, you already know and we reviewed examples, I believe that you already understood potential

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benefits that we expect to get from, for example, effective usage of all course, by splitting tasks

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into subtasks, supposed to improve performance.

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But we would help us in all cases.

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Let's talk about disadvantages of, for example, probably after this lesson, you got an impression

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that Fork Join framework is something extremely cool, efficient and super fast.

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Probably even started to think that you have to use it.

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Most often.

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The evolution of Fergin pool vary between different engineers.

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Not everyone agreed and shared benefits of this type.

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If you would search the Internet pros and cons of, for example, you would discover that a group of

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people who doesn't like, for example, because of different reasons on the slide, you can see the

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list of the issues and drawbacks of, for example, based on different people opinion.

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So it makes sense in some degree and in my opinion, worse to share with you.

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So the drawbacks of, for example, are a faulty task manager.

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The foraging technique splits the work into fragments and joins the results together.

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And some practice that allows an intermediate joint for each fork can only work successfully in a controlled

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environment.

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A fatal flaw with Fergin framework by opinion of some group of people is that it is trying to manage

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and intimidate.

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Join in a task outside of a controlled environment.

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Only the operating system as c the operating system can manage and intimidate join in the task and usually

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there is a problem of errors, exceptions in subsequently FEG tasks.

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And the answer to most of the cases that may happen in real life is uncertainty.

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But this is not why people choose drama when we want to create robust application within the tools and

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techniques to deal with uncertainties.

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Inefficient, since all four tasks go into the same work as Red Deck, this team in various threads

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will fight each other at the top of the deck over the four tasks.

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This framework can never function efficiently in high performance environment, special purpose.

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There are some restrictions to follow to make sure we can benefit from using.

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For example, recommended restrictions must be plain.

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That is mean between one hundred and ten thousand basic computational steps in the compute masset compute

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intensive code only.

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No blockin, no input.

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Output, no synchronization, slow and unscalable, only works well on a small number of processors,

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this design can never scale to hundreds or thousands of processors.

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The overhead and reservation would nullify the benefits of additional processors exceedingly complex.

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You can spend more time if you wish to investigate.

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The source code of Thorbjoern framework was all Nasta types and how it is connected with the rest of

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concurrent tools and JDK.

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And you would agree that this is not the easiest and clear for understanding piece of JDK lacking in

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professional attributes.

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As a professional software engineer, as we always striving for excellence and following the best practices

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some of them are, programs fail usually as a worst possible time.

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Consequently, error recovery is paramount.

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Software needs Deunan balancing of resources.

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Administrators sometimes need classification, also called alerting logs and necessary.

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The software should be useful across a wide range of computer needs.

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The Fork Join Framework has none of this inadequate in scope.

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The forging framework is only designed to work in a trivial segment of the computing world on Java standards

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addition only on high performance workstations.

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Six plus CPUs without high persuading do not compute, only work with no task input output, no Intertrust

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concurrency and no networking.

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So this is just some of the criticism against for of joint pool.

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At the end of the day, it will be up to you how often and when to use it.

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And now you have all necessary information to make this decision.

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Let's recap what we have learned in this lesson.

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In this lesson we learned what Fork Join framework is now, you know, the main masses of, for example,

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class in the lesson.

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We had some examples where the recursive action and recursive task, we executed these types of tasks

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with the help of our gene pool.

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And at the end of the lesson, we have discussed Fergin framework drawbacks.

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That's it for this lesson.

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Thanks a lot for your attention.

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Have a great day and see you in the next lesson.