Revise.md

Key Java Concurrency Tools:

Here are the main tools and frameworks in Java’s concurrency world, and CompletableFuture is not the end—there are some even more powerful and specialized tools!

1. Thread Class (Basic Approach):

• we can create a new thread by extending the Thread class or implementing the Runnable interface.
• Not very flexible—it's manual, and error-prone, as we need to manage thread lifecycle and exceptions yourself.

2. Runnable and Callable (Functional Tasks):

• Runnable: Represents a task that doesn't return a result or throw a checked exception.
• Callable: A more advanced version of Runnable that can return a result and throw exceptions.
• Both can be submitted to an ExecutorService for management by a thread pool.

3. Future (Basic Asynchronous Tool):

• When we submit a Callable to an ExecutorService, it returns a Future.
• This allows we to retrieve the result when it's ready using future.get().
• The problem is that get() is blocking, which means it pauses the calling thread until the result is available.

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Advanced Concurrency and Parallelism Tools:

4. CompletableFuture (Asynchronous and Non-blocking):

• CompletableFuture builds upon Future, offering non-blocking features like thenApply, thenAccept, and thenRun.
• It allows chaining of tasks in an asynchronous fashion, supports combining multiple asynchronous operations, and lets we react to results or handle exceptions elegantly.
• we can write truly asynchronous, non-blocking code, and compose complex workflows of tasks.

So, yes, CompletableFuture is one of the most advanced general-purpose concurrency tools, but there's more when we need fine control or specific use cases.

5. ForkJoinPool (Parallelism):

• For heavy computational tasks, Java introduced ForkJoinPool with the goal of parallelizing work more efficiently.
• It works using divide-and-conquer algorithms by splitting tasks into smaller sub-tasks and executing them in parallel.
• we can submit RecursiveTask (returns a result) or RecursiveAction (does not return a result) to it.
• It’s great for tasks like parallel sorting, matrix multiplication, or recursive problems like mergesort.

6. Parallel Streams (Data Parallelism):

• Java 8 introduced parallel streams, allowing we to perform parallel processing on collections.
• It simplifies writing parallel code by abstracting concurrency.
• Example: list.parallelStream().map(...).collect(...) processes elements in parallel.
• It’s designed for data parallelism, where the same operation is performed on multiple data elements in parallel.

Use parallel streams for bulk operations on collections, but avoid using them for complex task coordination because they're high-level and abstract away the control.

7. Actor Model with Akka (Reactive Framework):

• Akka is a reactive toolkit that operates using the Actor Model for highly concurrent, distributed systems.
• Instead of directly managing threads, Akka actors communicate by sending messages to each other, and each actor processes messages asynchronously and in isolation.
• It’s a higher-level abstraction than CompletableFuture and great for scalable and fault-tolerant applications, especially in distributed systems.

8. Project Loom (Virtual Threads - Upcoming):

• Project Loom is a new initiative for Java that introduces lightweight, virtual threads (similar to green threads).
• These threads will allow developers to handle millions of concurrent tasks without worrying about the system’s OS-level thread limitations.
• Non-blocking IO becomes easier and more natural because these lightweight threads can handle blocking code without real blocking.

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Where Does CompletableFuture Fit?

• CompletableFuture is a sweet spot when we want non-blocking concurrency with composition of tasks and exception handling.
• It works great when we have asynchronous operations but don't want to block the calling thread for the result.
• If our use case is even more complex, we can use ForkJoinPool for intensive computation or Akka for reactive systems.

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When to Use What?

1. Basic parallel tasks: Use ExecutorService with Future.
2. Asynchronous tasks with callbacks: Use CompletableFuture.
3. Parallel processing on large datasets: Use Parallel Streams.
4. Recursive parallel tasks: Use ForkJoinPool.
5. Complex, concurrent systems: Use Akka or await Project Loom.

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Summary:

• CompletableFuture is one of the most powerful tools for writing asynchronous, non-blocking code.
• However, it’s not the final or only tool—ForkJoinPool, Parallel Streams, and frameworks like Akka offer solutions for even more specialized concurrency needs.
• For the future, Project Loom will change the game by making concurrency even easier to handle with virtual threads.

ExecutorService Role :

When we talk about ExecutorService, it is one of the best frameworks for managing threads efficiently in Java.The relationship between ExecutorService, Future, and CompletableFuture, and why they are often used together:

Why ExecutorService is Important:

1. Thread Management: ExecutorService manages a pool of threads for you, so we don't have to manually create or manage individual threads. This is a huge advantage because it prevents the overhead and complexity of directly creating threads.
2. Concurrency Control: It allows we to submit tasks (either Runnable or Callable) to the pool, and it handles the concurrency behind the scenes. It ensures efficient resource management, especially when dealing with a large number of tasks.

How Future Relates to ExecutorService:

• When we submit a Callable task to the ExecutorService, we get back a Future. This Future represents the result of the task that will be computed in the background. we can later call future.get() to retrieve the result of the task.

• So, Future and ExecutorService are often used together. When we use ExecutorService to submit a task, it internally returns a Future, which we can use to monitor or retrieve the result asynchronously.

  Example:

  ExecutorService executor = Executors.newFixedThreadPool(10);
  Future<Integer> future = executor.submit(() -> {
      // Some computation
      return 42;
  });
  
  // Block to get the result (this will block until the task is complete)
  Integer result = future.get();

Why CompletableFuture and not Future with ExecutorService?

Now, the main reason we talk about CompletableFuture more and not just ExecutorService with Future is because CompletableFuture offers more flexibility and non-blocking operations.

1. Non-blocking behavior:

   • Future.get() is blocking—when we call it, the current thread has to wait for the result.
   • With CompletableFuture, we can chain callbacks and write asynchronous, non-blocking code. we don’t need to block the thread waiting for the result; instead, we can use methods like thenApply(), thenAccept(), etc.

2. More Composable:

   • CompletableFuture allows we to chain tasks together, so we can create pipelines of asynchronous tasks, whereas ExecutorService with Future is more low-level and only lets we execute and retrieve single tasks.

   Example with CompletableFuture:

   CompletableFuture.supplyAsync(() -> {
       // Long-running task
       return 42;
   }).thenApply(result -> {
       // Non-blocking callback
       System.out.println("Result: " + result);
       return result;
   });

But ExecutorService is still important:

• ExecutorService is still crucial in the background, and in fact, CompletableFuture can use an ExecutorService under the hood to run tasks in the thread pool.

• If we don't specify an executor explicitly, CompletableFuture will use a default one (common ForkJoinPool), but we can pass a custom ExecutorService to control the thread pool:

  ExecutorService executor = Executors.newFixedThreadPool(10);
  CompletableFuture.supplyAsync(() -> {
      return 42;
  }, executor).thenAccept(result -> {
      System.out.println("Result: " + result);
  });

To Summarize:

• ExecutorService is the framework that manages threads and handles task execution. It's the backbone for most multithreading operations.
• Future is the basic tool used to retrieve results from tasks submitted to an ExecutorService, but it blocks when retrieving the result.
• CompletableFuture is an enhanced version, allowing we to write non-blocking code and chain asynchronous tasks, while still using an ExecutorService under the hood.

So, while we aren't explicitly talking about ExecutorService all the time, it's still there—and we can use it with both Future and CompletableFuture depending on our needs.

Structured concurrency Concept :

Structured concurrency is a concept that aims to make working with concurrency safer, more predictable, and easier to manage. It focuses on ensuring that tasks or threads are created, executed, and terminated in a structured and controlled way, so we don’t run into issues like resource leaks, deadlocks, or other unpredictable behavior.

Here's a breakdown of what structured concurrency is and why it's important:

1. What is Structured Concurrency?

Structured concurrency is a programming paradigm that:

• Ensures tasks are organized hierarchically. When we start a concurrent task, it must complete within the lifetime of its parent (like a function or a block of code).
• All concurrent tasks (like threads or asynchronous tasks) must finish before the parent scope completes. This prevents dangling tasks that can run in the background without supervision.

The idea is to make concurrent programming more like structured programming: just like functions, loops, or conditionals have clear beginnings and ends, structured concurrency ensures that concurrency has clear and well-defined scopes.

2. Why is Structured Concurrency Important?

In traditional concurrent programming, we can spawn threads or tasks that run in the background indefinitely. This can lead to:

• Orphaned tasks: Tasks that keep running even after the function that spawned them has finished.
• Resource leaks: Because threads can outlive their creators, they may hold onto resources like memory or locks, causing potential leaks or deadlocks.
• Error handling: Unhandled exceptions in one thread might not be caught by the parent, leading to inconsistent states or silent failures.

Structured concurrency addresses these issues by:

• Ensuring all threads/tasks are tracked.
• Making sure that when a parent function or scope ends, all its child tasks (threads, futures, etc.) are properly cleaned up, either by finishing their work or being canceled.
• Simplifying error handling by propagating exceptions across all child tasks, making it easier to handle errors consistently.

3. Analogy with Structured Programming:

Just like structured programming made it easier to reason about programs by using clear constructs like loops and functions, structured concurrency ensures that concurrency is neatly packaged in a way that prevents unintended consequences.

4. Structured Concurrency in Java:

In Java, structured concurrency is gaining attention in modern development due to the complexity of concurrent applications. It's not yet a formal feature in Java, but recent changes and frameworks are moving toward this direction.

For example:

• CompletableFuture and ExecutorService already give we some control over task lifetimes, but we can still have situations where a task outlives the scope that spawned it, which structured concurrency aims to avoid.
• Java's Project Loom is working on introducing virtual threads, which are lightweight threads that allow for more structured and managed concurrency.

5. Benefits of Structured Concurrency:

• Easier to reason about: Since tasks are scoped and tied to the parent, it's clear when and where tasks will start and finish.
• Better error handling: Any exceptions in child tasks can bubble up properly to the parent, ensuring no silent failures.
• Less resource leakage: Tasks that outlive their parent scopes are automatically cleaned up or canceled.
• Simpler debugging: Since concurrency is scoped, it's easier to debug concurrent tasks when they're part of a structured hierarchy.

6. Example of Structured Concurrency:

Consider a scenario where you're downloading multiple files concurrently. In traditional concurrency, if one thread fails, it might not clean up properly or might still hold resources. With structured concurrency, we ensure that all downloads are tied to a single scope, and if any thread fails or the parent function finishes, all related tasks are cleaned up automatically.

In Java, we might use structured concurrency-like patterns with something like this (using an executor to manage the thread pool):

public void processFiles(List<String> files) {
    ExecutorService executor = Executors.newFixedThreadPool(4);
    try {
        List<Future<Boolean>> results = new ArrayList<>();
        for (String file : files) {
            Future<Boolean> result = executor.submit(() -> {
                // Download the file
                return downloadFile(file);
            });
            results.add(result);
        }
        
        // Ensure all tasks complete before proceeding
        for (Future<Boolean> result : results) {
            if (!result.get()) {
                throw new RuntimeException("File processing failed");
            }
        }
    } finally {
        executor.shutdown();  // Clean up all threads
    }
}

In this example:

• All tasks are started within the scope of the processFiles method.
• The parent scope (the processFiles function) waits for all child tasks (the downloadFile tasks) to finish.
• No task is allowed to outlive the parent scope.

With structured concurrency, we don't leave any threads or tasks running when you're done with the method.

7. Project Loom and Structured Concurrency:

Java’s Project Loom is aiming to simplify concurrency by introducing virtual threads and structured concurrency patterns. These lightweight threads are easier to manage and can work with structured concurrency principles out of the box. With Loom, we will be able to use structured concurrency at a much lower cost to the system, as virtual threads will be more efficient and less resource-heavy than traditional threads.

Summary:

• Structured concurrency is about ensuring that concurrent tasks have well-defined lifetimes and are managed within a structured scope.
• It helps prevent common issues like orphaned tasks, resource leaks, and makes error handling simpler.
• Java is moving towards structured concurrency with tools like CompletableFuture and Project Loom.

This is a more disciplined and predictable approach to concurrency, making our application more robust and easier to maintain.