Showing posts with label Java Concurrency. Show all posts
Showing posts with label Java Concurrency. Show all posts

Friday, 30 December 2016

Java Tutorial: Java Threads (Thread pool executor | Thread pool in java | Java thread pool)

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Introduction

Creating a new operating system thread for every incoming task in Java incurs significant memory and CPU overhead. A Thread Pool solves this problem by maintaining a pool of pre-created, reusable worker threads that execute tasks asynchronously from a blocking queue.

In this guide, you will learn how the ThreadPoolExecutor and the java.util.concurrent.Executors framework simplify multithreading, optimize system resource utilization, and improve application throughput.

1. Create a Runnable Task

Define a task by implementing the Runnable interface to represent the work to be executed by worker threads:

public class WorkerTask implements Runnable {
    private final String taskName;

    public WorkerTask(String taskName) {
        this.taskName = taskName;
    }

    @Override
    public void run() {
        System.out.println(Thread.currentThread().getName() + " executing " + taskName);
        try {
            Thread.sleep(1000); // Simulate work
        } catch (InterruptedException e) {
            Thread.currentThread().interrupt();
        }
        System.out.println(Thread.currentThread().getName() + " completed " + taskName);
    }
}
  

2. Initialize and Submit Tasks to ExecutorService

Create a fixed-size thread pool using the Executors factory class and submit multiple tasks for execution:

import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;

public class ThreadPoolDemo {
    public static void main(String[] args) {
        // Create a thread pool with 3 worker threads
        ExecutorService executor = Executors.newFixedThreadPool(3);

        // Submit 6 tasks to the pool
        for (int i = 1; i <= 6; i++) {
            executor.execute(new WorkerTask("Task-" + i));
        }

        // Shut down the executor gracefully after completion
        executor.shutdown();
    }
}
  

3. Key Advantages of Using Thread Pools

  • Resource Management: Prevents system degradation caused by creating too many threads simultaneously.
  • Better Performance: Eliminates thread creation and teardown latency by reusing existing threads.
  • Task Queueing: Safely buffers excess tasks in internal blocking queues until threads become available.

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Tuesday, 29 November 2016

Java Tutorial : Java Threads (Life cycle of a Thread in Java | Java thread life cycle_V6)

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What is a Thread Life Cycle in Java?

In Java, multithreading allows concurrent execution of two or more parts of a program to maximize CPU utilization. From creation to termination, every thread transitions through several distinct states managed by the JVM and OS scheduler.

Key States in Java Thread Life Cycle

  • New (Born): When a thread instance is created using the Thread class or Runnable interface, before calling start().
  • Runnable: After invoking start(), the thread becomes ready to run and waits for CPU time allocation from the thread scheduler.
  • Blocked / Waiting: When a thread is waiting to acquire a monitor lock or waiting indefinitely for another thread's notification.
  • Timed Waiting: When a thread waits for a specified time period (e.g., using sleep(ms) or join(ms)).
  • Terminated (Dead): When the thread finishes executing its run() method or terminates abruptly due to an unhandled exception.

Why Master Thread States?

Understanding these transitions helps you write robust concurrent applications, avoid common concurrency pitfalls like deadlocks and race conditions, and optimize system performance effectively.

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Java Tutorial : Java Threads (Life cycle of a Thread in Java | Java thread life cycle_V6) 
Java Tutorial : Java Threads (Life cycle of a Thread in Java | Java thread life cycle_V6) 
Java Tutorial : Java Threads (Life cycle of a Thread in Java | Java thread life cycle_V6) 
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  • Java Tutorial : Java Threads (Life cycle of a Thread in Java | Java thread life cycle_V5)

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    How Threads Work in Java

    A thread is a lightweight sub-process that allows a program to operate more efficiently by doing multiple tasks simultaneously. When you execute a Java program, the Java Virtual Machine (JVM) allocates execution paths, enabling concurrent processing through the thread life cycle.

    Step-by-Step Thread Execution Flow

    • 1. Instantiation: You create a thread object either by extending the Thread class or implementing the Runnable interface.
    • 2. Invoking start(): Calling start() notifies the thread scheduler that the thread is ready to execute its run() method.
    • 3. Execution & Scheduling: The JVM Thread Scheduler picks the thread from the ready pool and allocates CPU time slices to execute the business logic.
    • 4. Pausing & Resuming: Threads can temporarily enter waiting, timed-waiting, or blocked states during I/O operations or lock acquisition.
    • 5. Termination: Once the run() method finishes execution, the thread completes its life cycle and is garbage collected.

    Key Takeaway

    Understanding how threads transition between different states ensures you can build responsive, high-performance Java applications without common pitfalls like race conditions and resource leaks.

    Related Tutorials from Ram N Java


    Click here to watch in Youtube :
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    Java Tutorial : Java Threads (Life cycle of a Thread in Java | Java thread life cycle_V5) 
    Java Tutorial : Java Threads (Life cycle of a Thread in Java | Java thread life cycle_V5) 
    Java Tutorial : Java Threads (Life cycle of a Thread in Java | Java thread life cycle_V5) 
    See also:
  • All JavaEE Viedos Playlist
  • All JavaEE Viedos
  • All JAVA EE Links
  • Servlets Tutorial
  • All Design Patterns Links
  • JDBC Tutorial
  • Java Collection Framework Tutorial
  • JAVA Tutorial
  • Kids Tutorial
  • Thursday, 15 August 2013

    Scheduler Design Pattern

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    What is the Scheduler Design Pattern?

    In concurrent programming, managing the execution timing and coordination among threads accessing shared resources is crucial. The Scheduler Pattern is a specialized concurrency design pattern that provides explicit control over thread scheduling.

    Core Definition: The Scheduler design pattern is used to explicitly control when threads may execute single-threaded code blocks. It uses an explicit scheduler object that coordinates and sequences waiting threads.

    Real-World Example: File Read & Write Operations

    Consider a shared text file on the file system named names.txt containing employee names (such as "David" and "Steve"). In our system, we have three threads interacting with this file:

    • Two Reader Threads: Read contents from names.txt and print them to the console.
    • One Writer Thread: Appends new names into names.txt.

    If both the writer and readers access the file at the exact same moment without coordination, data corruption, file lock errors, or stale reads occur.

    How the Scheduler Object Coordinates Threads

    Instead of allowing threads to access the file arbitrarily, a Scheduler object explicitly sequences and coordinates when each thread gets access:

    • The Scheduler can schedule the reader threads to read from names.txt at fixed intervals (for instance, every 30 minutes).
    • The Scheduler can schedule the writer thread to execute and write updates at designated intervals (for instance, every 45 minutes).
    • It ensures write operations execute in isolation without clashing with ongoing reads, keeping thread functionalities well-ordered and conflict-free.

    Relationship with the Read-Write Lock Pattern

    The Read-Write Lock Pattern is frequently implemented using the Scheduler Pattern. By placing a scheduler in charge of lock acquisition, the system can enforce fairness—ensuring writer threads are not starved by a constant stream of reader threads, and vice-versa.

    Key Benefits of the Scheduler Pattern

    • Explicit Execution Sequencing: Gives application logic complete control over when and in what order waiting threads run.
    • Prevents Thread Starvation: Ensures fair access to shared resources across competing tasks.
    • Separates Scheduling from Execution: Keeps business task logic clean and decoupled from thread timing and synchronization rules.

    Recommended Concurrency Tutorials:


    Click here to watch in Youtube : https://www.youtube.com/watch?v=sGflGs2s1Bg

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    Scheduler Design Pattern















    See also:

  • All Design Patterns Links
  • Sunday, 11 August 2013

    Read-write lock Design Pattern

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    What is the Read-Write Lock Design Pattern?

    In multithreaded programming, a standard mutual exclusion lock (like a simple synchronized block) allows only one thread to access a resource at a time—even if all concurrent threads are simply reading data without modifying it. This introduces unnecessary bottlenecks. The Read-Write Lock Pattern (RW Lock) solves this by distinguishing between read and write access.

    Core Definition: The Read-Write Lock pattern is a concurrency design pattern that allows concurrent read access to an object by multiple threads, but requires exclusive access for write operations.

    The Readers-Writer Concurrency Problem

    The classic Readers-Writer Problem illustrates the fundamental challenges of concurrent shared data access:

    • If a thread is writing to data while another thread is reading, the reader may encounter dirty, inconsistent, or partially updated values.
    • If multiple threads try to write simultaneously without coordination, data gets corrupted.
    • However, multiple threads reading the exact same data at the same time cause zero conflict, as long as no write operation takes place.

    Real-World Example: File Object Access

    Consider a shared File Object in the file system accessed by four threads:

    • 3 Reader Threads (Threads 1, 2, and 3): Read information from the file object.
    • 1 Writer Thread (Thread 4): Writes updates to the file object.

    Rule 1: Concurrent Reading is Permitted

    All three reader threads can acquire the Read Lock concurrently and read information from the file in parallel without blocking one another.

    Rule 2: Writers Wait for Ongoing Readers

    If the writer thread (Thread 4) arrives while the reader threads are active, it cannot acquire the lock. The writer is blocked and must wait until all reader threads finish their work.

    Rule 3: Writing Requires Exclusive Access

    Once the writer thread acquires the Write Lock, no other thread—whether a reader or another writer—can access the file. All incoming reader threads are blocked until the writer completes its write operation and releases the lock.

    Java Implementation: ReentrantReadWriteLock

    In enterprise Java, this pattern is built right into java.util.concurrent.locks.ReentrantReadWriteLock:

    ReadWriteLock rwLock = new ReentrantReadWriteLock();
    
    // Reading concurrently
    rwLock.readLock().lock();
    try {
        // Read shared data concurrently
    } finally {
        rwLock.readLock().unlock();
    }
    
    // Writing exclusively
    rwLock.writeLock().lock();
    try {
        // Modify shared data exclusively
    } finally {
        rwLock.writeLock().unlock();
    }

    Key Advantages of Read-Write Lock

    • Significantly Higher Read Throughput: Maximizes performance in read-heavy applications (such as in-memory caches and catalogs).
    • Guarantees Thread Safety: Enforces strict exclusive access during writes, preventing race conditions and dirty reads.
    • Separation of Concerns: Explicitly separates read operations from mutation logic.

    Recommended Concurrency Tutorials:


    Click here to watch in Youtube : https://www.youtube.com/watch?v=xaKrYlmRCjM

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    Read-write lock Design Pattern















    See also:

  • All Design Patterns Links
  • Wednesday, 7 August 2013

    Concurrency patterns

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    What are Concurrency Design Patterns?

    In modern software engineering, multithreading and asynchronous task execution are critical for building scalable, high-performance applications. However, concurrent execution introduces significant challenges—such as race conditions, deadlocks, thread starvations, and thread-safety bugs.

    Concurrency Design Patterns are architectural and design-level blueprints that handle the coordination, scheduling, synchronization, and safe execution of multiple concurrent threads and processes.

    Essential Concurrency Design Patterns Checklist

    Here are the core concurrency design patterns utilized in enterprise Java and multithreaded system design:

    • Active Object Pattern: Decouples method execution from method invocation for objects that each reside in their own thread of control.
    • Balking Pattern: Executes an action on an object only when the object is in a valid state; otherwise, the request returns immediately without executing.
    • Binding Properties Pattern: Synchronizes property changes across multiple objects concurrently.
    • Double-Checked Locking Pattern: Reduces the overhead of acquiring a lock by testing the locking criterion before acquiring the lock.
    • Event-Based Asynchronous Pattern: Addresses multithreading issues using asynchronous event-driven notifications.
    • Guarded Suspension Pattern: Suspends thread execution until a specific condition or precondition is satisfied.
    • Join Pattern: Provides a declarative way to coordinate concurrent message-passing threads.
    • Lock Pattern: Enforces mutual exclusion to protect shared mutable state across threads.
    • Messaging Design Pattern (MDP): Coordinates communication between distributed concurrent components via message queues.
    • Monitor Object Pattern: Synchronizes concurrent method execution to ensure only one method runs within an object at a time.
    • Reactor Pattern: Demultiplexes and dispatches incoming events synchronously to associated handlers using an event loop.
    • Read-Write Lock Pattern: Allows concurrent read operations while ensuring exclusive access for write operations.
    • Scheduler Pattern: Explicitly controls the order in which threads execute sequential code blocks.
    • Thread Pool Pattern: Reuses a fixed pool of pre-allocated worker threads to execute tasks rather than repeatedly allocating and destroying threads.
    • Thread-Specific Storage Pattern: Allows multiple threads to access logically global data using thread-local storage without locking overhead.

    Why Master Concurrency Patterns?

    • Prevent Deadlocks and Race Conditions: Proven mechanisms for managing thread synchronization safely.
    • Maximize Hardware Utilization: Efficiently leverage multi-core CPU architectures.
    • Foundation of Modern Frameworks: Forms the core engine of Java Concurrency Utilities (java.util.concurrent), Netty, Node.js, and Akka.

    Recommended Concurrency & Architecture Tutorials:


    Click here to watch in Youtube : https://www.youtube.com/watch?v=a6TNZgqqJlg

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    Concurrency patterns














    See also:

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  • Friday, 2 August 2013

    Thread Pool Design Pattern

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    What is the Thread Pool Design Pattern?

    In multithreaded enterprise applications, repeatedly creating and destroying OS threads incurs massive memory and CPU overhead. The Thread Pool Pattern solves this by maintaining a pool of worker threads ready to execute incoming tasks.

    Core Definition: The Thread Pool pattern is a specialized variation of the Object Pool Pattern where worker threads are managed, reused, and allocated to execute incoming tasks from a waiting queue.

    The 3 Core Components of a Thread Pool

    The architecture of the Thread Pool pattern centers around three key elements:

    • 1. Task Queue (Waiting Tasks): Holds the waiting tasks (or jobs) submitted by client applications that need execution.
    • 2. Thread Pool (Worker Threads): Responsible for creating, maintaining, and managing worker threads. Each thread pulls a task from the task queue, executes it, and repeats until the queue is empty.
    • 3. Completed Task Queue: Once a worker thread completes a task, the finished job or result is moved to the completed task queue, freeing up the thread to accept new work.

    How Dynamic Worker Scaling Works

    Consider a high-performance web server handling client requests:

    1. When 100 concurrent HTTP requests arrive, they enter the waiting task queue.
    2. The thread pool allocates or spins up worker threads to handle those 100 requests concurrently.
    3. Once tasks are finished, threads either return to an idle/sleep state in the pool or scale down dynamically based on configured thresholds.
    // Standard Java Executor Framework Thread Pool
    ExecutorService threadPool = Executors.newFixedThreadPool(10);
    
    // Submitting tasks to the pool
    threadPool.submit(() -> {
        System.out.println("Processing task inside thread: " + Thread.currentThread().getName());
    });
    
    // Proper shutdown
    threadPool.shutdown();

    Key Advantages of Using a Thread Pool

    • High Performance: Eliminates the costly thread creation and teardown overhead by reusing active threads.
    • Resource Management: Prevents Out-Of-Memory (OOM) errors and CPU thrashing by placing a hard ceiling on concurrent active threads.
    • Underpins Java Concurrency: Forms the exact operational engine behind Java’s java.util.concurrent.ThreadPoolExecutor, Spring’s @Async, and web application containers like Tomcat and Netty.

    Recommended Concurrency & Design Pattern Tutorials:


    Click here to watch in Youtube : https://www.youtube.com/watch?v=kfr49sS-FNE

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    Thread Pool Design Pattern














    See also:

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