####//short keys:- idea ide java
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//alt + enter to create/show suggestion to create local variable# coreJava17-learning-program
In Java, multithreading is a core feature that allows concurrent execution of two or more threads. Understanding the different thread methods—sleep(), yield(), wait(), notify(), and join()—is crucial for effective thread management. Here's a brief description of each, along with real-time examples.
Description: Pauses the execution of the current thread for a specified duration (in milliseconds). It doesn't release any locks.
Example: Simulating a download process.
java code
class DownloadTask extends Thread {
public void run() {
System.out.println("Download started.");
try {
// Simulate download time
Thread.sleep(5000);
} catch (InterruptedException e) {
e.printStackTrace();
}
System.out.println("Download completed.");
}
}
public class SleepExample {
public static void main(String[] args) {
DownloadTask task = new DownloadTask();
task.start();
}
}
Description: Suggests to the thread scheduler that the current thread is willing to yield its current use of the CPU. This method does not guarantee that another thread will start running; it's just a hint.
Example: Threads attempting to process tasks in a round-robin fashion.
java code
class Task extends Thread {
public void run() {
for (int i = 0; i < 5; i++) {
System.out.println(Thread.currentThread().getName() + " is executing.");
Thread.yield(); // Suggest to yield the CPU
}
}
}
public class YieldExample {
public static void main(String[] args) {
Task t1 = new Task();
Task t2 = new Task();
t1.start();
t2.start();
}
}
Description: Causes the current thread to wait until another thread invokes notify() or notifyAll() on the same object. It releases the lock on the object.
Example: A producer-consumer scenario.
java code
class SharedResource {
private int data;
private boolean available = false;
public synchronized int consume() throws InterruptedException {
while (!available) {
wait(); // Wait until data is available
}
available = false;
notify(); // Notify producer
return data;
}
public synchronized void produce(int value) throws InterruptedException {
while (available) {
wait(); // Wait until data is consumed
}
data = value;
available = true;
notify(); // Notify consumer
}
}
class Producer extends Thread {
SharedResource resource;
Producer(SharedResource resource) {
this.resource = resource;
}
public void run() {
for (int i = 0; i < 5; i++) {
try {
resource.produce(i);
System.out.println("Produced: " + i);
} catch (InterruptedException e) {
e.printStackTrace();
}
}
}
}
class Consumer extends Thread {
SharedResource resource;
Consumer(SharedResource resource) {
this.resource = resource;
}
public void run() {
for (int i = 0; i < 5; i++) {
try {
int value = resource.consume();
System.out.println("Consumed: " + value);
} catch (InterruptedException e) {
e.printStackTrace();
}
}
}
}
public class WaitNotifyExample {
public static void main(String[] args) {
SharedResource resource = new SharedResource();
new Producer(resource).start();
new Consumer(resource).start();
}
}
Description: Wakes up a single thread (or all waiting threads, if notifyAll() is called) that is waiting on the object's monitor.
Example: This is already demonstrated in the producer-consumer scenario above.
Description: Waits for a thread to die. When one thread calls join() on another, it blocks until that thread terminates.
Example: Ensuring one thread completes before proceeding in another thread.
java code
class TaskWithJoin extends Thread {
public void run() {
for (int i = 1; i <= 3; i++) {
System.out.println(Thread.currentThread().getName() + " executing task " + i);
try {
Thread.sleep(1000);
} catch (InterruptedException e) {
e.printStackTrace();
}
}
}
}
public class JoinExample {
public static void main(String[] args) {
TaskWithJoin task1 = new TaskWithJoin();
TaskWithJoin task2 = new TaskWithJoin();
task1.start();
try {
task1.join(); // Main thread waits for task1 to complete
} catch (InterruptedException e) {
e.printStackTrace();
}
task2.start(); // Starts task2 after task1 finishes
}
}
Summary
sleep(): Temporarily halts the thread.
yield(): Suggests the thread scheduler to give up the current CPU time slice.
wait()/notify(): Used for inter-thread communication, particularly in producer-consumer scenarios.
join(): Ensures one thread completes before another continues.
These methods help manage thread execution effectively in Java applications.
// Functional Interface
// Method Reference
// Constructor Reference
// Default and Static Method in Functional Interface by developer written
// LocalDate, LocalDateTime
// Collection Framework optimized
// CompletableFuture introduced to overcome the limitation of Future
// stream API to work on collection Object
// lambda expression to work on Functional Interface
In Java, multithreading is a core feature that allows concurrent execution of two or more threads. Understanding the different thread methods—sleep(), yield(), wait(), notify(), and join()—is crucial for effective thread management. Here's a brief description of each, along with real-time examples.
1. sleep(long millis)
Description: Pauses the execution of the current thread for a specified duration (in milliseconds). It doesn't release any locks.
Example: Simulating a download process.
java code
class DownloadTask extends Thread {
public void run() {
System.out.println("Download started.");
try {
// Simulate download time
Thread.sleep(5000);
} catch (InterruptedException e) {
e.printStackTrace();
}
System.out.println("Download completed.");
}
}
public class SleepExample {
public static void main(String[] args) {
DownloadTask task = new DownloadTask();
task.start();
}
}
2. yield()
Description: Suggests to the thread scheduler that the current thread is willing to yield its current use of the CPU. This method does not guarantee that another thread will start running; it's just a hint.
Example: Threads attempting to process tasks in a round-robin fashion.
java code
class Task extends Thread {
public void run() {
for (int i = 0; i < 5; i++) {
System.out.println(Thread.currentThread().getName() + " is executing.");
Thread.yield(); // Suggest to yield the CPU
}
}
}
public class YieldExample {
public static void main(String[] args) {
Task t1 = new Task();
Task t2 = new Task();
t1.start();
t2.start();
}
}
3. wait()
Description: Causes the current thread to wait until another thread invokes notify() or notifyAll() on the same object. It releases the lock on the object.
Example: A producer-consumer scenario.
java code
class SharedResource {
private int data;
private boolean available = false;
public synchronized int consume() throws InterruptedException {
while (!available) {
wait(); // Wait until data is available
}
available = false;
notify(); // Notify producer
return data;
}
public synchronized void produce(int value) throws InterruptedException {
while (available) {
wait(); // Wait until data is consumed
}
data = value;
available = true;
notify(); // Notify consumer
}
}
class Producer extends Thread {
SharedResource resource;
Producer(SharedResource resource) {
this.resource = resource;
}
public void run() {
for (int i = 0; i < 5; i++) {
try {
resource.produce(i);
System.out.println("Produced: " + i);
} catch (InterruptedException e) {
e.printStackTrace();
}
}
}
}
class Consumer extends Thread {
SharedResource resource;
Consumer(SharedResource resource) {
this.resource = resource;
}
public void run() {
for (int i = 0; i < 5; i++) {
try {
int value = resource.consume();
System.out.println("Consumed: " + value);
} catch (InterruptedException e) {
e.printStackTrace();
}
}
}
}
public class WaitNotifyExample {
public static void main(String[] args) {
SharedResource resource = new SharedResource();
new Producer(resource).start();
new Consumer(resource).start();
}
}
4.notify() and notifyAll()
Description: Wakes up a single thread (or all waiting threads, if notifyAll() is called) that is waiting on the object's monitor.
Example: This is already demonstrated in the producer-consumer scenario above.
5. join()
Description: Waits for a thread to die. When one thread calls join() on another, it blocks until that thread terminates.
Example: Ensuring one thread completes before proceeding in another thread.
java code
class TaskWithJoin extends Thread {
public void run() {
for (int i = 1; i <= 3; i++) {
System.out.println(Thread.currentThread().getName() + " executing task " + i);
try {
Thread.sleep(1000);
} catch (InterruptedException e) {
e.printStackTrace();
}
}
}
}
public class JoinExample {
public static void main(String[] args) {
TaskWithJoin task1 = new TaskWithJoin();
TaskWithJoin task2 = new TaskWithJoin();
task1.start();
try {
task1.join(); // Main thread waits for task1 to complete
} catch (InterruptedException e) {
e.printStackTrace();
}
task2.start(); // Starts task2 after task1 finishes
}
}
Summary
sleep(): Temporarily halts the thread.
yield(): Suggests the thread scheduler to give up the current CPU time slice.
wait()/notify(): Used for inter-thread communication, particularly in producer-consumer scenarios.
join(): Ensures one thread completes before another continues.
These methods help manage thread execution effectively in Java applications.
describe by real time about java Thread program with these methods sleep(), yield(), wait(), notify(), and join()
Java provides a multi-threading mechanism to allow concurrent execution of multiple tasks. Here's a real-time explanation of Java threads focusing on the methods you mentioned:
1.sleep()
• Purpose: Causes the current thread to pause execution for a specified time, giving other threads a chance to execute.
• Usage in real-time: Suppose you are creating a program to simulate a clock. Every second, the thread can sleep for 1000 milliseconds (sleep(1000)) to wait before updating the time again.
• Example:
java code
public class SleepExample extends Thread {
public void run() {
for (int i = 1; i <= 5; i++) {
try {
Thread.sleep(1000); // Thread sleeps for 1 second
} catch (InterruptedException e) {
System.out.println(e);
}
System.out.println(i);
}
}
public static void main(String[] args) {
SleepExample t1 = new SleepExample();
t1.start(); // Starts the thread
}
}
• Real-time scenario: Used to simulate delays, such as refreshing a UI, polling a service, or implementing timed retries in APIs.
2. yield()
• Purpose: Hints to the thread scheduler that the current thread is willing to yield its execution to other threads of the same priority.
• Usage in real-time: In a CPU-bound task (e.g., calculating Fibonacci numbers), you may want to allow other equal-priority threads to run if they are waiting.
• Example:
java code
public class YieldExample extends Thread {
public void run() {
for (int i = 0; i < 5; i++) {
System.out.println(Thread.currentThread().getName() + " - " + i);
Thread.yield(); // Suggests yielding the CPU to other threads
}
}
public static void main(String[] args) {
YieldExample t1 = new YieldExample();
YieldExample t2 = new YieldExample();
t1.start();
t2.start();
}
}
• Real-time scenario: Often used in testing multi-threaded applications or in scenarios where threads are competing for resources but need to balance their execution time.
3. wait()
• Purpose: Causes the current thread to wait until another thread invokes the notify() or notifyAll() methods on the same object.
• Usage in real-time: In a producer-consumer problem, the producer thread produces data and notifies the consumer. The consumer waits until the producer provides the necessary data.
• Example:
java code
public class WaitNotifyExample {
public static void main(String[] args) {
final Object lock = new Object();
Thread t1 = new Thread(() -> {
synchronized (lock) {
try {
System.out.println("Thread1 waiting...");
lock.wait(); // Thread waits here
} catch (InterruptedException e) {
e.printStackTrace();
}
System.out.println("Thread1 resumed");
}
});
Thread t2 = new Thread(() -> {
synchronized (lock) {
System.out.println("Thread2 notifying...");
lock.notify(); // Notify waiting threads
}
});
t1.start();
try { Thread.sleep(1000); } catch (InterruptedException e) { }
t2.start();
}
}
• Real-time scenario: Used in event-driven applications where a thread waits for an event (data availability) before proceeding.
4. notify()
• Purpose: Wakes up a single thread that is waiting on the object's monitor (if any), which has previously invoked wait().
• Usage in real-time: Suppose you are writing a download manager. Once the download thread finishes downloading, it can notify a processing thread waiting for the file to be available.
• Example: (Same as in the wait() example)
• Real-time scenario: Used to notify or signal another thread to resume its execution after a resource becomes available or a condition is met.
5. join()
• Purpose: Makes the calling thread wait until the thread on which join() was called finishes its execution.
• Usage in real-time: Imagine you have several threads that perform various initialization tasks in an application, but you want the main thread to wait for all these initialization tasks to complete before continuing.
• Example:
java code
public class JoinExample extends Thread {
public void run() {
for (int i = 1; i <= 3; i++) {
try {
Thread.sleep(500); // Simulate work
} catch (InterruptedException e) {
System.out.println(e);
}
System.out.println(Thread.currentThread().getName() + " - " + i);
}
}
public static void main(String[] args) {
JoinExample t1 = new JoinExample();
JoinExample t2 = new JoinExample();
t1.start();
t2.start();
try {
t1.join(); // Wait for t1 to finish
t2.join(); // Wait for t2 to finish
} catch (InterruptedException e) {
System.out.println(e);
}
System.out.println("All threads have finished.");
}
}
• Real-time scenario: Used in applications where certain tasks need to be completed before proceeding further, such as a main program waiting for background tasks like logging, downloading, or processing.
Summary Table:
Method Effect Real-Time Use Case
sleep() Pauses the current thread for a specific amount of time Simulating delays (e.g., refreshing UI every second)
yield() Hints to the scheduler that the thread is willing to yield to other threads of the same priority Balancing CPU usage among threads
wait() Causes a thread to wait until another thread invokes notify() or notifyAll() Producer-consumer scenarios (waiting for a resource to become available)
notify() Wakes up a single thread waiting on the object's monitor Signaling when a resource becomes available or an event occurs
join() Makes the calling thread wait for another thread to finish execution Ensuring background tasks complete before proceeding in the main thread
These methods are essential in designing multi-threaded Java programs, helping in synchronization and controlled execution.
describe by real time about java Thread producer consumer program with these methods sleep(), yield(), wait(), notify(), and join()
In a Producer-Consumer problem, two types of threads work together: the producer thread generates data and adds it to a shared resource (typically a queue or buffer), while the consumer thread retrieves and processes this data. Proper synchronization is necessary to ensure that producers and consumers don’t conflict over shared resources and that consumers don't consume from an empty buffer while producers don’t produce into a full buffer.
Let's incorporate the methods sleep(), yield(), wait(), notify(), and join() into a Producer-Consumer program example.
Key Points:
• Producer will generate items and place them into a buffer (represented as a List or Queue).
• Consumer will take items from the buffer and process them.
• Both threads will coordinate using wait() and notify() to avoid accessing the buffer when it’s either empty (for consumers) or full (for producers).
• sleep() can be used by either thread to simulate the time taken to produce or consume items.
• yield() can be used to allow other threads of equal priority a chance to execute.
• join() ensures the main thread waits until both producer and consumer threads have completed.
Example of Producer-Consumer Using the Methods
java code
import java.util.LinkedList;
import java.util.Queue;
class ProducerConsumerExample {
// Shared buffer between producer and consumer
private final Queue<Integer> buffer = new LinkedList<>();
private final int BUFFER_SIZE = 5;
// Producer thread
class Producer extends Thread {
@Override
public void run() {
int item = 0;
while (true) {
synchronized (buffer) {
// Wait if the buffer is full
while (buffer.size() == BUFFER_SIZE) {
try {
System.out.println("Buffer is full, producer waiting...");
buffer.wait(); // Producer waits if buffer is full
} catch (InterruptedException e) {
e.printStackTrace();
}
}
// Produce an item
item++;
buffer.add(item);
System.out.println("Produced: " + item);
// Notify the consumer that there is something in the buffer
buffer.notify();
// Simulate some time taken to produce
try {
Thread.sleep(1000); // Producer sleeps to simulate work
} catch (InterruptedException e) {
e.printStackTrace();
}
}
Thread.yield(); // Give other threads a chance to execute
}
}
}
// Consumer thread
class Consumer extends Thread {
@Override
public void run() {
while (true) {
synchronized (buffer) {
// Wait if the buffer is empty
while (buffer.isEmpty()) {
try {
System.out.println("Buffer is empty, consumer waiting...");
buffer.wait(); // Consumer waits if buffer is empty
} catch (InterruptedException e) {
e.printStackTrace();
}
}
// Consume an item
int item = buffer.poll();
System.out.println("Consumed: " + item);
// Notify the producer that there is space in the buffer
buffer.notify();
// Simulate some time taken to consume
try {
Thread.sleep(500); // Consumer sleeps to simulate work
} catch (InterruptedException e) {
e.printStackTrace();
}
}
Thread.yield(); // Allow other threads to execute
}
}
}
public static void main(String[] args) throws InterruptedException {
ProducerConsumerExample pc = new ProducerConsumerExample();
// Creating producer and consumer threads
Producer producer = pc.new Producer();
Consumer consumer = pc.new Consumer();
// Starting producer and consumer threads
producer.start();
consumer.start();
// Main thread waits for both producer and consumer to finish
producer.join();
consumer.join();
}
}
Real-time Explanation of How Each Method Works in this Program:
1. sleep():
o Both producer and consumer use sleep() to simulate the time taken to produce and consume items.
o For example, the producer sleeps for 1000 milliseconds after producing an item, and the consumer sleeps for 500 milliseconds after consuming one.
o Real-time use: This simulates real-world scenarios where producing or consuming an item takes time, like saving data to a database or reading from a file.
2. yield():
o After every cycle of producing or consuming, the thread calls Thread.yield() to suggest that other threads with the same priority can take over. This prevents a single thread from hogging the CPU.
o Real-time use: In a highly concurrent system where multiple producers and consumers are running, yield() ensures balanced execution among threads.
3. wait():
o When the buffer is full, the producer calls wait() to release the lock and wait until the buffer has space. Similarly, when the buffer is empty, the consumer calls wait() until the producer adds more items.
o Real-time use: This avoids busy-waiting. The producer doesn’t keep trying to add items to a full buffer, and the consumer doesn’t keep trying to consume from an empty buffer, saving CPU cycles.
4. notify():
o When the producer adds an item to the buffer, it calls notify() to wake up the consumer if it’s waiting on the buffer. Similarly, when the consumer removes an item, it calls notify() to wake up the producer if it's waiting.
o Real-time use: This ensures that both the producer and consumer are in sync, signaling each other when the shared resource (buffer) is available.
5. join():
o In the main() method, the main thread waits for both the producer and consumer to finish by calling join() on both threads. This ensures that the program doesn’t terminate until both threads are done working.
o Real-time use: This can be used in scenarios where the main program needs to wait for background tasks (like producers and consumers) to complete before shutting down or proceeding to the next task.
Output Example:
vbnet
Copy code
Produced: 1
Buffer is empty, consumer waiting...
Consumed: 1
Produced: 2
Consumed: 2
Produced: 3
Buffer is full, producer waiting...
Consumed: 3
Produced: 4
...
Real-World Application:
In an API-based system, producers could represent clients sending requests (such as adding tasks to a queue), and consumers could represent workers processing those requests (such as sending a response back to the client). The wait(), notify(), and join() methods ensure that clients don’t overload the server with too many tasks, while workers process requests efficiently.
describe real time thread program in springboot eCommerce project
In a Spring Boot eCommerce project, a real-time thread program can be implemented to handle concurrent tasks, such as processing orders, sending notifications, or updating inventory levels. Here's a high-level overview of how to design and implement a real-time thread program in a Spring Boot eCommerce project:
Design Considerations
1. Thread Pool: Create a thread pool to manage a fixed number of threads that can execute tasks concurrently. This ensures efficient use of system resources and prevents thread creation overhead.
2. Task Queue: Design a task queue to hold tasks that need to be executed by the thread pool. This queue can be implemented using a data structure like a BlockingQueue or a message broker like RabbitMQ.
3. Task Execution: Define a task execution mechanism that retrieves tasks from the queue and assigns them to available threads in the pool.
4. Task Types: Identify the types of tasks that need to be executed in real-time, such as order processing, notification sending, or inventory updates.
Implementation
1. Create a Thread Pool: Use the ThreadPoolTaskExecutor class from Spring Framework to create a thread pool with a fixed number of threads.
java code
@Bean
public ThreadPoolTaskExecutor threadPoolTaskExecutor() {
ThreadPoolTaskExecutor executor = new ThreadPoolTaskExecutor();
executor.setCorePoolSize(5); // initial number of threads
executor.setMaxPoolSize(10); // maximum number of threads
executor.setQueueCapacity(20); // task queue capacity
return executor;
}
2. Define a Task Queue: Create a task queue using a BlockingQueue or a message broker like RabbitMQ. For simplicity, let's use a BlockingQueue.
java code
@Bean
public BlockingQueue<Task> taskQueue() {
return new LinkedBlockingQueue<>();
}
3. Implement Task Execution: Create a task execution mechanism that retrieves tasks from the queue and assigns them to available threads in the pool. You can use a TaskExecutor interface to define the task execution logic.
java
public interface TaskExecutor {
void execute(Task task);
}
public class RealTimeTaskExecutor implements TaskExecutor {
@Autowired
private ThreadPoolTaskExecutor threadPoolTaskExecutor;
@Override
public void execute(Task task) {
threadPoolTaskExecutor.execute(() -> {
// execute the task
task.execute();
});
}
}
4. Define Task Types: Identify the types of tasks that need to be executed in real-time and create corresponding task classes. For example, you can create an OrderProcessingTask class that processes orders in real-time.
java code
public class OrderProcessingTask implements Task {
private Order order;
public OrderProcessingTask(Order order) {
this.order = order;
}
@Override
public void execute() {
// process the order
// ...
}
}
5. Integrate with eCommerce Project: Integrate the real-time thread program with your eCommerce project by injecting the RealTimeTaskExecutor instance into the relevant components. For example, you can inject it into a service class that handles order processing.
java code
@Service
public class OrderService {
@Autowired
private RealTimeTaskExecutor realTimeTaskExecutor;
public void processOrder(Order order) {
// create an OrderProcessingTask instance
OrderProcessingTask task = new OrderProcessingTask(order);
// execute the task using the real-time task executor
realTimeTaskExecutor.execute(task);
}
}
By following these steps, you can design and implement a real-time thread program in a Spring Boot eCommerce project to handle concurrent tasks efficiently.
#ArrayList and LinkedList both implement the List interface and maintain insertion order. Both are non-synchronized classes.
However, there are many differences between the ArrayList and LinkedList classes that are given below.
ArrayList
LinkedList
1) ArrayList internally uses a dynamic array to store the elements.
LinkedList internally uses a doubly linked list to store the elements.
2) Manipulation with ArrayList is slow because it internally uses an array. If any element is removed from the array, all the other elements are shifted in memory.
Manipulation with LinkedList is faster than ArrayList because it uses a doubly linked list, so no bit shifting is required in memory.
3) An ArrayList class can act as a list only because it implements List only.
LinkedList class can act as a list and queue both because it implements List and Deque interfaces.
4) ArrayList is better for storing and accessing data.
LinkedList is better for manipulating data.
5) The memory location for the elements of an ArrayList is contiguous.
The location for the elements of a linked list is not contagious.
6) Generally, when an ArrayList is initialized, a default capacity of 10 is assigned to the ArrayList.
There is no case of default capacity in a LinkedList. In LinkedList, an empty list is created when a LinkedList is initialized.
7) To be precise, an ArrayList is a resizable array.
LinkedList implements the doubly linked list of the list interface.
#LinkedList vs ArrayList in Java
All the differences between LinkedList and ArrayList have their root in the difference between Array and LinkedList data structure. If you are familiar with Array and LinkedList data structure you will most likely derive the following differences between them:
1. Since Array is an index based data-structure searching or getting element from Array with index is pretty fast. Array provides O(1) performance for get(index) method but remove is costly in ArrayList as you need to rearrange all elements.
On the Other hand, LinkedList doesn't provide Random or index-based access and you need to iterate over the linked list to retrieve any element which is of order O(n).
2. Insertions are easy and fast in LinkedList as compared to ArrayList because there is no risk of resizing the array and copying content to the new array if the array gets full which makes adding into ArrayList of O(n) in the worst case while adding is O(1) operation in LinkedList in Java. ArrayList also needs to update its index if you insert something anywhere except at the end of the array.
3. Removal is like insertions better in LinkedList than ArrayList.
4. LinkedList has more memory overhead than ArrayList because in ArrayList each index only holds an actual object (data) but in the case of LinkedList, each node holds both data and address of the next and previous node.
When to use LinkedList and ArrayList in Java?
As I said LinkedList is not as popular as ArrayList but still, there are situations where a LinkedList is a better choice than ArrayList in Java. Use LinkedList in Java if:
1. Your application can live without Random access. Because if you need nth element in LinkedList you need to first traverse up to nth element O(n) and then you get data from that node.
2. Your application is more insertion and deletion driver and you insert or remove more than retrieval. Since insertion or removal doesn't involve resizing it's much faster than ArrayList.
And, if you need to know more diffrences betwen ArrayList and LinkedList in Java then here is a nice talbe which you can refer:
Difference between LinkedList vs ArrayList in Java? Answer
Difference between LinkedList and ArrayList in JavaThat’s all on the difference between ArrayList and LinkedList in Java. Use ArrayList in Java for all their situation where you need non-synchronized index-based access. ArrayList is fast and easy to use, just try to minimize array resizing by constructing ArrayList with a proper initial size.
3. What is the difference between deadlock and starvation in the context of Operating Systems?
Deadlock - When each process possesses a resource and waits for another process to retain a resource, a deadlock ensues. Mutual Exclusion, Hold and Wait, No Preemption, and Circular Wait are all necessary circumstances for the deadlock to occur. No process that is holding one resource while waiting for another is performed in this scenario.
Starvation - When high priority processes continue to run while low priority processes are stalled for an indeterminate time, this is known as starvation. A continual stream of higher-priority processes in a densely loaded computer system can prevent a low-priority operation from ever receiving the CPU. When resources are scarce, high-priority processes consume them continuously. Ageing can help to tackle the problem of starvation. The importance of long waiting processes is increasingly raised as processes age.
The following table lists the differences between deadlock and starvation:
Deadlock Starvation
In the case of deadlock, none of the processes is executed since they are waiting for each other to finish. In case of starvation, high-priority processes continue to run, whereas low-priority activities are halted.
In this case, processes are preventing resources from being used. In this case, high-priority processes consume resources constantly.
The necessary conditions for deadlock are:
No Preemption
Hold and Wait
Circular Wait
Mutual Exclusion
The necessary condition for starvation includes that the process must be having low priority and there must be other high priority resources that are continuously occupying the resources.
It can be avoided by avoiding the conditions that lead to deadlock. Starvation can be avoided with the concept of ageing.
ConcurrentHashMap in Java is designed for efficient concurrent access, allowing multiple threads to read and update the map simultaneously without compromising data integrity. Here's how it works internally: Structure: Segments: Internally, ConcurrentHashMap is divided into segments (by default 16). Each segment acts like a separate hash table, allowing different threads to work on different segments concurrently. This reduces contention and improves performance. Locks: Each segment has its own lock. When a thread wants to modify a segment, it acquires the lock for that segment only, allowing other threads to access other segments without waiting. Hashing: Like HashMap, ConcurrentHashMap uses a hash function to map keys to buckets within a segment. Operations: Read Operations: Reads (e.g., get) are typically lock-free. Threads can read values from the map without acquiring any locks, enabling high concurrency for read-heavy workloads. Write Operations: Writes (e.g., put, remove) require locking the corresponding segment. This ensures that only one thread can modify a specific segment at a time, preventing data corruption. Iteration: ConcurrentHashMap provides fail-safe iterators, which means that they do not throw ConcurrentModificationException if the map is modified during iteration. Instead, they iterate over a snapshot of the map's state at the time the iterator was created. Fail-Safe Nature: ConcurrentHashMap's fail-safe iterators achieve their safety by operating on a copy of the map's data, not the live data itself. This means that modifications made to the map after the iterator is created will not be reflected in the iterator. However, it's important to note that the snapshot might not be entirely consistent if multiple threads are modifying the map concurrently. Benefits: Thread-Safety: ConcurrentHashMap is thread-safe, eliminating the need for external synchronization mechanisms when accessing the map from multiple threads. Performance: By using fine-grained locking at the segment level, ConcurrentHashMap allows for high concurrency, making it significantly faster than using a synchronized HashMap in multi-threaded environments.
In Spring Boot, backpressure can be applied to handle situations where data production rate exceeds the consumption rate, especially in reactive systems. Here’s an example of applying backpressure using Project Reactor in a Spring Boot application. We'll use Flux with a Backpressure strategy to control the flow of data.
Scenario Let's assume we have a data stream of integers being produced at a high rate, and we need to control the consumption rate using backpressure to avoid overwhelming the system.
Step-by-Step Example
- Add Dependencies Make sure to include the spring-boot-starter-webflux dependency in your pom.xml:
xml Copy code org.springframework.boot spring-boot-starter-webflux 2. Controller with Backpressure Example Create a ReactiveController that produces a high-rate stream of data, with backpressure implemented.
java Copy code import org.springframework.web.bind.annotation.GetMapping; import org.springframework.web.bind.annotation.RestController; import reactor.core.publisher.Flux; import reactor.core.scheduler.Schedulers;
import java.time.Duration;
@RestController public class ReactiveController {
@GetMapping("/stream")
public Flux<Integer> streamData() {
// Generate an infinite stream of numbers from 1 upwards
return Flux.range(1, 1000)
.delayElements(Duration.ofMillis(10)) // Simulate production rate
.doOnNext(i -> System.out.println("Produced: " + i))
.onBackpressureBuffer(50, // Buffer size before dropping items
i -> System.out.println("Dropping item: " + i)) // Drop handler
.publishOn(Schedulers.boundedElastic(), 5) // Limit consumer rate
.doOnNext(i -> System.out.println("Consumed: " + i));
}
} Explanation Flux.range(1, 1000).delayElements(Duration.ofMillis(10)) produces an integer stream from 1 to 1000 with a delay between items to simulate production rate. .onBackpressureBuffer(50, i -> System.out.println("Dropping item: " + i)) adds a buffer of 50 items. If the buffer is full, new items will be dropped. .publishOn(Schedulers.boundedElastic(), 5) uses the bounded elastic scheduler and limits the consumption rate to 5 items at a time. doOnNext logs production and consumption rates. Testing the Backpressure When you hit the endpoint (/stream), you should see the output where:
Produced items are logged continuously at a faster rate. Consumption of items is regulated by the backpressure limit, showing how some items are dropped if the buffer exceeds capacity. Additional Strategies onBackpressureDrop(): Drops items immediately if they can’t be processed in time. onBackpressureLatest(): Keeps the latest item in the buffer, dropping older ones. onBackpressureError(): Signals an error if backpressure can't be applied effectively. This example should give a basic understanding of handling backpressure in a Spring Boot reactive application with Project Reactor.
You said: describe completablefutire by example java8 ChatGPT said: ChatGPT In Java 8, CompletableFuture is part of the java.util.concurrent package and provides a powerful way to handle asynchronous programming. It allows you to define a pipeline of tasks to be executed asynchronously, either in parallel or in sequence, while also providing support for error handling and transformations.
Here’s a basic example to illustrate the usage of CompletableFuture:
Scenario Suppose we have two tasks:
Fetch a user's information from a database. Fetch the user’s credit score based on their ID. We’ll use CompletableFuture to perform both tasks asynchronously and then combine the results.
Example Code java Copy code import java.util.concurrent.CompletableFuture; import java.util.concurrent.ExecutionException;
public class CompletableFutureExample {
public static void main(String[] args) throws ExecutionException, InterruptedException {
// Step 1: Fetch user information asynchronously
CompletableFuture<String> userInfoFuture = CompletableFuture.supplyAsync(() -> {
System.out.println("Fetching user info...");
delay(1); // Simulate delay
return "User123"; // Example user ID
});
// Step 2: Fetch credit score asynchronously based on user ID
CompletableFuture<Integer> creditScoreFuture = userInfoFuture.thenApplyAsync(userId -> {
System.out.println("Fetching credit score for user: " + userId);
delay(2); // Simulate delay
return 700; // Example credit score
});
// Combine results and print
CompletableFuture<Void> combinedFuture = creditScoreFuture.thenAccept(score -> {
System.out.println("User's credit score is: " + score);
});
// Wait for all tasks to complete
combinedFuture.get();
}
// Helper method to simulate a delay
private static void delay(int seconds) {
try {
Thread.sleep(seconds * 1000);
} catch (InterruptedException e) {
throw new IllegalStateException(e);
}
}
} Explanation supplyAsync: CompletableFuture.supplyAsync starts an asynchronous task that fetches user information. It returns a CompletableFuture which contains the user ID.
thenApplyAsync: After fetching the user ID, we use thenApplyAsync to start another asynchronous task to fetch the credit score based on the user ID. It takes the result from userInfoFuture and uses it to fetch the credit score.
thenAccept: Finally, thenAccept is used to consume the result of creditScoreFuture. Here, we print the credit score after the asynchronous operations are complete.
get(): Calling get() on combinedFuture ensures the main thread waits until the entire pipeline completes.
Output If you run this example, you’ll see something like this:
plaintext Copy code Fetching user info... Fetching credit score for user: User123 User's credit score is: 700 Additional Notes Exception Handling: Use exceptionally or handle to deal with exceptions in CompletableFuture. Combining Futures: CompletableFuture also supports combining multiple futures, like thenCombine for results from multiple asynchronous tasks. This example demonstrates CompletableFuture basics, allowing asynchronous, non-blocking code with easy chaining and handling of results.
You said: describe completablefuture with executorsercive ChatGPT said: ChatGPT CompletableFuture in Java can be combined with ExecutorService to provide more control over the threads executing the asynchronous tasks. By default, CompletableFuture uses the ForkJoinPool.commonPool() for asynchronous tasks, but with an ExecutorService, we can specify our own thread pool to better control the execution environment, resources, and behavior of the asynchronous tasks.
Here's a detailed example:
Scenario Let’s say we have two tasks:
Fetch product details from a database. Fetch the product's pricing information based on the product ID. Both tasks need to run asynchronously, and we want to control the threads executing them using a custom ExecutorService.
Example Code with ExecutorService java Copy code import java.util.concurrent.CompletableFuture; import java.util.concurrent.ExecutionException; import java.util.concurrent.ExecutorService; import java.util.concurrent.Executors;
public class CompletableFutureWithExecutorServiceExample {
public static void main(String[] args) throws ExecutionException, InterruptedException {
// Step 1: Create a custom ExecutorService
ExecutorService executorService = Executors.newFixedThreadPool(2);
try {
// Step 2: Fetch product details asynchronously with ExecutorService
CompletableFuture<String> productDetailsFuture = CompletableFuture.supplyAsync(() -> {
System.out.println("Fetching product details... [" + Thread.currentThread().getName() + "]");
delay(1); // Simulate delay
return "Product123"; // Example product ID
}, executorService);
// Step 3: Fetch product pricing asynchronously with ExecutorService, after product ID is retrieved
CompletableFuture<Double> productPriceFuture = productDetailsFuture.thenApplyAsync(productId -> {
System.out.println("Fetching product price for: " + productId + " [" + Thread.currentThread().getName() + "]");
delay(2); // Simulate delay
return 199.99; // Example price
}, executorService);
// Step 4: Combine results and print the output
CompletableFuture<Void> combinedFuture = productPriceFuture.thenAccept(price -> {
System.out.println("Product price is: $" + price);
});
// Wait for all tasks to complete
combinedFuture.get();
} finally {
// Step 5: Shut down the ExecutorService
executorService.shutdown();
}
}
// Helper method to simulate delay
private static void delay(int seconds) {
try {
Thread.sleep(seconds * 1000);
} catch (InterruptedException e) {
throw new IllegalStateException(e);
}
}
} Explanation Custom ExecutorService: We create a FixedThreadPool with 2 threads. This executor will control the thread execution of our asynchronous tasks.
supplyAsync with ExecutorService: The supplyAsync method is passed the executorService as the second argument, which controls where this task will be executed. Here, we simulate fetching product details asynchronously.
thenApplyAsync with ExecutorService: After fetching the product details, thenApplyAsync performs a second task (fetching the product price). By providing the executorService, we ensure this step also runs within the custom executor, giving us consistent control over the thread execution.
thenAccept: Once both tasks complete, we handle the final result with thenAccept, printing the product price.
Shutdown the ExecutorService: It’s important to call executorService.shutdown() to release resources once all tasks are completed.
Output If you run this example, you’ll see output similar to:
plaintext Copy code Fetching product details... [pool-1-thread-1] Fetching product price for: Product123 [pool-1-thread-2] Product price is: $199.99 Benefits of Using ExecutorService with CompletableFuture Control over Threads: With ExecutorService, we decide on the number of threads and control the underlying thread pool's lifecycle. Improved Resource Management: By using a thread pool with limited threads, we can manage system resources better, especially if we’re executing many asynchronous tasks. Thread Reuse: Using a thread pool avoids the overhead of creating and destroying threads repeatedly, making the application more efficient. This approach is particularly helpful in real-world applications where resource control is essential for optimal performance and system stability.
You said: CompletableFuture with exception handling ChatGPT said: ChatGPT CompletableFuture provides powerful exception handling mechanisms to handle errors that may occur during asynchronous operations. You can use exceptionally, handle, or whenComplete to manage and recover from exceptions gracefully.
Key Exception Handling Methods exceptionally: Allows you to handle exceptions and provide a default value in case of an error. handle: Allows you to handle both the result and the exception, giving you more flexibility. whenComplete: Allows you to inspect the result or exception but doesn’t change the final outcome. Example Code with CompletableFuture and Exception Handling Let’s assume we have an asynchronous task to fetch user details by ID, and there's a chance of an exception (e.g., if the user ID is invalid).
java Copy code import java.util.concurrent.CompletableFuture; import java.util.concurrent.ExecutionException;
public class CompletableFutureExceptionHandlingExample {
public static void main(String[] args) {
// Example user ID (negative ID will simulate an error scenario)
int userId = -1;
// Step 1: Start an asynchronous task to fetch user details
CompletableFuture<String> userDetailsFuture = CompletableFuture.supplyAsync(() -> {
if (userId < 0) {
throw new IllegalArgumentException("User ID cannot be negative");
}
return "User" + userId;
});
// Step 2: Handle exception using `exceptionally`
CompletableFuture<String> handledExceptionally = userDetailsFuture.exceptionally(ex -> {
System.out.println("Exception occurred: " + ex.getMessage());
return "Default User"; // Fallback value
});
// Step 3: Handle exception and result using `handle`
CompletableFuture<String> handledWithHandle = userDetailsFuture.handle((result, ex) -> {
if (ex != null) {
System.out.println("Handling error with handle: " + ex.getMessage());
return "Handled User";
}
return result;
});
// Step 4: Inspect the result or exception using `whenComplete`
userDetailsFuture.whenComplete((result, ex) -> {
if (ex != null) {
System.out.println("whenComplete: An error occurred - " + ex.getMessage());
} else {
System.out.println("whenComplete: Successfully fetched - " + result);
}
});
try {
// Print the outcomes
System.out.println("Result with exceptionally: " + handledExceptionally.get());
System.out.println("Result with handle: " + handledWithHandle.get());
} catch (InterruptedException | ExecutionException e) {
e.printStackTrace();
}
}
} Explanation exceptionally:
exceptionally is called if an exception occurs. It provides a fallback value ("Default User") if the user ID is invalid. handle:
handle provides access to both the result and the exception. If an exception occurs, we handle it by returning a different value ("Handled User"). Otherwise, we return the successful result. whenComplete:
whenComplete allows inspecting the result or exception but doesn’t modify the outcome of the CompletableFuture. Here, we log the result or exception without affecting the final result. Output If you run the code with userId = -1, you’ll see:
plaintext Copy code Exception occurred: User ID cannot be negative Handling error with handle: User ID cannot be negative whenComplete: An error occurred - User ID cannot be negative Result with exceptionally: Default User Result with handle: Handled User If you use a valid userId, say userId = 10, you’ll get:
plaintext Copy code whenComplete: Successfully fetched - User10 Result with exceptionally: User10 Result with handle: User10 Summary of Exception Handling Techniques Use exceptionally to handle exceptions and provide a default or fallback value. Use handle for flexible handling, as it can process both result and exception. Use whenComplete to inspect the result or exception without changing the outcome. This setup allows robust error management in asynchronous pipelines, making CompletableFuture a strong choice for complex asynchronous workflows.
You said: name of all Executor pool provider classes with usage scenario ChatGPT said: ChatGPT Java provides several Executor and ExecutorService implementations for different scenarios, all of which manage thread pools to efficiently execute concurrent tasks. Here’s a list of the primary executor pool provider classes and when to use each.
- SingleThreadExecutor Class: Executors.newSingleThreadExecutor() Usage Scenario: Use when tasks need to be executed sequentially, in a single background thread, ensuring that tasks are processed one after another without concurrency. Example: java Copy code ExecutorService executor = Executors.newSingleThreadExecutor(); executor.submit(() -> System.out.println("Task executed by a single thread"));
- FixedThreadPool Class: Executors.newFixedThreadPool(int nThreads) Usage Scenario: Best when the number of concurrent tasks is known and does not change, such as a server handling a fixed number of clients. Limits the number of threads to nThreads, reusing them for different tasks. Example: java Copy code ExecutorService executor = Executors.newFixedThreadPool(4); for (int i = 0; i < 10; i++) { executor.submit(() -> System.out.println("Task executed by a fixed thread pool")); }
- CachedThreadPool Class: Executors.newCachedThreadPool() Usage Scenario: Suitable for a large number of short-lived asynchronous tasks where threads may sit idle often, such as lightweight background tasks or handling HTTP requests. The pool grows as needed but reuses existing threads if possible. Example: java Copy code ExecutorService executor = Executors.newCachedThreadPool(); for (int i = 0; i < 10; i++) { executor.submit(() -> System.out.println("Task executed by a cached thread pool")); }
- ScheduledThreadPool Class: Executors.newScheduledThreadPool(int corePoolSize) Usage Scenario: Ideal for periodic or delayed task execution, like scheduled maintenance tasks or repeated checks. Threads are reused across scheduled tasks. Example: java Copy code ScheduledExecutorService scheduler = Executors.newScheduledThreadPool(2); scheduler.scheduleAtFixedRate(() -> System.out.println("Scheduled task executed"), 0, 10, TimeUnit.SECONDS);
- WorkStealingPool (Java 8 and above) Class: Executors.newWorkStealingPool(int parallelism) Usage Scenario: Best suited for large numbers of small, asynchronous tasks that can benefit from load balancing across multiple cores, such as large parallel computations. Threads steal tasks from each other to maintain high utilization. Example: java Copy code ExecutorService executor = Executors.newWorkStealingPool(); for (int i = 0; i < 10; i++) { executor.submit(() -> System.out.println("Task executed by a work-stealing pool")); }
- ForkJoinPool Class: new ForkJoinPool(int parallelism) Usage Scenario: Optimized for tasks that can be recursively split into smaller sub-tasks (divide and conquer approach), like processing large datasets or recursive algorithms. Uses a work-stealing algorithm to maximize efficiency. Example: java Copy code ForkJoinPool forkJoinPool = new ForkJoinPool(4); forkJoinPool.submit(() -> System.out.println("Task executed by ForkJoinPool"));
- SingleThreadScheduledExecutor Class: Executors.newSingleThreadScheduledExecutor() Usage Scenario: Useful when tasks need to be scheduled on a single thread, but also require scheduling at fixed intervals or with delays. For example, periodic maintenance tasks in a single-threaded environment. Example: java Copy code ScheduledExecutorService singleScheduler = Executors.newSingleThreadScheduledExecutor(); singleScheduler.schedule(() -> System.out.println("Single-thread scheduled task"), 5, TimeUnit.SECONDS);
- VirtualThreadPerTaskExecutor (Java 19 and above - Preview Feature) Class: Executors.newVirtualThreadPerTaskExecutor() Usage Scenario: Optimized for massive concurrency by creating lightweight virtual threads instead of OS threads. Suitable for high-throughput applications like handling a large number of concurrent user requests or microservices, without being limited by the number of OS threads. Example: java Copy code ExecutorService executor = Executors.newVirtualThreadPerTaskExecutor(); for (int i = 0; i < 10; i++) { executor.submit(() -> System.out.println("Task executed by a virtual thread pool")); } Summary Table Executor Pool Class Use Case SingleThreadExecutor newSingleThreadExecutor() Sequential task execution, no concurrency. FixedThreadPool newFixedThreadPool(int n) Fixed number of threads for predictable task loads. CachedThreadPool newCachedThreadPool() Short-lived tasks, dynamically growing pool. ScheduledThreadPool newScheduledThreadPool(int n) Delayed or periodic task execution. WorkStealingPool newWorkStealingPool(int n) Large, asynchronous, parallelizable tasks. ForkJoinPool new ForkJoinPool(int n) Divide-and-conquer recursive tasks. SingleThreadScheduledExecutor newSingleThreadScheduledExecutor() Single-threaded, periodic execution. VirtualThreadPerTaskExecutor (Java 19+) newVirtualThreadPerTaskExecutor() Massive concurrency with lightweight threads. Each executor type provides a unique set of capabilities for different workload patterns, making it possible to efficiently handle both lightweight and resource-intensive tasks.