Finger Tree framework and concurrent programming in the Java class library
Finger Tree framework and concurrent programming in the Java class library
introduction:
Finger Tree is an efficient data structure. It is widely used in various scenarios in the Java class library, especially in concurrent programming.This article will introduce the concept and principle of Finger Tree, and use the Java code example to illustrate its application in concurrent programming.
1. Finger Tree Overview
2. Finger Tree Principle
2. Find elements
Finger Tree supports fast searching elements by fingers.Through the finger, the tree can be divided into smaller parts to reduce the range of search.In each node, you can determine whether you need to continue searching in the left sub -tree or right child tree through the position and element position of the comparison.In this way, you can quickly locate the elements you need to query.
3. Insert and delete elements
Finger Tree supports high -efficiency insertion and delete operations.The insertion operation can maintain the balance of the tree by updating the fingers and signs and perform the necessary heavy balance operations.Delete operations can be found by finding elements to be deleted, removing it from the tree, and performing necessary heavy balance operations to maintain the balance of the tree.
Third, the application of Finger Tree in concurrent programming
1. Implementation of concurrent queue
Finger Tree can be used to achieve efficient concurrent queue.By saving the queue elements in Finger Tree, you can quickly insert and delete the operation, and maintain the order of the queue.When inserting and deleting operations, use an appropriate synchronization mechanism (lock or CAS operation) to ensure the correctness of concurrent access.
Below is a simple Java code example, demonstrating how to use Finger Tree to achieve a concurrent queue:
import java.util.concurrent.locks.Lock;
import java.util.concurrent.locks.ReentrantLock;
public class ConcurrentQueue<T> {
private FingerTree<T> tree;
private Lock lock;
public ConcurrentQueue() {
tree = FingerTree.empty();
lock = new ReentrantLock();
}
public void enqueue(T element) {
lock.lock();
try {
tree = tree.addLast(element);
} finally {
lock.unlock();
}
}
public T dequeue() {
lock.lock();
try {
if (tree.isEmpty()) {
throw new IllegalStateException("Queue is empty");
}
T element = tree.getFirst();
tree = tree.removeFirst();
return element;
} finally {
lock.unlock();
}
}
}
In the above code, the Re entranceLock is used as the synchronization mechanism to lock and unlock LOCK in the enqueue () and dequeue () methods, respectively.By calling Finger Tree's addLast () and Removefirst () methods, you can add elements to the tail of the queue and delete elements from the head of the queue.
2. Implementation of concurrent collection
In addition to the compilation queue, FINCER TREE can also be used to achieve efficient concurrency collection, such as concurrent listing or concurrent collection.By saving the set elements in Finger Tree, and using Finger Tree's insertion and deleting operations, efficient concurrency collection can be achieved.In concurrent access, an appropriate synchronization mechanism also needs to be used to ensure correctness.
in conclusion:
references:
1. Ralf Hinze, "Finger Trees: A Simple General-purpose Data Structure", Journal of Functional Programming, Vol. 16, No. 2, 2006.
2. Simon Marlow, "Parallel and Concurrent Programming in Haskell", O'Reilly Media, 2013.
