HashMap source code analysis and optimization techniques in Jin Collections

HashMap source code analysis and optimization techniques in Jin Collections Overview: HashMap is one of the most commonly used data structures in Java, which aims to provide efficient key values and retrieval.In Jin Collections, the implementation of HashMap has been optimized to provide better performance and efficiency.This article will analyze the source code of HashMap in Jin Collections and introduce some optimization techniques to help you better understand and use HashMap. 1. Basic principles of HashMap: HashMap uses the hash table as a data storage structure, and the key is mapped to the bucket through the hash function to achieve the key value of the key value of O (1) time complexity.Jin Collections has improved some of the source code of HashMap to improve the performance of hash tables and avoid hash collision. 2. The source code analysis of the HashMap in Jin Collections: In Jin Collections, the HashMap source code has been optimized and improved.The following are some key implementation details: -The dynamic adjustment of hash table capacity: In Jin Collections, the initial capacity of HashMap defaults to 16, and the capacity will be dynamically adjusted with the number of elements.When the load factor of HashMap reaches a threshold (default 0.75), the capacity will be automatically expanded to twice the original, and the position of each element in the new capacity is re -calculated to maintain the performance of the hash table. -Link list and red and black tree optimization: In order to solve the hash collision and improve the retrieval efficiency, the HashMap in Jin Collections achieves a combination of linked lists and red and black trees.When the length of the linked list in the barrel exceeds the threshold (default 8), the linked list will be converted into red and black trees, which will improve the efficiency of retrieval in average. -The portfolio security: HashMap in Jin Collections implements a mechanism of thread security, and use locks and synchronization code blocks to ensure security access in multi -threaded environments. 3. Optimization of HashMap in Jin Collections: In addition to the source code optimization, Jin Collections also provides some optimization techniques to improve the performance and efficiency of HashMap.Here are some commonly used optimization skills: -Specify the initial capacity when initialized hashmap: When creating a HashMap instance, by specifying the initial capacity, the capacity adjustment can be avoided frequently when adding a large amount of elements to improve performance. -For frequent insertion and delete operations: Frequent insertion and deleting operations can lead to the expansion and contraction of the hash table and affect performance.If possible, try to add or delete elements at one time to reduce the number of modifications to the hash table. -The initial capacity of HashMap in advance: If the number of elements in HashMap can be estimated, the initial capacity can be set in advance to avoid the overhead of automatic capacity adjustment. -Cose the right load factor: The load factor is an important parameter that affects the performance of HashMap.According to actual needs, choose an appropriate load factor value to balance between performance and memory occupation. Example code: The following is an example code using HashMap in Jin Collections to show how to use HashMap to store and retrieve key values: import org.jincollections.collection.HashMap; public class HashMapExample { public static void main(String[] args) { // Create a HashMap instance HashMap<String, Integer> hashMap = new HashMap<>(); // Add key value pair hashMap.put("apple", 1); hashMap.put("banana", 2); hashMap.put("orange", 3); // Search key value pair int value = hashMap.get("banana"); System.out.println("The value of 'banana' is: " + value); } } Summarize: The HashMap in Jin Collections is optimized and improved through source code, providing efficient key -value pairs of storage and retrieval.This article understands the source code of Hashmap in Jin Collections, and introduces some optimization techniques to help you better understand and use HashMap.Through reasonable configuration of initial capacity, avoid frequent insertion and delete operations, the performance and efficiency of HashMap can be further improved.I hope this article will help you understand and use HashMap in Jin Collections.