Research on the technical principles of the technical principles of the Java class library medium and high -frequency transaction (HFT) collection framework

Research on the technical principles of the technical principles of the Java class library medium and high -frequency transaction (HFT) collection framework Abstract: High -frequency trading (HFT) is a high -speed and efficient trading strategy in the financial field, which is very important for processing massive real -time data and realizing instant transactions.In the HFT system, the collection framework plays a key role and effectively manages and operates data sets.This article will explore the technical principles of implementing the high -frequency transaction set framework of the Java class library, including concurrent access, performance optimization, and data structure selection. 1. Parallel visits In the high -frequency trading system, multiple threads may read and write data sets at the same time, so concurrent access is a key point of the set framework.Java provides a variety of complications, such as ConcurrenThashMap and ConcurrenTlinkedQueue. They realize effective concurrency control based on thread security algorithms.These classes use lock mechanisms or lock -free algorithms to ensure the atomicity and visibility of multi -threaded access.In actual encoding, we need to choose a suitable concurrency collection class based on the characteristics of data access, while using an appropriate lock mechanism to ensure the consistency and concurrent performance of the data. Example code: // Create a concurrent hashmap ConcurrentMap<String, Integer> hftMap = new ConcurrentHashMap<>(); // Add data to the concurrent hashMap hftMap.put("apple", 50); hftMap.put("banana", 75); // Use the iterator to traverse and output the key value pair for (Map.Entry<String, Integer> entry : hftMap.entrySet()) { System.out.println(entry.getKey() + ": " + entry.getValue()); } Performance optimization Because the high -frequency trading system needs to process a large amount of real -time data, the performance optimization of the setting framework is also very important.We can improve performance through the following methods: 1. Data structure selection: Choosing the appropriate data structure is essential for a high -frequency trading system.For example, linkedList is more suitable than ArrayList for scenes that need to be inserted and deleted quickly. For scenarios that need to be accessed quickly and randomly, ArrayList is more suitable than LinkedList. 2. Reduce lock particle size: The lock -locking conference leads to thread disputes, thereby reducing performance.Considering the use of fine -grained locks or lock -free algorithms to reduce lock competition and improve concurrency performance. 3. Batch operation: In high -frequency trading systems, batch operations can significantly improve performance.For example, use batch insertion and batch modifications to reduce frequent access to sets. Example code: // Use ArrayList to store data List<String> hftList = new ArrayList<>(); // Batch add data hftList.addAll(Arrays.asList("apple", "banana", "cherry")); // Batch delete data hftList.removeAll(Arrays.asList("apple", "orange")); // Traversing and output data for (String item : hftList) { System.out.println(item); } 3. Data structure selection In high -frequency trading systems, the selection of data structure has a significant impact on performance and functional requirements.The following are several common collection data structures: 1. Array (Array): It is suitable for scenes that require fast and random access, but the performance of inserting and deleting operations is poor. 2. LinkedList: It is suitable for scenes that need to be inserted and deleted frequently, but the performance of random access is poor. 3. HashMap: It is suitable for scenes that need to index and find quickly, but do not guarantee the order of elements. 4. Tree: It is suitable for scenarios that require orderly access and search, but the performance of large -scale data insertion and deletion is poor. Through comprehensive consideration of data access mode and performance requirements, the appropriate data structure is selected to achieve high -frequency trading set framework. in conclusion: This article discusses the technical principles of implementing the high -frequency transaction set framework of the Java class library, including concurrent access, performance optimization, and data structure selection.In the HFT system, the set framework is the key to efficiently processing massive real -time data.Reasonable selection of technical means such as data structure, optimization concurrent access, and reducing competition in locking can improve the performance and maintenance of high -frequency trading systems. references: 1. Oracle Java Documentation - https://docs.oracle.com/en/java/javase/15/ 2. The second edition of "Java High concurrent program design" -Qian Wenxiao, Machinery Industry Press