Order book data is characterized by fine-grained events, strong peak bursts, dense state access, and strict time-series constraints, which dictates that its stream processing framework must simultaneously satisfy low latency, strong consistency, and high throughput. Focusing on the issue of "performance bottleneck analysis and optimization of order book event-driven stream processing frameworks," this paper, based on a review of research on stream processing systems, checkpointing protocols, elastic scheduling, order book modeling, and event stream prediction over the past three years, proposes a five-layer bottleneck analysis framework addressing market data access, event routing, state management, checkpointing, and elastic scaling. Furthermore, considering the load structure of order book event streams, a three-objective model of throughput, latency, and resources is constructed, and collaborative optimization strategies including fine-grained partitioning, hotspot isolation, asynchronous state access, layered checkpointing, and hybrid resource deployment are presented. The study argues that the core contradiction in the order book scenario is not insufficient computation of a single operator, but rather the superposition of high-frequency state read/write, out-of-order event correction, peak load propagation, and the overhead of fault tolerance mechanisms. Through comparison of literature data and mechanism analysis, it can be seen that the joint optimization of state decoupling, predictive elasticity and topology-level parameters can significantly improve end-to-end latency stability and enhance processing resilience under extreme conditions.

Wenjie Jiang. Performance Bottleneck Analysis and Optimization of an Order Book Event-Driven Stream Processing Framework—An Integrated Study for Low-Latency Matching and Real-Time Risk Control. Machine Learning Theory and Practice (2026), Vol. 6, Issue 1: 38-48. https://doi.org/10.38007/ML.2026.060105.

[1] Dingyuan Liu. Measuring the Sensitivity of Local Skill Structures to AI Substitution Risks Based on Occupational Task Decomposition. Socio-Economic Statistics Research (2025), Vol. 6, Issue 2: 177-184

[2] Zhen Zhong. Big Data Engineering and Intelligent Analysis Framework for Compliance Investigation. Academic Journal of Computing & Information Science (2025), Vol. 8, Issue 11: 107-115

[3] Chen, X. (2024, November). Cloud Storage User Behavior Analysis and Dynamic Replica Strategy Optimization Based on Improved RFM and Fuzzy Clustering. In International Conference on Cognitive based Information Processing and Applications (pp. 425-434). Singapore: Springer Nature Singapore.

[4] Wu, L. (2025, December). Design and Application of Automatic Data Set Generation Tool Based on KLEE in Embedded Memory Management Performance Test Framework. In 2025 IEEE 17th International Conference on Computational Intelligence and Communication Networks (CICN) (pp. 1111-1117). IEEE.

[5] Wu, L. (2025, December). Design and Application of Automatic Data Set Generation Tool Based on KLEE in Embedded Memory Management Performance Test Framework. In 2025 IEEE 17th International Conference on Computational Intelligence and Communication Networks (CICN) (pp. 1111-1117). IEEE.

[6] Truong, T. H. (2026). Research on Risks and Countermeasures of Enterprise E-Commerce Transformation in the Cross-Border E-Commerce Environment.

[7] Qi, Y. (2025, October). Research on Privacy Protection of AI Models in Big Data Using Differential Privacy Technology. In 2025 2nd International Conference on Software, Systems and Information Technology (SSITCON) (pp. 1-5). IEEE.

[8] Hua, X. (2024, November). Design and Implementation of a Game QoE Monitoring and Evaluation System Driven by Network Traffic Analysis. In International Conference on Cognitive based Information Processing and Applications (pp. 149-161). Singapore: Springer Nature Singapore.

[9] Huang, J. (2025, August). Research on Multi-Model Fusion Machine Learning Demand Intelligent Forecasting System in Cloud Computing Environment. In 2025 2nd International Conference on Intelligent Algorithms for Computational Intelligence Systems (IACIS) (pp. 1-7). IEEE.

[10] Huang, J. (2025, September). Performance Evaluation Index System and Engineering Best Practice of Production-Level Time Series Machine Learning System. In 2025 International Conference on Intelligent Communication Networks and Computational Techniques (ICICNCT) (pp. 01-07). IEEE.

[11] Zhou, Y. (2024, November). Construction of a Multi-factor Quantitative Stock Selection System for the New Energy Industry Based on Microservices Architecture and Machine Learning Components. In International Conference on Cognitive based Information Processing and Applications (pp. 163-174). Singapore: Springer Nature Singapore.

[12] Sun, Q. (2026). Research on Lightweight Intelligent Dialogue Systems Based on Semantic Entity Enhanced Intention Recognition and Rule Retrieval Generation Hybrid Models.

[13] Wang, Y. (2026). Research on the Application of Artificial Intelligence in Supply Chain Risk Early Warning.

[14] Liu, H. (2026). Research on the Application of Causal Reasoning Method in Content Compliance Experimental Evaluation.

[15] Liu, H. (2026). Research on Dynamic Price Prediction of E-commerce Based on Time Series Modeling.

[16] Yu, X. (2025). Digital Transformation Empowers Growth Marketing with Marketing Data Analysis Integration and Real-Time Display Strategy.

[17] Yu, X. (2026). Strategy Models and Practical Research of Growth Marketing under the Background of Digital Transformation.

[18] Yin, J. (2026). Research on Financial Time Series Prediction and Multiscale Correlation Based on the Fusion of Network Big Data and Deep Learning.

[19] Hou, Y. (2026). Research on BIOS and BMC Compatibility Optimization Methods for Cross-Generation Servers in Production Environments.

[20] Sun, Q. (2026). Research on a Robotic Natural Language Intelligent Decision-Making Framework Based on Large Language Models, Thinking Chain Reasoning, and Multi-Agent Collaboration.

[21] Hou, Y. (2026). Research on Server Performance Stability Assurance Mechanisms during Cross-Generation Computing Platform Upgrades.

[22] Han, X. (2026). Research on Process Decision-Making Behavior under Incomplete Information Conditions in Automobile Manufacturing Systems.

[23] Han, X. (2026). Research on Automotive Manufacturing Process Optimization Methods for Multi-Supplier Collaboration.

[24] Truong, T. H. (2025). Research on the Application of Digital Healthcare Platforms in Chronic Disease Management. Advances in Computer and Communication, 6(5).

[25] Hong, Y. (2026). Research on Warehouse Capacity Optimization Methods Based on Predictive Modeling. Engineering Advances, 6(1).

[26] Hong, Y. (2025). Architecture Design and Performance Optimization of a Large-scale Online Simulation Platform for Business Decision-making. Advances in Computer and Communication, 6(4).

[27] Xuanrui Zhang. Exploration of the Application of Big Data Technology in Financial Fraud Monitoring. Socio-Economic Statistics Research (2026), Vol. 7, Issue 1: 19-26

[28] Zhang, X. (2025, May). Automobile Finance Credit Fraud Risk Early Warning System based on Louvain Algorithm and XGBoost Model. In 2025 3rd International Conference on Data Science and Information System (ICDSIS) (pp. 1-7). IEEE.

[29] Wang, C. (2025). Research on Market Evaluation Strategies for Financial Institutions Based on Big Data Analysis.

[30] Lu, Z. (2025). AI-Driven Cross-Cloud Operations Language Standardisation and Knowledge Sharing System. European Journal of AI, Computing & Informatics, 1(4), 43-50.

[31] Lu, Z. (2025). Design and Practice of AI Intelligent Mentor System for DevOps Education. European Journal of Education Science, 1(3), 25-31.

[32] Huijie Pan. Discussion on Low-Latency Computing Strategies in Real-Time Hardware Generation. International Journal of Neural Network (2025), Vol. 4, Issue 1: 57-64.

[33] Linwei Wu. Application and Development of Blockchain Technology in Financial Infraustructure Innovation. International Journal of Business Management and Economics and Trade (2025), Vol. 6, Issue 1: 213-220.

[34] Yilin Fu. Data-driven Optimization of Capital Market Trading Strategies and Risk Management. International Journal of Business Management and Economics and Trade (2025), Vol. 6, Issue 1: 221-228.

[35] Qifeng Hu. Optimization and Upgrade Path of Tax Management Software System Based on Cloud Platform. Socio-Economic Statistics Research (2025), Vol. 6, Issue 2: 194-200.

[36] Jin Li. Performance Analysis of Efficient Microservice Architecture in the Financial Industry. Machine Learning Theory and Practice (2026), Vol. 6, Issue 1: 1-9.

[37] Yixian Jiang. Performance Optimization and Improvement of Advertising Machine Learning Platform Based on Distributed Systems. International Journal of Big Data Intelligent Technology (2026), Vol. 7, Issue 1: 9-17

[38] Bukun Ren. Multimodal Learning Method for Cross-Modal Data Alignment and Retrieval. International Journal of Multimedia Computing (2026), Vol. 7, Issue 1: 1-8.

[39] Shuang Yuan. Research on Abnormal Detection and Transaction Risk Management Based on Machine Learning. International Journal of Social Sciences and Economic Management (2026), Vol. 7, Issue 1: 10-18

[40] Zhengle Wei. Research on Innovative Design of Financial Derivatives and Market Risk Management Strategies. International Journal of Social Sciences and Economic Management (2026), Vol. 7, Issue 1: 19-27

[41] Yuhan Zhou. Green Bonds and Sustainable Financing Models in Energy Finance. International Journal of Social Sciences and Economic Management (2026), Vol. 7, Issue 1: 28-35

[42] Yilin Fu. Research on the Application of Innovative Financial Technologies in Capital Market Risk Management. Socio-Economic Statistics Research (2026), Vol. 7, Issue 1: 1-9

[43] Linwei Wu. Data Visualization and Decision Support Analysis Based on Tableau. Socio-Economic Statistics Research (2026), Vol. 7, Issue 1: 10-18

[44] Xinran Tu. Resource Allocation Optimization and Cost Saving Analysis Based on Data Mining. International Journal of Business Management and Economics and Trade (2026), Vol. 7, Issue 1: 1-9

[45] Wang, C. (2026). Research on the Control of Uncertainty Risks in Investment Decision-making by Financial Modeling.