In this paper, we describe veDB-HTAP, a highly integrated, efficient, and adaptive HTAP system recently built in ByteDance. veDB-HTAP adopts a highly integrated system architecture by leveraging the Secondary Engine mechanism provided by MySQL and provides a seamless query processing experience across OLTP and OLAP engines. In addition, we introduce a cost-based and machine-learning-based smart query router that significantly outperforms the rule-based query router used in ByteHTAP, a precursor of veDB-HTAP. A key design principle of veDB-HTAP is the collaboration and adaptability of major system components, including query planning, query execution, and unified storage. Our adaptive query execution can be classified into two categories: 1) adaptive execution that dynamically collects and utilizes runtime statistics for better query performance; 2) utilizing runtime resource information to achieve a high quality of service even under heavy workloads. The experiments show that veDB-HTAP can achieve more than 3× speedup for TPC-H while consuming only one-third of the resources compared to ByteHTAP.

Nowadays real-time industrial applications are generating a huge amount of data continuously every day. To process these large data streams, we need fast and efficient methodologies and systems. A useful feature desired for data scientists and analysts is to have easy to visualize and understand machine learning models. Decision trees are preferred in many real-time applications for this reason, and also, because combined in an ensemble, they are one of the most powerful methods in machine learning.

WeChat is one of the most popular mobile messaging applications worldwide. However, due to the proprietary nature of WeChat, its characteristics and performance impact on cellular networks remain largely unexplored. This paper presents the first measurement study that dissects real-world WeChat traffic in a cellular network. We build ChatDissect, a protocol inference tool that infers the unique protocol formats and semantics of WeChat in a fine-grained manner. ChatDissect enables us to distinguish WeChat and its specific tasks from general network traffic traces. As a case study, we collect a real-world dataset from a commercial 3G cellular network in China and use ChatDissect to identify around 150K WeChat users with 16GB of WeChat payloads. We unveil the signatures, server architecture, and workflows of WeChat, and further analyze the activities of the extracted WeChat traffic.

Service Oriented Architecture is currently regarded as the next step for software architectures and achieve great usage in web services. However, the traditional SOA uses request/response pattern and is not suit for loose coupling, asynchronous scene while Even-Driven Architecture works well. To support the effective execution of possibly distributed and completely decoupled and heterogeneous services, synchronously or asynchronously executed in an efficient manner, there is an urgent need to integrate EDA and SOA into the next generation of SOA. We propose a semantic publish/subscribe system called JTangPS to serve as the event platform for event based SOA to satisfy the new challenges.