👋 Hi, I’m @Flink-ddd, Keen on studying various technologies and applying them in actual business. I have Java development experience and practical use of some big data technology stacks, and I am currently learning artificial intelligence technology.

Java field: 1: Have a deep understanding and research on microservice architecture and DevOps architecture 2: Have practical project experience based on in-depth research and secondary development of technology stacks to help companies build technology systems and improve business development efficiency.

Example 1: Based on Prometheus+grafana technology, secondary development is carried out. Develop a full-link monitoring alarm that meets the company's business monitoring project and the company's business. The alarm methods include SMS, email, and third-party office software, including server level, project interface level, business process level, etc.

Example 2: Based on springboot, webscoket, zookeeper, kafka, MinIO, mysql and other technologies, develop an instant messaging system that supports millions of users online at the same time, supporting single and group chats, voice calls, video calls, etc.

Example 3: Based on springboot, springcloud, elasticsearch, flink-cdc, MySQL, MongoDB and other technologies, develop an enterprise-level search center that supports efficient search of billions of data.

Example 4: Develop a knowledge graph center based on Neo4j to meet the changing business coverage.

Example 5: Based on DDD domain-driven design, develop a multifunctional payment center within the company group to meet the payment business of all business lines of the entire company, and have experienced millions of payment data per day.

Example 6: Based on flink-cdc, develop a data synchronization center to support the capture of real-time change data of heterogeneous data sources and write it to the target table and message queue.

The data synchronization center supports visual configuration monitoring data sources, custom topics, custom synchronization strategies, etc., to help business lines handle the synchronization needs of massive data, etc. There are many other projects that are not listed one by one, involving e-commerce, medical and other fields.

Big data field: 1: There is a practical application of some core technology stacks, including the understanding of data lake and data grid construction. 2: Understanding and application of OLAP

Example 1: Build an enterprise-level flink cluster, extend the flink computing center, support projects such as statistics center, data synchronization center, computing engine, and make real-time data lake based on flink.

Example 2: Do enterprise-level OLAP based on clickhouse

Example 3: Do enterprise-level log collection platform based on flume, etc.

🌱 I’m currently learning LLM and Deep Learning etc

📫 How to reach me: [email protected] what's app: 8130 2719