The big data session of Pegasus & Ele. me Technology Salon came to a successful end

On the afternoon of August 26, Pegasus and Ele. me Technology Salon successfully concluded in Chuangye Commune. The salon with big data as the theme, to the technology practice as the breakthrough point, the best application according to the local service life of hot, new retail and supplement each other with big data of cloud computing and other industries, specially invited hungry yao, shells, daily fresh and qingyun QingCloud four experts conducted a profound and wonderful content to share.

First of all, With the theme of “Intelligent scheduling System of Ele. me driven by data and algorithm”, Mr. Ning Chen, senior algorithm expert of BDI Big Data Department of Ele. me, revealed for the first time how the daily order volume of ten million orders was dispatched through the intelligent scheduling system. Scheduling can be said to be the most core link in the field of instant distribution. Chen Ning pointed out that “the biggest goal of intelligent dispatching system is to replace the work of single dispatcher, avoid human intervention, and realize intelligent and automatic dispatching and path planning.” He introduced the core components of ele. me intelligent scheduling system, dispatching strategy, time prediction, supply and demand balance and location service subsystem respectively.

Professor Jian Huiyang, r & D engineer of Shell Big Data Architecture Group, shared the practice and application of shell real-time analysis and monitoring system. Jian Huiyang first introduced in detail the system requirements of different roles such as shell operation, development, analysis and operation, and then analyzed the system process and architecture to meet the real-time task average processing 20W+ data per second, and analyzed in detail the problems of loss, repetition, delay and other aspects in the practice. Four tuning methods of Kafka, SparkStreaming, ElasticSearch and Druid are given, and each tuning method is explained in detail with specific implementation cases.

After the break, Teacher Dong Si generation, senior algorithm engineer of big data from Daily Youxian, brought the application analysis of big data in fresh food industry. In the process of sharing, Teacher Dong talked about the unique characteristics of fresh commodities, such as large demand, perishable and fast inventory cycle, which are different from other ordinary commodities. The rapid rise of Daily Youxian in a short period of time depends to a large extent on the realization of strong fresh replenishment technology. From the aspects of commodity management, replenishment plan, storage and cold chain, algorithm and prediction, Mr. Dong systematically presented the intelligent replenishment technology of fresh food to the audience. This technology has a certain demonstration role for the whole fresh food industry.

Mr. Peng Ke, senior big data product engineer of QingCloud, took the Application of Internet of Things as the starting point to share the last part of this salon activity — The exploration of big data application in the era of cloud computing and Internet of Things. Along with the development of the Internet of things is overwhelm, penco teachers from the aspects of the technical architecture of the Internet of things and Internet of things application case of big data century put forward an understanding of the Internet of things, in addition, penco teachers also from their own experience in project and everybody discusses together the problems encountered in the development process and their solutions.

During the intermission, the lecturers were besieged one after another and had a very lively discussion about sharing details.

The whole salon lasted for three and a half hours. Four experts unlocked the application and practice of big data in different industries from different perspectives. It was interesting and full of useful materials. In the current era of continuous innovation in big data application, Pegasus will organize more online and offline exchanges to provide more support for technological innovation exchanges between enterprises and professional improvement of technical personnel.