Design And Implementation Of Data Collection And Storage System Based On Big Data Architecture

Netizens and web are closely connection in all over the levels in the era of Internet 3.0.Various kinds of information are explosive growing,data is infiltrated into all walks of life,and artificial intelligence is developing rapidly.The datas whict is the base of artificial intelligence is often in a mess,which makes the difficulty of data analysis or AI intelligent model training greatly improved.Therefore,the collection and storage of data regularization is urgent for the development of data analysis and artificial intelligence.At first,it analyzes the research status in related fields at home and abroad,and puts forward the requirements of acquisition and storage in real-world application production for the existing shortage of storage middleware architecture,and proposes a big data architecture based on this series of requirements——Data collection and storage system.Secondly,the key technologies of data acquisition are studied,and the existing framework technology and middleware are selected.Data collection is proposed for data docking and crawling.In view of the inconsistency between data cleaning and storage speed,the message queue middleware method is adopted to eliminate the peak of the data volume request during the peak period.Then,the system designs the existing storage middleware for the high availability requirements of the system in the formal production environment,adopts the distributed and data write-back hooks,and carries out the downtime strategy design to ensure the system 7*24 hours uninterrupted service.The data is not lost for at least 3 days to ensure the reliability of the data and the stability of the service.Finally,the springBoot framework is used to build such a web system based on big data architecture for data acquisition and storage.To sum up,it studies the technology of data collection and storage which based on big data architecture,and realized a high-concurrency,large-flow,high-availability data acquisition and storage system based on the existing middleware of big data storage.