Research On Query System Of Oil Drilling Information Optimization Based On Big Data

With the advent of the digital era,the information construction of the oil drilling industry has developed rapidly,and the data related to drilling production management information has increased exponentially.Traditional drilling information storage and query systems have been difficult to meet the statistical analysis of massive drilling data storage and query demand.In this paper,the theory and methods of big data are used to study and construct an optimized query system for oil drilling information based on big data,so as to further improve the timeliness and effectiveness of oil drilling information in a big data environment.First,the analysis explores the current limitations and deficiencies of traditional relational database distributed query,Apache Hadoop Hive distributed query and NoSQL database distributed query.Pointing out that in the face of a big data environment,there are many data sources,large amounts of data,and many types of data.Traditional database query systems lack effective processing methods.Apache Hadoop Hive distributed query operations are often accompanied by some redundant and time-consuming operations,and the development and maintenance of "NoSQL" database distributed queries is excessive.Second,the overall framework of an oil drilling information query system based on big data is designed and constructed.Using big data theory and methods,combined with the traditional query system architecture,design and build an oil drilling information query system architecture and software platform that supports real-time,parallel and interactive queries based on big data.Third,the research proposes the drilling data indexing algorithm and Top-k optimization query algorithm under the big data environment.Through the integration of Apache Kylin,Hive,HBase,etc.starting from the logical layer and storage layer of the data model,respectively,dimensional pruning optimization,coding optimization,keyword RowKey design optimization,forming drilling data index algorithm and Top-k query optimization algorithm.Fourth,with oil drilling information as the background,in light of the data characteristics of drilling production,an optimized query system for oil drilling information based on big data was developed.The system achieves efficient optimization of the performance of query services,reducing and avoiding many redundant operations.For simple queries,the performance level is milliseconds,and for millions of rows,the performance level is second.