The data warehouse is the most widely used database structure in many decision support systems around the world. This is the reason why a lot of research has been conducted in the literature over the last two decades ...The data warehouse is the most widely used database structure in many decision support systems around the world. This is the reason why a lot of research has been conducted in the literature over the last two decades on their design, refreshment and optimization. The manipulation of hypercubes (cubes) of data is a frequently used operation in the design of multidimensional data warehouses, due to their better adaptation to OLAP (On-Line Analytical Processing). However, the updating of these hypercubes is a very complicated process due mainly to the mass and complexity of the data presented. The purpose of this paper is to present the state of the art of works based on multidimensional modeling using the hypercube as a unit of presentation of data stores. It starts with the base of this process which is the choice of the views (cubes) forming our data warehouse base. The objective of this work is to describe the state of the art of research works dealing with the selection of materialized views in decision support systems.展开更多
Modern database systems desperate for the ability to support highly scalable transactions and efficient queries simultaneously for real-time applications.One solution is to utilize query optimization techniques on the...Modern database systems desperate for the ability to support highly scalable transactions and efficient queries simultaneously for real-time applications.One solution is to utilize query optimization techniques on the on-line transaction processing(OLTP)systems.The materialized view is considered as a panacea to decrease query latency.However,it also involves the significant cost of maintenance which trades away transaction performance.In this paper,we examine the design space and conclude several design features for the implementation of a view on a distributed log-structured merge-tree(LSMtree),which is a well-known structure for improving data write performance.As a result,we develop two incremental view maintenance(IVM)approaches on LSM-tree.One avoids join computation in view maintenance transactions.Another with two optimizations is proposed to decouple the view maintenance with the transaction process.Under the asynchronous update,we also provide consistency queries for views.Experiments on TPC-H benchmark show our methods achieve better performance than straightforward methods on different workloads.展开更多
文摘The data warehouse is the most widely used database structure in many decision support systems around the world. This is the reason why a lot of research has been conducted in the literature over the last two decades on their design, refreshment and optimization. The manipulation of hypercubes (cubes) of data is a frequently used operation in the design of multidimensional data warehouses, due to their better adaptation to OLAP (On-Line Analytical Processing). However, the updating of these hypercubes is a very complicated process due mainly to the mass and complexity of the data presented. The purpose of this paper is to present the state of the art of works based on multidimensional modeling using the hypercube as a unit of presentation of data stores. It starts with the base of this process which is the choice of the views (cubes) forming our data warehouse base. The objective of this work is to describe the state of the art of research works dealing with the selection of materialized views in decision support systems.
基金This work was partially supported by Youth Foundation of National Science Foundation(61702189)National Science Foundation(61772202).
文摘Modern database systems desperate for the ability to support highly scalable transactions and efficient queries simultaneously for real-time applications.One solution is to utilize query optimization techniques on the on-line transaction processing(OLTP)systems.The materialized view is considered as a panacea to decrease query latency.However,it also involves the significant cost of maintenance which trades away transaction performance.In this paper,we examine the design space and conclude several design features for the implementation of a view on a distributed log-structured merge-tree(LSMtree),which is a well-known structure for improving data write performance.As a result,we develop two incremental view maintenance(IVM)approaches on LSM-tree.One avoids join computation in view maintenance transactions.Another with two optimizations is proposed to decouple the view maintenance with the transaction process.Under the asynchronous update,we also provide consistency queries for views.Experiments on TPC-H benchmark show our methods achieve better performance than straightforward methods on different workloads.
