Automated performance tuning of data management systems offer various benefits such as improved performance, declined administration costs, and reduced workloads to database administrators (DBAs). Currently, DBAs tune...Automated performance tuning of data management systems offer various benefits such as improved performance, declined administration costs, and reduced workloads to database administrators (DBAs). Currently, DBAs tune the performance of database systems with a little help from the database servers. In this paper, we propose a new technique for automated performance tuning of data management systems. Firstly, we show how to use the periods of low workload time for performance improvements in the periods of high workload time. We demonstrate that extensions of a database system with materialised views and indices when a workload is low may contribute to better performance for a successive period of high workload. The paper proposes several online algorithms for continuous processing of estimated database workloads and for the discovery of the best plan for materialised view and index database extensions and of elimination of the extensions that are no longer needed. We present the results of experiments that show how the proposed automated performance tuning technique improves the overall performance of a data management system. 展开更多
Data security and privacy issues are magnified by the volume,the variety,and the velocity of Big Data and by the lack,up to now,of a reference data model and related data manipulation languages.In this paper,we focus ...Data security and privacy issues are magnified by the volume,the variety,and the velocity of Big Data and by the lack,up to now,of a reference data model and related data manipulation languages.In this paper,we focus on one of the key data security services,that is,access control,by highlighting the differences with traditional data management systems and describing a set of requirements that any access control solution for Big Data platforms may fulfill.We then describe the state of the art and discuss open research issues.展开更多
Data security and privacy issues are magnified by the volume,the variety,and the velocity of Big Data and by the lack,up to now,of a reference data model and related data manipulation languages.In this paper,we focus ...Data security and privacy issues are magnified by the volume,the variety,and the velocity of Big Data and by the lack,up to now,of a reference data model and related data manipulation languages.In this paper,we focus on one of the key data security services,that is,access control,by highlighting the differences with traditional data management systems and describing a set of requirements that any access control solution for Big Data platforms may fulfill.We then describe the state of the art and discuss open research issues.展开更多
This paper is concerned with the development of product data management （PDM） systems--WPDM systems based on web technologies. As a tool to integrate information, traditional PDM system has many benefits for the com...This paper is concerned with the development of product data management （PDM） systems--WPDM systems based on web technologies. As a tool to integrate information, traditional PDM system has many benefits for the companies in such aspects as improving design productivity, better control over projects and so on. With the maturing of web technologies, the advantages of WPDM system are obvious. We will show these advantages in detail in Part 3. WPDM system is built on three-tier application model to provide security and flexibility, they are back-end, middle layer and front-end. The basic designs in each layer will be briefly introduced in Part 4. In the future, WPDM will be extended to integrate with other applications to provide a complete web-based engineering environment.展开更多
Data stream management system (DSMS) provides convenient solutions to the problem of processing continuous queries on data streams.Previous approaches for scheduling these queries and their operators assume that each ...Data stream management system (DSMS) provides convenient solutions to the problem of processing continuous queries on data streams.Previous approaches for scheduling these queries and their operators assume that each operator runs in separate thread or all operators combine in one query plan and run in a single thread.Both approaches suffer from severe drawbacks concerning the thread overhead and the stalls due to expensive operators.To overcome these drawbacks,a novel approach called clustered operators scheduling (COS) is proposed that adaptively clusters operators of the query plan into a number of groups based on their selectivity and computing cost using S-mean clustering.Experimental evaluation is provided to demonstrate the potential benefits of COS scheduling over the other scheduling strategies.COS can provide adaptive,flexible,reliable,scalable and robust design for continuous query processor.展开更多
文摘Automated performance tuning of data management systems offer various benefits such as improved performance, declined administration costs, and reduced workloads to database administrators (DBAs). Currently, DBAs tune the performance of database systems with a little help from the database servers. In this paper, we propose a new technique for automated performance tuning of data management systems. Firstly, we show how to use the periods of low workload time for performance improvements in the periods of high workload time. We demonstrate that extensions of a database system with materialised views and indices when a workload is low may contribute to better performance for a successive period of high workload. The paper proposes several online algorithms for continuous processing of estimated database workloads and for the discovery of the best plan for materialised view and index database extensions and of elimination of the extensions that are no longer needed. We present the results of experiments that show how the proposed automated performance tuning technique improves the overall performance of a data management system.
文摘Data security and privacy issues are magnified by the volume,the variety,and the velocity of Big Data and by the lack,up to now,of a reference data model and related data manipulation languages.In this paper,we focus on one of the key data security services,that is,access control,by highlighting the differences with traditional data management systems and describing a set of requirements that any access control solution for Big Data platforms may fulfill.We then describe the state of the art and discuss open research issues.
文摘Data security and privacy issues are magnified by the volume,the variety,and the velocity of Big Data and by the lack,up to now,of a reference data model and related data manipulation languages.In this paper,we focus on one of the key data security services,that is,access control,by highlighting the differences with traditional data management systems and describing a set of requirements that any access control solution for Big Data platforms may fulfill.We then describe the state of the art and discuss open research issues.
文摘This paper is concerned with the development of product data management （PDM） systems--WPDM systems based on web technologies. As a tool to integrate information, traditional PDM system has many benefits for the companies in such aspects as improving design productivity, better control over projects and so on. With the maturing of web technologies, the advantages of WPDM system are obvious. We will show these advantages in detail in Part 3. WPDM system is built on three-tier application model to provide security and flexibility, they are back-end, middle layer and front-end. The basic designs in each layer will be briefly introduced in Part 4. In the future, WPDM will be extended to integrate with other applications to provide a complete web-based engineering environment.
基金Project(50275150) supported by the National Natural Science Foundation of ChinaProject(20040533035) supported by the National Research Foundation for the Doctoral Program of Higher Education of China
文摘Data stream management system (DSMS) provides convenient solutions to the problem of processing continuous queries on data streams.Previous approaches for scheduling these queries and their operators assume that each operator runs in separate thread or all operators combine in one query plan and run in a single thread.Both approaches suffer from severe drawbacks concerning the thread overhead and the stalls due to expensive operators.To overcome these drawbacks,a novel approach called clustered operators scheduling (COS) is proposed that adaptively clusters operators of the query plan into a number of groups based on their selectivity and computing cost using S-mean clustering.Experimental evaluation is provided to demonstrate the potential benefits of COS scheduling over the other scheduling strategies.COS can provide adaptive,flexible,reliable,scalable and robust design for continuous query processor.
