To solve the query processing correctness problem for semantic-based relational data integration,the semantics of SAPRQL（simple protocol and RDF query language） queries is defined.In the course of query rewriting,al...To solve the query processing correctness problem for semantic-based relational data integration,the semantics of SAPRQL（simple protocol and RDF query language） queries is defined.In the course of query rewriting,all relative tables are found and decomposed into minimal connectable units.Minimal connectable units are joined according to semantic queries to produce the semantically correct query plans.Algorithms for query rewriting and transforming are presented.Computational complexity of the algorithms is discussed.Under the worst case,the query decomposing algorithm can be finished in O（n2） time and the query rewriting algorithm requires O（nm） time.And the performance of the algorithms is verified by experiments,and experimental results show that when the length of query is less than 8,the query processing algorithms can provide satisfactory performance.展开更多
The idea of positional inverted index is exploited for indexing of graph database. The main idea is the use of hashing tables in order to prune a considerable portion of graph database that cannot contain the answer s...The idea of positional inverted index is exploited for indexing of graph database. The main idea is the use of hashing tables in order to prune a considerable portion of graph database that cannot contain the answer set. These tables are implemented using column-based techniques and are used to store graphs of database, frequent sub-graphs and the neighborhood of nodes. In order to exact checking of remaining graphs, the vertex invariant is used for isomorphism test which can be parallel implemented. The results of evaluation indicate that proposed method outperforms existing methods.展开更多
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
RDF is the data interchange layer for the Semantic Web. an RDF repository should provide not only the necessary scalability In order to manage the increasing amount of RDF data, and efficiency, but also sufficient inf...RDF is the data interchange layer for the Semantic Web. an RDF repository should provide not only the necessary scalability In order to manage the increasing amount of RDF data, and efficiency, but also sufficient inference capabilities. Though existing RDF repositories have made progress towards these goals, there is still ample space for improving the overall performance. In this paper, we propose a native RDF repository, System H, to pursue a better tradeoff among system scalability, query efficiency, and inference capabilities. System II takes a hypergraph representation for RDF as the data model for its persistent storage, which effectively avoids the costs of data model transformation when accessing RDF data. Based on this native storage scheme, a set of efficient semantic query processing techniques are designed. First, several indices are built to accelerate RDF data access including a value index, a labeling scheme for transitive closure computation, and three triple indices. Second, we propose a hybrid inference strategy under the pD＊ semantics to support inference for OWL-Lite with a relatively low computational complexity. Finally, we extend the SPARQL algebra to explicitly express inference semantics in logical query plan by defining some new algebra operators. In addition, MD5 hash value of URI and schema level cache are introduced as practical implementation techniques. The results of performance evaluation on the LUBM benchmark and a real data set show that System Ⅱ has a better combined metric value than other comparable systems.展开更多
Incomplete data accompanies our life processes and covers almost all fields of scientific studies, as a result of delivery failure, no power of battery, accidental loss, etc. However, how to model, index, and query in...Incomplete data accompanies our life processes and covers almost all fields of scientific studies, as a result of delivery failure, no power of battery, accidental loss, etc. However, how to model, index, and query incomplete data in- curs big challenges. For example, the queries struggling with incomplete data usually have dissatisfying query results due to the improper incompleteness handling methods. In this pa- per, we systematically review the management of incomplete data, including modelling, indexing, querying, and handling methods in terms of incomplete data. We also overview sev- eral application scenarios of incomplete data, and summa- rize the existing systems related to incomplete data. It is our hope that this survey could provide insights to the database community on how incomplete data is managed, and inspire database researchers to develop more advanced processing techniques and tools to cope with the issues resulting from incomplete data in the real world.展开更多
基金Weaponry Equipment Pre-Research Foundation of PLA Equipment Ministry (No. 9140A06050409JB8102)Pre-Research Foundation of PLA University of Science and Technology (No. 2009JSJ11)
文摘To solve the query processing correctness problem for semantic-based relational data integration,the semantics of SAPRQL（simple protocol and RDF query language） queries is defined.In the course of query rewriting,all relative tables are found and decomposed into minimal connectable units.Minimal connectable units are joined according to semantic queries to produce the semantically correct query plans.Algorithms for query rewriting and transforming are presented.Computational complexity of the algorithms is discussed.Under the worst case,the query decomposing algorithm can be finished in O（n2） time and the query rewriting algorithm requires O（nm） time.And the performance of the algorithms is verified by experiments,and experimental results show that when the length of query is less than 8,the query processing algorithms can provide satisfactory performance.
文摘The idea of positional inverted index is exploited for indexing of graph database. The main idea is the use of hashing tables in order to prune a considerable portion of graph database that cannot contain the answer set. These tables are implemented using column-based techniques and are used to store graphs of database, frequent sub-graphs and the neighborhood of nodes. In order to exact checking of remaining graphs, the vertex invariant is used for isomorphism test which can be parallel implemented. The results of evaluation indicate that proposed method outperforms existing methods.
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.
基金supported by the National Natural Science Foundation of China under Grant Nos.90604025 and 60773106the National Basic Research 973 Program of China under Grant Nos.2003CB317007 and 2007CB310803
文摘RDF is the data interchange layer for the Semantic Web. an RDF repository should provide not only the necessary scalability In order to manage the increasing amount of RDF data, and efficiency, but also sufficient inference capabilities. Though existing RDF repositories have made progress towards these goals, there is still ample space for improving the overall performance. In this paper, we propose a native RDF repository, System H, to pursue a better tradeoff among system scalability, query efficiency, and inference capabilities. System II takes a hypergraph representation for RDF as the data model for its persistent storage, which effectively avoids the costs of data model transformation when accessing RDF data. Based on this native storage scheme, a set of efficient semantic query processing techniques are designed. First, several indices are built to accelerate RDF data access including a value index, a labeling scheme for transitive closure computation, and three triple indices. Second, we propose a hybrid inference strategy under the pD＊ semantics to support inference for OWL-Lite with a relatively low computational complexity. Finally, we extend the SPARQL algebra to explicitly express inference semantics in logical query plan by defining some new algebra operators. In addition, MD5 hash value of URI and schema level cache are introduced as practical implementation techniques. The results of performance evaluation on the LUBM benchmark and a real data set show that System Ⅱ has a better combined metric value than other comparable systems.
文摘Incomplete data accompanies our life processes and covers almost all fields of scientific studies, as a result of delivery failure, no power of battery, accidental loss, etc. However, how to model, index, and query incomplete data in- curs big challenges. For example, the queries struggling with incomplete data usually have dissatisfying query results due to the improper incompleteness handling methods. In this pa- per, we systematically review the management of incomplete data, including modelling, indexing, querying, and handling methods in terms of incomplete data. We also overview sev- eral application scenarios of incomplete data, and summa- rize the existing systems related to incomplete data. It is our hope that this survey could provide insights to the database community on how incomplete data is managed, and inspire database researchers to develop more advanced processing techniques and tools to cope with the issues resulting from incomplete data in the real world.
