Pub Date : 2004-03-30DOI: 10.1109/ICDE.2004.1320021
R. Barga, Shimin Chen, D. Lomet
Phoenix/App supports software components whose states are made persistent across a system crash via redo recovery, replaying logged interactions. Our initial prototype force logged all request/reply events resulting from intercomponent method calls and returns. We describe an enhanced prototype that implements: (i) log optimizations to improve normal execution performance; and (ii) checkpointing to improve recovery performance. Logging is reduced in two ways: (1) we only log information required to remove nondeterminism, and we only force the log when an event "commits" the state of the component to other parts of the system; (2) we introduce new component types that provide our enhanced system with more information, enabling further reduction in logging. To improve recovery performance, we save the values of the fields of a component to the log in an application "checkpoint". We describe the system elements that we exploit for these optimizations, and characterize the performance gains that result.
{"title":"Improving logging and recovery performance in Phoenix/App","authors":"R. Barga, Shimin Chen, D. Lomet","doi":"10.1109/ICDE.2004.1320021","DOIUrl":"https://doi.org/10.1109/ICDE.2004.1320021","url":null,"abstract":"Phoenix/App supports software components whose states are made persistent across a system crash via redo recovery, replaying logged interactions. Our initial prototype force logged all request/reply events resulting from intercomponent method calls and returns. We describe an enhanced prototype that implements: (i) log optimizations to improve normal execution performance; and (ii) checkpointing to improve recovery performance. Logging is reduced in two ways: (1) we only log information required to remove nondeterminism, and we only force the log when an event \"commits\" the state of the component to other parts of the system; (2) we introduce new component types that provide our enhanced system with more information, enabling further reduction in logging. To improve recovery performance, we save the values of the fields of a component to the log in an application \"checkpoint\". We describe the system elements that we exploit for these optimizations, and characterize the performance gains that result.","PeriodicalId":358862,"journal":{"name":"Proceedings. 20th International Conference on Data Engineering","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131453667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2004-03-30DOI: 10.1109/ICDE.2004.1320025
David T. McWherter, Bianca Schroeder, A. Ailamaki, Mor Harchol-Balter
Transactional workloads are a hallmark of modern OLTP and Web applications, ranging from electronic commerce and banking to online shopping. Often, the database at the core of these applications is the performance bottleneck. Given the limited resources available to the database, transaction execution times can vary wildly as they compete and wait for critical resources. As the competitor is "only a click away", valuable (high-priority) users must be ensured consistently good performance via QoS and transaction prioritization. This paper analyzes and proposes prioritization for transactional workloads in traditional database systems (DBMS). This work first performs a detailed bottleneck analysis of resource usage by transactional workloads on commercial and noncommercial DBMS (IBM DB2, Post-greSQL, Shore) under a range of configurations. Second, this work implements and evaluates the performance of several preemptive and nonpreemptive DBMS prioritization policies in PostgreSQL and Shore. The primary contributions of this work include (i) understanding the bottleneck resources in transactional DBMS workloads and (ii) a demonstration that prioritization in traditional DBMS can provide 2x-5x improvement for high-priority transactions using simple scheduling policies, without expense to low-priority transactions.
{"title":"Priority mechanisms for OLTP and transactional Web applications","authors":"David T. McWherter, Bianca Schroeder, A. Ailamaki, Mor Harchol-Balter","doi":"10.1109/ICDE.2004.1320025","DOIUrl":"https://doi.org/10.1109/ICDE.2004.1320025","url":null,"abstract":"Transactional workloads are a hallmark of modern OLTP and Web applications, ranging from electronic commerce and banking to online shopping. Often, the database at the core of these applications is the performance bottleneck. Given the limited resources available to the database, transaction execution times can vary wildly as they compete and wait for critical resources. As the competitor is \"only a click away\", valuable (high-priority) users must be ensured consistently good performance via QoS and transaction prioritization. This paper analyzes and proposes prioritization for transactional workloads in traditional database systems (DBMS). This work first performs a detailed bottleneck analysis of resource usage by transactional workloads on commercial and noncommercial DBMS (IBM DB2, Post-greSQL, Shore) under a range of configurations. Second, this work implements and evaluates the performance of several preemptive and nonpreemptive DBMS prioritization policies in PostgreSQL and Shore. The primary contributions of this work include (i) understanding the bottleneck resources in transactional DBMS workloads and (ii) a demonstration that prioritization in traditional DBMS can provide 2x-5x improvement for high-priority transactions using simple scheduling policies, without expense to low-priority transactions.","PeriodicalId":358862,"journal":{"name":"Proceedings. 20th International Conference on Data Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129720236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. Kaushik, R. Krishnamurthy, J. Naughton, R. Ramakrishnan
Recently, there has been a great deal of interest in the development of techniques to evaluate path expressions over collections of XML documents. In general, these path expressions contain both structural and keyword components. Several methods have been proposed for processing path expressions over graph/tree-structured XML data. These methods can be classified into two broad classes. The first involves graph traversal where the input query is evaluated by traversing the data graph or some compressed representation. The other class involves information-retrieval style processing using inverted lists. In this framework, structure indexes have been proposed to be used as a substitute for graph traversal. Here, we focus on a subclass of CAS queries consisting of simple path expressions. We study algorithmic issues in integrating structure indexes with inverted lists for the evaluation of these queries, where we rank all documents that match the query and return the top k documents in order of relevance.
{"title":"On the integration of structure indexes and inverted lists","authors":"R. Kaushik, R. Krishnamurthy, J. Naughton, R. Ramakrishnan","doi":"10.1145/1007568.1007656","DOIUrl":"https://doi.org/10.1145/1007568.1007656","url":null,"abstract":"Recently, there has been a great deal of interest in the development of techniques to evaluate path expressions over collections of XML documents. In general, these path expressions contain both structural and keyword components. Several methods have been proposed for processing path expressions over graph/tree-structured XML data. These methods can be classified into two broad classes. The first involves graph traversal where the input query is evaluated by traversing the data graph or some compressed representation. The other class involves information-retrieval style processing using inverted lists. In this framework, structure indexes have been proposed to be used as a substitute for graph traversal. Here, we focus on a subclass of CAS queries consisting of simple path expressions. We study algorithmic issues in integrating structure indexes with inverted lists for the evaluation of these queries, where we rank all documents that match the query and return the top k documents in order of relevance.","PeriodicalId":358862,"journal":{"name":"Proceedings. 20th International Conference on Data Engineering","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121910639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2004-03-30DOI: 10.1109/ICDE.2004.1320017
Songting Chen, Jun Chen, Xin Zhang, Elke A. Rundensteiner
Data integration over multiple heterogeneous data sources has become increasingly important for modern applications. The integrated data is usually stored in materialized views for high availability and better performance. Such views must be maintained after the data sources change. In a loosely-coupled and dynamic environment, such as the Data Grid, the sources may autonomously change not only their data but also their schema, query capabilities or semantics, which may consequently cause the ongoing view maintenance fail. We analyze the maintenance errors and classify them into different classes of dependencies. We then propose several dependency detection and correction algorithms to handle these new classes of concurrency. Our techniques are not tied to specific maintenance algorithms nor to a particular data model. To our knowledge, this is the first complete solution to the view maintenance concurrency problems for both data and schema changes. We have implemented the proposed solutions and experimentally evaluated the impact of anomalies on maintenance performance and trade-offs between different dependency detection algorithms.
{"title":"Detection and correction of conflicting source updates for view maintenance","authors":"Songting Chen, Jun Chen, Xin Zhang, Elke A. Rundensteiner","doi":"10.1109/ICDE.2004.1320017","DOIUrl":"https://doi.org/10.1109/ICDE.2004.1320017","url":null,"abstract":"Data integration over multiple heterogeneous data sources has become increasingly important for modern applications. The integrated data is usually stored in materialized views for high availability and better performance. Such views must be maintained after the data sources change. In a loosely-coupled and dynamic environment, such as the Data Grid, the sources may autonomously change not only their data but also their schema, query capabilities or semantics, which may consequently cause the ongoing view maintenance fail. We analyze the maintenance errors and classify them into different classes of dependencies. We then propose several dependency detection and correction algorithms to handle these new classes of concurrency. Our techniques are not tied to specific maintenance algorithms nor to a particular data model. To our knowledge, this is the first complete solution to the view maintenance concurrency problems for both data and schema changes. We have implemented the proposed solutions and experimentally evaluated the impact of anomalies on maintenance performance and trade-offs between different dependency detection algorithms.","PeriodicalId":358862,"journal":{"name":"Proceedings. 20th International Conference on Data Engineering","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128253640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2004-03-30DOI: 10.1109/ICDE.2004.1320016
Khuzaima S. Daudjee, K. Salem
Lazy replication is a popular technique for improving the performance and availability of database systems. Although there are concurrency control techniques, which guarantee serializability in lazy replication systems, these techniques result in undesirable transaction orderings. Since transactions may see stale data, they may be serialized in an order different from the one in which they were submitted. Strong serializability avoids such problems, but it is very costly to implement. We propose a generalized form of strong serializability that is suitable for use with lazy replication. In addition to having many of the advantages of strong serializability, it can be implemented more efficiently. We show how generalized strong serializability can be implemented in a lazy replication system, and we present the results of a simulation study that quantifies the strengths and limitations of the approach.
{"title":"Lazy database replication with ordering guarantees","authors":"Khuzaima S. Daudjee, K. Salem","doi":"10.1109/ICDE.2004.1320016","DOIUrl":"https://doi.org/10.1109/ICDE.2004.1320016","url":null,"abstract":"Lazy replication is a popular technique for improving the performance and availability of database systems. Although there are concurrency control techniques, which guarantee serializability in lazy replication systems, these techniques result in undesirable transaction orderings. Since transactions may see stale data, they may be serialized in an order different from the one in which they were submitted. Strong serializability avoids such problems, but it is very costly to implement. We propose a generalized form of strong serializability that is suitable for use with lazy replication. In addition to having many of the advantages of strong serializability, it can be implemented more efficiently. We show how generalized strong serializability can be implemented in a lazy replication system, and we present the results of a simulation study that quantifies the strengths and limitations of the approach.","PeriodicalId":358862,"journal":{"name":"Proceedings. 20th International Conference on Data Engineering","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130912794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2004-03-30DOI: 10.1109/ICDE.2004.1320035
Ying Feng, D. Agrawal, A. E. Abbadi, Ahmed A. Metwally
Data cube computation and representation are prohibitively expensive in terms of time and space. Prior work has focused on either reducing the computation time or condensing the representation of a data cube. We introduce range cubing as an efficient way to compute and compress the data cube without any loss of precision. A new data structure, range trie, is used to compress and identify correlation in attribute values, and compress the input dataset to effectively reduce the computational cost. The range cubing algorithm generates a compressed cube, called range cube, which partitions all cells into disjoint ranges. Each range represents a subset of cells with the same aggregation value, as a tuple which has the same number of dimensions as the input data tuples. The range cube preserves the roll-up/drill-down semantics of a data cube. Compared to H-cubing, experiments on real dataset show a running time of less than one thirtieth, still generating a range cube of less than one ninth of the space of the full cube, when both algorithms run in their preferred dimension orders. On synthetic data, range cubing demonstrates much better scalability, as well as higher adaptiveness to both data sparsity and skew.
{"title":"Range cube: efficient cube computation by exploiting data correlation","authors":"Ying Feng, D. Agrawal, A. E. Abbadi, Ahmed A. Metwally","doi":"10.1109/ICDE.2004.1320035","DOIUrl":"https://doi.org/10.1109/ICDE.2004.1320035","url":null,"abstract":"Data cube computation and representation are prohibitively expensive in terms of time and space. Prior work has focused on either reducing the computation time or condensing the representation of a data cube. We introduce range cubing as an efficient way to compute and compress the data cube without any loss of precision. A new data structure, range trie, is used to compress and identify correlation in attribute values, and compress the input dataset to effectively reduce the computational cost. The range cubing algorithm generates a compressed cube, called range cube, which partitions all cells into disjoint ranges. Each range represents a subset of cells with the same aggregation value, as a tuple which has the same number of dimensions as the input data tuples. The range cube preserves the roll-up/drill-down semantics of a data cube. Compared to H-cubing, experiments on real dataset show a running time of less than one thirtieth, still generating a range cube of less than one ninth of the space of the full cube, when both algorithms run in their preferred dimension orders. On synthetic data, range cubing demonstrates much better scalability, as well as higher adaptiveness to both data sparsity and skew.","PeriodicalId":358862,"journal":{"name":"Proceedings. 20th International Conference on Data Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130125345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2004-03-30DOI: 10.1109/ICDE.2004.1320085
J. Freire, Maya Ramanath, Lingzhi Zhang
A key component of XML data management systems is the result size estimator, which estimates the cardinalities of user queries. Estimated cardinalities are needed in a variety of tasks, including query optimization and cost-based storage design; and they can also be used to give users early feedback about the expected outcome of their queries. In contrast to previously proposed result estimators, which use specialized data structures and estimation algorithms, StatiX uses histograms to uniformly capture both the structural and value skew present in documents. The original version of StatiX was built as a proof of concept. With the goal of making the system publicly available, we have built StatiX++, a new and improved version of StatiX, which extends the original system in significant ways. In this demonstration, we show the key features of StatiX++.
{"title":"A flexible infrastructure for gathering XML statistics and estimating query cardinality","authors":"J. Freire, Maya Ramanath, Lingzhi Zhang","doi":"10.1109/ICDE.2004.1320085","DOIUrl":"https://doi.org/10.1109/ICDE.2004.1320085","url":null,"abstract":"A key component of XML data management systems is the result size estimator, which estimates the cardinalities of user queries. Estimated cardinalities are needed in a variety of tasks, including query optimization and cost-based storage design; and they can also be used to give users early feedback about the expected outcome of their queries. In contrast to previously proposed result estimators, which use specialized data structures and estimation algorithms, StatiX uses histograms to uniformly capture both the structural and value skew present in documents. The original version of StatiX was built as a proof of concept. With the goal of making the system publicly available, we have built StatiX++, a new and improved version of StatiX, which extends the original system in significant ways. In this demonstration, we show the key features of StatiX++.","PeriodicalId":358862,"journal":{"name":"Proceedings. 20th International Conference on Data Engineering","volume":"84 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120883441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2004-03-30DOI: 10.1109/ICDE.2004.1320018
Jeffrey Considine, Feifei Li, G. Kollios, J. Byers
In the emerging area of sensor-based systems, a significant challenge is to develop scalable, fault-tolerant methods to extract useful information from the data the sensors collect. An approach to this data management problem is the use of sensor database systems, exemplified by TinyDB and Cougar, which allow users to perform aggregation queries such as MIN, COUNT and AVG on a sensor network. Due to power and range constraints, centralized approaches are generally impractical, so most systems use in-network aggregation to reduce network traffic. However, these aggregation strategies become bandwidth-intensive when combined with the fault-tolerant, multipath routing methods often used in these environments. For example, duplicate-sensitive aggregates such as SUM cannot be computed exactly using substantially less bandwidth than explicit enumeration. To avoid this expense, we investigate the use of approximate in-network aggregation using small sketches. Our contributions are as follows: 1) we generalize well known duplicate-insensitive sketches for approximating COUNT to handle SUM, 2) we present and analyze methods for using sketches to produce accurate results with low communication and computation overhead, and 3) we present an extensive experimental validation of our methods.
{"title":"Approximate aggregation techniques for sensor databases","authors":"Jeffrey Considine, Feifei Li, G. Kollios, J. Byers","doi":"10.1109/ICDE.2004.1320018","DOIUrl":"https://doi.org/10.1109/ICDE.2004.1320018","url":null,"abstract":"In the emerging area of sensor-based systems, a significant challenge is to develop scalable, fault-tolerant methods to extract useful information from the data the sensors collect. An approach to this data management problem is the use of sensor database systems, exemplified by TinyDB and Cougar, which allow users to perform aggregation queries such as MIN, COUNT and AVG on a sensor network. Due to power and range constraints, centralized approaches are generally impractical, so most systems use in-network aggregation to reduce network traffic. However, these aggregation strategies become bandwidth-intensive when combined with the fault-tolerant, multipath routing methods often used in these environments. For example, duplicate-sensitive aggregates such as SUM cannot be computed exactly using substantially less bandwidth than explicit enumeration. To avoid this expense, we investigate the use of approximate in-network aggregation using small sketches. Our contributions are as follows: 1) we generalize well known duplicate-insensitive sketches for approximating COUNT to handle SUM, 2) we present and analyze methods for using sketches to produce accurate results with low communication and computation overhead, and 3) we present an extensive experimental validation of our methods.","PeriodicalId":358862,"journal":{"name":"Proceedings. 20th International Conference on Data Engineering","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123052900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2004-03-30DOI: 10.1109/ICDE.2004.1320076
B. Benatallah, Mohand-Said Hacid, Hye-young Paik, Christophe Rey, F. Toumani
More and more suppliers are offering access to their product or information portals (also called e-catalogs) via the Web. The key issue is how to efficiently integrate and query large, intricate, heterogeneous information sources such as e-catalogs. Traditional data integration approach, where the development of an integrated schema requires the understanding of both structure and semantics of all schemas of sources to be integrated, is hardly applicable because of the dynamic nature and size of the Web. We present WS-CatalogNet: a Web services based data sharing middleware infrastructure whose aims is to enhance the potential of e-catalogs by focusing on scalability and flexible aspects of their sharing and access.
{"title":"Peering and querying e-catalog communities","authors":"B. Benatallah, Mohand-Said Hacid, Hye-young Paik, Christophe Rey, F. Toumani","doi":"10.1109/ICDE.2004.1320076","DOIUrl":"https://doi.org/10.1109/ICDE.2004.1320076","url":null,"abstract":"More and more suppliers are offering access to their product or information portals (also called e-catalogs) via the Web. The key issue is how to efficiently integrate and query large, intricate, heterogeneous information sources such as e-catalogs. Traditional data integration approach, where the development of an integrated schema requires the understanding of both structure and semantics of all schemas of sources to be integrated, is hardly applicable because of the dynamic nature and size of the Web. We present WS-CatalogNet: a Web services based data sharing middleware infrastructure whose aims is to enhance the potential of e-catalogs by focusing on scalability and flexible aspects of their sharing and access.","PeriodicalId":358862,"journal":{"name":"Proceedings. 20th International Conference on Data Engineering","volume":"170 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122829902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2004-03-30DOI: 10.1109/ICDE.2004.1320031
D. Gawlick, Dmitry Lenkov, Aravind Yalamanchi, L. Chernobrod
The support for the expression data type in a relational database system allows storing of conditional expressions as data in database tables and evaluating them using SQL queries. In the context of this new capability, expressions can be interpreted as descriptions, queries, and filters, and this significantly broadens the use of a relational database system to support new types of applications. The paper presents an overview of the expression data type, relates expressions to descriptions, queries, and filters, considers applications pertaining to information distribution, demand analysis, and task assignment, and shows how these applications can be easily supported with improved functionality.
{"title":"Applications for expression data in relational database systems","authors":"D. Gawlick, Dmitry Lenkov, Aravind Yalamanchi, L. Chernobrod","doi":"10.1109/ICDE.2004.1320031","DOIUrl":"https://doi.org/10.1109/ICDE.2004.1320031","url":null,"abstract":"The support for the expression data type in a relational database system allows storing of conditional expressions as data in database tables and evaluating them using SQL queries. In the context of this new capability, expressions can be interpreted as descriptions, queries, and filters, and this significantly broadens the use of a relational database system to support new types of applications. The paper presents an overview of the expression data type, relates expressions to descriptions, queries, and filters, considers applications pertaining to information distribution, demand analysis, and task assignment, and shows how these applications can be easily supported with improved functionality.","PeriodicalId":358862,"journal":{"name":"Proceedings. 20th International Conference on Data Engineering","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116986565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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