Pub Date : 2001-04-02DOI: 10.1109/ICDE.2001.914835
C. Heinlein
Current workflow management technology does not provide adequate means for inter-workflow coordination as concurrently executing workflows are considered completely independent. While this simplified view might suffice for one application domain or the other, there are many real-world application scenarios where workflows, though independently modeled in order to remain comprehensible and manageable, are semantically interrelated. As pragmatical approaches, like merging interdependent workflows or inter-workflow message passing, do not satisfactorily solve the inter-workflow coordination problem, interaction expressions and graphs are proposed as a simple yet powerful formalism for the specification and implementation of synchronization conditions in general and inter-workflow dependencies in particular. In addition to a graph based semi-formal interpretation of the formalism, a precise formal semantics, an equivalent operational semantics, an efficient implementation of the latter, and detailed complexity analyses have been developed, allowing the formalism to be actually applied to solve real-world problems like inter-workflow coordination.
{"title":"Workflow and process synchronization with interaction expressions and graphs","authors":"C. Heinlein","doi":"10.1109/ICDE.2001.914835","DOIUrl":"https://doi.org/10.1109/ICDE.2001.914835","url":null,"abstract":"Current workflow management technology does not provide adequate means for inter-workflow coordination as concurrently executing workflows are considered completely independent. While this simplified view might suffice for one application domain or the other, there are many real-world application scenarios where workflows, though independently modeled in order to remain comprehensible and manageable, are semantically interrelated. As pragmatical approaches, like merging interdependent workflows or inter-workflow message passing, do not satisfactorily solve the inter-workflow coordination problem, interaction expressions and graphs are proposed as a simple yet powerful formalism for the specification and implementation of synchronization conditions in general and inter-workflow dependencies in particular. In addition to a graph based semi-formal interpretation of the formalism, a precise formal semantics, an equivalent operational semantics, an efficient implementation of the latter, and detailed complexity analyses have been developed, allowing the formalism to be actually applied to solve real-world problems like inter-workflow coordination.","PeriodicalId":431818,"journal":{"name":"Proceedings 17th International Conference on Data Engineering","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125864085","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 : 2001-04-02DOI: 10.1109/ICDE.2001.914852
Wolfgang Lehner, R. Cochrane, H. Pirahesh, Markos Zaharioudakis
Automatic summary tables (ASTs), more commonly known as materialized views, are widely used to enhance query performance, particularly for aggregate queries. Such queries access a huge number of rows to retrieve aggregated summary data while performing multiple joins in the context of a typical data warehouse star schema. To keep ASTs consistent with their underlying base data, the ASTs are either immediately synchronized or fully recomputed. This paper proposes an optimization strategy for simultaneously refreshing multiple ASTs, thus avoiding multiple scans of a large fact table (one pass for AST computation). A query stacking strategy detects common sub-expressions using the available query matching technology of DB2. Since exact common sub-expressions are rare, the novel query sharing approach systematically generates common subexpressions for a given set of "related" queries, considering different predicates, grouping expressions, and sets of base tables. The theoretical framework, a prototype implementation of both strategies in the IBM DB2 UDB/UWO database system, and performance evaluations based on the TPC/R data schema are presented in this paper.
{"title":"fAST refresh using mass query optimization","authors":"Wolfgang Lehner, R. Cochrane, H. Pirahesh, Markos Zaharioudakis","doi":"10.1109/ICDE.2001.914852","DOIUrl":"https://doi.org/10.1109/ICDE.2001.914852","url":null,"abstract":"Automatic summary tables (ASTs), more commonly known as materialized views, are widely used to enhance query performance, particularly for aggregate queries. Such queries access a huge number of rows to retrieve aggregated summary data while performing multiple joins in the context of a typical data warehouse star schema. To keep ASTs consistent with their underlying base data, the ASTs are either immediately synchronized or fully recomputed. This paper proposes an optimization strategy for simultaneously refreshing multiple ASTs, thus avoiding multiple scans of a large fact table (one pass for AST computation). A query stacking strategy detects common sub-expressions using the available query matching technology of DB2. Since exact common sub-expressions are rare, the novel query sharing approach systematically generates common subexpressions for a given set of \"related\" queries, considering different predicates, grouping expressions, and sets of base tables. The theoretical framework, a prototype implementation of both strategies in the IBM DB2 UDB/UWO database system, and performance evaluations based on the TPC/R data schema are presented in this paper.","PeriodicalId":431818,"journal":{"name":"Proceedings 17th International Conference on Data Engineering","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122867941","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 : 2001-04-02DOI: 10.1109/ICDE.2001.914841
D. H. Fishman
Automating the interactions between trusted business partners is a major goal of businesses today. This is often called "supply-chain integration". The intent is to make the businesses more responsive to customer needs and more efficient in their business or manufacturing processes. This paper describes an infrastructure that facilitates the collaboration of trusted business partners to achieve common business goals.
{"title":"Data management support of Web applications","authors":"D. H. Fishman","doi":"10.1109/ICDE.2001.914841","DOIUrl":"https://doi.org/10.1109/ICDE.2001.914841","url":null,"abstract":"Automating the interactions between trusted business partners is a major goal of businesses today. This is often called \"supply-chain integration\". The intent is to make the businesses more responsive to customer needs and more efficient in their business or manufacturing processes. This paper describes an infrastructure that facilitates the collaboration of trusted business partners to achieve common business goals.","PeriodicalId":431818,"journal":{"name":"Proceedings 17th International Conference on Data Engineering","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114491900","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 : 2001-04-02DOI: 10.1109/ICDE.2001.914850
Amir Netz, S. Chaudhuri, U. Fayyad, J. Bernhardt
The integration of data mining with traditional database systems is key to making it convenient, easy to deploy in real applications, and to growing its user base. We describe the new API for data mining proposed by Microsoft as extensions to the OLE DB standard. We illustrate the basic notions that motivated the API's design and describe the key components of an OLE DB for the data mining provider. We also include examples of the usage and treat the problems of data representation and integration with the SQL framework. We believe this new API will go a long way in enabling deployment of data mining in enterprise data warehouses. A reference implementation of a provider is available with the recent release of Microsoft SQL Server 2000 database system.
数据挖掘与传统数据库系统的集成是使其方便、易于在实际应用程序中部署以及扩大其用户基础的关键。我们将微软提出的用于数据挖掘的新API描述为OLE DB标准的扩展。我们说明了激发API设计的基本概念，并描述了数据挖掘提供者的OLE DB的关键组件。我们还包括使用示例，并处理数据表示和与SQL框架集成的问题。我们相信这个新的API将在企业数据仓库中部署数据挖掘方面大有帮助。最近发布的Microsoft SQL Server 2000数据库系统提供了提供程序的参考实现。
{"title":"Integrating data mining with SQL databases: OLE DB for data mining","authors":"Amir Netz, S. Chaudhuri, U. Fayyad, J. Bernhardt","doi":"10.1109/ICDE.2001.914850","DOIUrl":"https://doi.org/10.1109/ICDE.2001.914850","url":null,"abstract":"The integration of data mining with traditional database systems is key to making it convenient, easy to deploy in real applications, and to growing its user base. We describe the new API for data mining proposed by Microsoft as extensions to the OLE DB standard. We illustrate the basic notions that motivated the API's design and describe the key components of an OLE DB for the data mining provider. We also include examples of the usage and treat the problems of data representation and integration with the SQL framework. We believe this new API will go a long way in enabling deployment of data mining in enterprise data warehouses. A reference implementation of a provider is available with the recent release of Microsoft SQL Server 2000 database system.","PeriodicalId":431818,"journal":{"name":"Proceedings 17th International Conference on Data Engineering","volume":"2 8","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120808565","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 : 2001-04-02DOI: 10.1109/ICDE.2001.914848
A. Tung, Jean Hou, Jiawei Han
Clustering in spatial data mining is to group similar objects based on their distance, connectivity, or their relative density in space. In the real world there exist many physical obstacles such as rivers, lakes and highways, and their presence may affect the result of clustering substantially. We study the problem of clustering in the presence of obstacles and define it as a COD (Clustering with Obstructed Distance) problem. As a solution to this problem, we propose a scalable clustering algorithm, called COD-CLARANS. We discuss various forms of pre-processed information that could enhance the efficiency of COD-CLARANS. In the strictest sense, the COD problem can be treated as a change in distance function and thus could be handled by current clustering algorithms by changing the distance function. However, we show that by pushing the task of handling obstacles into COD-CLARANS instead of abstracting it at the distance function level, more optimization can be done in the form of a pruning function E'. We conduct various performance studies to show that COD-CLARANS is both efficient and effective.
空间数据挖掘中的聚类是根据相似对象在空间中的距离、连通性或相对密度对其进行分组。在现实世界中，存在许多物理障碍，如河流、湖泊和高速公路，它们的存在可能会对聚类结果产生很大的影响。我们研究了障碍物存在下的聚类问题，并将其定义为COD (clustered with obstacle Distance)问题。为了解决这个问题，我们提出了一种可扩展的聚类算法，称为COD-CLARANS。我们讨论了可以提高COD-CLARANS效率的各种形式的预处理信息。从严格意义上讲，COD问题可以看作是距离函数的变化，因此当前的聚类算法可以通过改变距离函数来处理COD问题。然而，我们表明，通过将处理障碍物的任务推入COD-CLARANS而不是在距离函数级别抽象它，可以以修剪函数E'的形式进行更多优化。我们进行了各种性能研究，以表明COD-CLARANS既高效又有效。
{"title":"Spatial clustering in the presence of obstacles","authors":"A. Tung, Jean Hou, Jiawei Han","doi":"10.1109/ICDE.2001.914848","DOIUrl":"https://doi.org/10.1109/ICDE.2001.914848","url":null,"abstract":"Clustering in spatial data mining is to group similar objects based on their distance, connectivity, or their relative density in space. In the real world there exist many physical obstacles such as rivers, lakes and highways, and their presence may affect the result of clustering substantially. We study the problem of clustering in the presence of obstacles and define it as a COD (Clustering with Obstructed Distance) problem. As a solution to this problem, we propose a scalable clustering algorithm, called COD-CLARANS. We discuss various forms of pre-processed information that could enhance the efficiency of COD-CLARANS. In the strictest sense, the COD problem can be treated as a change in distance function and thus could be handled by current clustering algorithms by changing the distance function. However, we show that by pushing the task of handling obstacles into COD-CLARANS instead of abstracting it at the distance function level, more optimization can be done in the form of a pruning function E'. We conduct various performance studies to show that COD-CLARANS is both efficient and effective.","PeriodicalId":431818,"journal":{"name":"Proceedings 17th International Conference on Data Engineering","volume":"309 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124398094","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 : 2001-04-02DOI: 10.1109/ICDE.2001.914867
S. Chaudhuri, Gautam Das, Mayur Datar, R. Motwani, Vivek R. Narasayya
Studies the problem of approximately answering aggregation queries using sampling. We observe that uniform sampling performs poorly when the distribution of the aggregated attribute is skewed. To address this issue, we introduce a technique called outlier indexing. Uniform sampling is also ineffective for queries with low selectivity. We rely on weighted sampling based on workload information to overcome this shortcoming. We demonstrate that a combination of outlier indexing with weighted sampling can be used to answer aggregation queries with a significantly reduced approximation error compared to either uniform sampling or weighted sampling alone. We discuss the implementation of these techniques on Microsoft's SQL Server and present experimental results that demonstrate the merits of our techniques.
{"title":"Overcoming limitations of sampling for aggregation queries","authors":"S. Chaudhuri, Gautam Das, Mayur Datar, R. Motwani, Vivek R. Narasayya","doi":"10.1109/ICDE.2001.914867","DOIUrl":"https://doi.org/10.1109/ICDE.2001.914867","url":null,"abstract":"Studies the problem of approximately answering aggregation queries using sampling. We observe that uniform sampling performs poorly when the distribution of the aggregated attribute is skewed. To address this issue, we introduce a technique called outlier indexing. Uniform sampling is also ineffective for queries with low selectivity. We rely on weighted sampling based on workload information to overcome this shortcoming. We demonstrate that a combination of outlier indexing with weighted sampling can be used to answer aggregation queries with a significantly reduced approximation error compared to either uniform sampling or weighted sampling alone. We discuss the implementation of these techniques on Microsoft's SQL Server and present experimental results that demonstrate the merits of our techniques.","PeriodicalId":431818,"journal":{"name":"Proceedings 17th International Conference on Data Engineering","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116820226","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 : 2001-04-02DOI: 10.1109/ICDE.2001.914831
Eric Gigukre
Applications require access to database servers for many purposes. Mobile users, those who use their computing devices away from a traditional local area network, require access to data even when central database servers are unavailable. iAnywhere Solutions provides a number of solutions that address the challenges of offline and wireless data access. The article discusses those challenges and presents solutions.
{"title":"Mobile data management: challenges of wireless and offline data access","authors":"Eric Gigukre","doi":"10.1109/ICDE.2001.914831","DOIUrl":"https://doi.org/10.1109/ICDE.2001.914831","url":null,"abstract":"Applications require access to database servers for many purposes. Mobile users, those who use their computing devices away from a traditional local area network, require access to data even when central database servers are unavailable. iAnywhere Solutions provides a number of solutions that address the challenges of offline and wireless data access. The article discusses those challenges and presents solutions.","PeriodicalId":431818,"journal":{"name":"Proceedings 17th International Conference on Data Engineering","volume":"181 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122665185","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 : 2001-04-02DOI: 10.1109/ICDE.2001.914839
Wei Wang, Jiong Yang, R. Muntz
Data mining has been an area of increasing interest. The association rule discovery problem in particular has been widely studied. However, there are still some unresolved problems. For example, research on mining patterns in the evolution of numerical attributes is still lacking. This is both a challenging problem and one with significant practical applications in business, science, and medicine. In this paper we present a temporal association rule model for evolving numerical attributes. Metrics for qualifying a temporal association rule include the familiar measures of support and strength used in traditional association rule mining and a new metric called density. The density metric not only gives us a way to extract the rules that best represent the data, but also provides an effective mechanism to prune the search space. An efficient algorithm is devised for mining temporal association rules, which utilizes all three thresholds (especially the strength) to prune the search space drastically. Moreover, the resulting rules are represented in a concise manner via rule sets to reduce the output size. Experimental results on real and synthetic data sets demonstrate the efficiency of our algorithm.
{"title":"TAR: temporal association rules on evolving numerical attributes","authors":"Wei Wang, Jiong Yang, R. Muntz","doi":"10.1109/ICDE.2001.914839","DOIUrl":"https://doi.org/10.1109/ICDE.2001.914839","url":null,"abstract":"Data mining has been an area of increasing interest. The association rule discovery problem in particular has been widely studied. However, there are still some unresolved problems. For example, research on mining patterns in the evolution of numerical attributes is still lacking. This is both a challenging problem and one with significant practical applications in business, science, and medicine. In this paper we present a temporal association rule model for evolving numerical attributes. Metrics for qualifying a temporal association rule include the familiar measures of support and strength used in traditional association rule mining and a new metric called density. The density metric not only gives us a way to extract the rules that best represent the data, but also provides an effective mechanism to prune the search space. An efficient algorithm is devised for mining temporal association rules, which utilizes all three thresholds (especially the strength) to prune the search space drastically. Moreover, the resulting rules are represented in a concise manner via rule sets to reduce the output size. Experimental results on real and synthetic data sets demonstrate the efficiency of our algorithm.","PeriodicalId":431818,"journal":{"name":"Proceedings 17th International Conference on Data Engineering","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123588607","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 : 2001-04-02DOI: 10.1109/ICDE.2001.914843
Dao Dinh Kha, Masatoshi Yoshikawa, Shunsuke Uemura
For most of the index structures for XML data proposed so far, updating is a problem, because an XML element's coordinates are expressed using absolute values. Due to the structural relationship among the elements in XML documents, we have to re-compute these absolute values if the content of the source data is updated. The reconstruction requires the updating of a large portion of the index files, which causes a serious problem, especially when the XML data content is updated frequently. In this paper, we propose an indexing structure scheme based on the relative region coordinates that can effectively deal with the update problem. The main idea is that we express the coordinates of an XML element based on the region of its parent element. We present an algorithm to construct a tree-structured index in which related coordinates are stored together. In consequence, our indexing scheme requires the updating of only a small portion of the index file.
{"title":"An XML indexing structure with relative region coordinate","authors":"Dao Dinh Kha, Masatoshi Yoshikawa, Shunsuke Uemura","doi":"10.1109/ICDE.2001.914843","DOIUrl":"https://doi.org/10.1109/ICDE.2001.914843","url":null,"abstract":"For most of the index structures for XML data proposed so far, updating is a problem, because an XML element's coordinates are expressed using absolute values. Due to the structural relationship among the elements in XML documents, we have to re-compute these absolute values if the content of the source data is updated. The reconstruction requires the updating of a large portion of the index files, which causes a serious problem, especially when the XML data content is updated frequently. In this paper, we propose an indexing structure scheme based on the relative region coordinates that can effectively deal with the update problem. The main idea is that we express the coordinates of an XML element based on the region of its parent element. We present an algorithm to construct a tree-structured index in which related coordinates are stored together. In consequence, our indexing scheme requires the updating of only a small portion of the index file.","PeriodicalId":431818,"journal":{"name":"Proceedings 17th International Conference on Data Engineering","volume":"16 1-2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120924351","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 : 2001-04-02DOI: 10.1109/ICDE.2001.914870
N. Mittal, Hui-I Hsiao
Relational DBMSs (RDBMSs) have evolved to an extent that they are used to manage almost all traditional business data in a robust fashion. Nevertheless, a large fraction of unstructured and semi-structured data continues to be managed by file systems. As companies increasingly depend on non-traditional data for their daily business operations, it becomes more and more important to provide higher degree of integrity, security and reliability to the data stored in file systems. DataLinks technology, developed at IBM Almaden Research Center, achieves this by providing a vital integration between a RDBMS and a file system. It enables the DBMS to manage files residing in file systems as though they are logically within the database. Current DataLinks technology supports only read access to external files that are being managed by the DBMS. This severely restricts the applicability of DataLinks technology in transaction-oriented and/or e-business applications. Traditional database systems enforce ACID properties for database updates. Extending these properties to cover both external files stored outside of a DBMS and metadata stored in the DBMS is a hard problem. This is because files are updated through a standard file-system API while metadata, which references the files, is updated through a database API. This paper describes our experiences in the design and prototyping of an advanced DataLinks technology that supports database-managed external file updates. This enhanced capability makes DataLinks technology an even more attractive solution for managing the world's data.
{"title":"Database managed external file update","authors":"N. Mittal, Hui-I Hsiao","doi":"10.1109/ICDE.2001.914870","DOIUrl":"https://doi.org/10.1109/ICDE.2001.914870","url":null,"abstract":"Relational DBMSs (RDBMSs) have evolved to an extent that they are used to manage almost all traditional business data in a robust fashion. Nevertheless, a large fraction of unstructured and semi-structured data continues to be managed by file systems. As companies increasingly depend on non-traditional data for their daily business operations, it becomes more and more important to provide higher degree of integrity, security and reliability to the data stored in file systems. DataLinks technology, developed at IBM Almaden Research Center, achieves this by providing a vital integration between a RDBMS and a file system. It enables the DBMS to manage files residing in file systems as though they are logically within the database. Current DataLinks technology supports only read access to external files that are being managed by the DBMS. This severely restricts the applicability of DataLinks technology in transaction-oriented and/or e-business applications. Traditional database systems enforce ACID properties for database updates. Extending these properties to cover both external files stored outside of a DBMS and metadata stored in the DBMS is a hard problem. This is because files are updated through a standard file-system API while metadata, which references the files, is updated through a database API. This paper describes our experiences in the design and prototyping of an advanced DataLinks technology that supports database-managed external file updates. This enhanced capability makes DataLinks technology an even more attractive solution for managing the world's data.","PeriodicalId":431818,"journal":{"name":"Proceedings 17th International Conference on Data Engineering","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126802090","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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