Barzan Mozafari, Kai Zeng, Loris D'antoni, C. Zaniolo
While Complex Event Processing (CEP) constitutes a considerable portion of the so-called Big Data analytics, current CEP systems can only process data having a simple structure, and are otherwise limited in their ability to efficiently support complex continuous queries on structured or semistructured information. However, XML-like streams represent a very popular form of data exchange, comprising large portions of social network and RSS feeds, financial feeds, configuration files, and similar applications requiring advanced CEP queries. In this article, we present the XSeq language and system that support CEP on XML streams, via an extension of XPath that is both powerful and amenable to an efficient implementation. Specifically, the XSeq language extends XPath with natural operators to express sequential and Kleene-* patterns over XML streams, while remaining highly amenable to efficient execution. In fact, XSeq is designed to take full advantage of the recently proposed Visibly Pushdown Automata (VPA), where higher expressive power can be achieved without compromising the computationally attractive properties of finite state automata. Besides the efficiency and expressivity benefits, the choice of VPA as the underlying model also enables XSeq to go beyond XML streams and be easily applicable to any data with both sequential and hierarchical structures, including JSON messages, RNA sequences, and software traces. Therefore, we illustrate the XSeq's power for CEP applications through examples from different domains and provide formal results on its expressiveness and complexity. Finally, we present several optimization techniques for XSeq queries. Our extensive experiments indicate that XSeq brings outstanding performance to CEP applications: two orders of magnitude improvement is obtained over the same queries executed in general-purpose XML engines.
{"title":"High-performance complex event processing over hierarchical data","authors":"Barzan Mozafari, Kai Zeng, Loris D'antoni, C. Zaniolo","doi":"10.1145/2536779","DOIUrl":"https://doi.org/10.1145/2536779","url":null,"abstract":"While Complex Event Processing (CEP) constitutes a considerable portion of the so-called Big Data analytics, current CEP systems can only process data having a simple structure, and are otherwise limited in their ability to efficiently support complex continuous queries on structured or semistructured information. However, XML-like streams represent a very popular form of data exchange, comprising large portions of social network and RSS feeds, financial feeds, configuration files, and similar applications requiring advanced CEP queries. In this article, we present the XSeq language and system that support CEP on XML streams, via an extension of XPath that is both powerful and amenable to an efficient implementation. Specifically, the XSeq language extends XPath with natural operators to express sequential and Kleene-* patterns over XML streams, while remaining highly amenable to efficient execution. In fact, XSeq is designed to take full advantage of the recently proposed Visibly Pushdown Automata (VPA), where higher expressive power can be achieved without compromising the computationally attractive properties of finite state automata. Besides the efficiency and expressivity benefits, the choice of VPA as the underlying model also enables XSeq to go beyond XML streams and be easily applicable to any data with both sequential and hierarchical structures, including JSON messages, RNA sequences, and software traces. Therefore, we illustrate the XSeq's power for CEP applications through examples from different domains and provide formal results on its expressiveness and complexity. Finally, we present several optimization techniques for XSeq queries. Our extensive experiments indicate that XSeq brings outstanding performance to CEP applications: two orders of magnitude improvement is obtained over the same queries executed in general-purpose XML engines.","PeriodicalId":50915,"journal":{"name":"ACM Transactions on Database Systems","volume":"11 1","pages":"21"},"PeriodicalIF":1.8,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75550230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Andrés Letelier, Jorge Pérez, R. Pichler, Sebastian Skritek
Static analysis is a fundamental task in query optimization. In this article we study static analysis and optimization techniques for SPARQL, which is the standard language for querying Semantic Web data. Of particular interest for us is the optionality feature in SPARQL. It is crucial in Semantic Web data management, where data sources are inherently incomplete and the user is usually interested in partial answers to queries. This feature is one of the most complicated constructors in SPARQL and also the one that makes this language depart from classical query languages such as relational conjunctive queries. We focus on the class of well-designed SPARQL queries, which has been proposed in the literature as a fragment of the language with good properties regarding query evaluation. We first propose a tree representation for SPARQL queries, called pattern trees, which captures the class of well-designed SPARQL graph patterns. Among other results, we propose several rules that can be used to transform pattern trees into a simple normal form, and study equivalence and containment. We also study the evaluation and enumeration problems for this class of queries.
{"title":"Static analysis and optimization of semantic web queries","authors":"Andrés Letelier, Jorge Pérez, R. Pichler, Sebastian Skritek","doi":"10.1145/2500130","DOIUrl":"https://doi.org/10.1145/2500130","url":null,"abstract":"Static analysis is a fundamental task in query optimization. In this article we study static analysis and optimization techniques for SPARQL, which is the standard language for querying Semantic Web data. Of particular interest for us is the optionality feature in SPARQL. It is crucial in Semantic Web data management, where data sources are inherently incomplete and the user is usually interested in partial answers to queries. This feature is one of the most complicated constructors in SPARQL and also the one that makes this language depart from classical query languages such as relational conjunctive queries. We focus on the class of well-designed SPARQL queries, which has been proposed in the literature as a fragment of the language with good properties regarding query evaluation. We first propose a tree representation for SPARQL queries, called pattern trees, which captures the class of well-designed SPARQL graph patterns. Among other results, we propose several rules that can be used to transform pattern trees into a simple normal form, and study equivalence and containment. We also study the evaluation and enumeration problems for this class of queries.","PeriodicalId":50915,"journal":{"name":"ACM Transactions on Database Systems","volume":"58 1","pages":"25"},"PeriodicalIF":1.8,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78473638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Sarma, Hongrae Lee, Hector Gonzalez, J. Madhavan, A. Halevy
Large-scale map visualization systems play an increasingly important role in presenting geographic datasets to end-users. Since these datasets can be extremely large, a map rendering system often needs to select a small fraction of the data to visualize them in a limited space. This article addresses the fundamental challenge of thinning: determining appropriate samples of data to be shown on specific geographical regions and zoom levels. Other than the sheer scale of the data, the thinning problem is challenging because of a number of other reasons: (1) data can consist of complex geographical shapes, (2) rendering of data needs to satisfy certain constraints, such as data being preserved across zoom levels and adjacent regions, and (3) after satisfying the constraints, an optimal solution needs to be chosen based on objectives such as maximality, fairness, and importance of data. This article formally defines and presents a complete solution to the thinning problem. First, we express the problem as an integer programming formulation that efficiently solves thinning for desired objectives. Second, we present more efficient solutions for maximality, based on DFS traversal of a spatial tree. Third, we consider the common special case of point datasets, and present an even more efficient randomized algorithm. Fourth, we show that contiguous regions are tractable for a general version of maximality for which arbitrary regions are intractable. Fifth, we examine the structure of our integer programming formulation and show that for point datasets, our program is integral. Finally, we have implemented all techniques from this article in Google Maps [Google 2005] visualizations of fusion tables [Gonzalez et al. 2010], and we describe a set of experiments that demonstrate the trade-offs among the algorithms.
大规模地图可视化系统在向最终用户呈现地理数据集方面发挥着越来越重要的作用。由于这些数据集可能非常大，因此地图渲染系统通常需要在有限的空间中选择一小部分数据来可视化它们。本文解决了细化的基本挑战:确定要在特定地理区域和缩放级别上显示的适当数据样本。除了数据的绝对规模之外，细化问题具有挑战性，因为许多其他原因:(1)数据可能由复杂的地理形状组成，(2)数据的呈现需要满足某些约束，例如跨缩放级别和相邻区域保存的数据，以及(3)在满足约束之后，需要根据数据的最大化，公平性和重要性等目标选择最优解决方案。本文正式定义并提出了细化问题的完整解决方案。首先，我们将问题表示为一个整数规划公式，有效地解决了期望目标的细化问题。其次，我们提出了基于空间树的DFS遍历的更有效的最大化解决方案。第三，我们考虑了点数据集的常见特殊情况，并提出了一种更有效的随机化算法。第四，我们证明了对于任意区域难以处理的最大值的一般版本，连续区域是可处理的。第五，我们检查了我们的整数规划公式的结构，并表明对于点数据集，我们的程序是积分的。最后，我们在谷歌地图[Google 2005]融合表可视化[Gonzalez et al. 2010]中实现了本文中的所有技术，并描述了一组实验，展示了算法之间的权衡。
{"title":"Consistent thinning of large geographical data for map visualization","authors":"A. Sarma, Hongrae Lee, Hector Gonzalez, J. Madhavan, A. Halevy","doi":"10.1145/2539032.2539034","DOIUrl":"https://doi.org/10.1145/2539032.2539034","url":null,"abstract":"Large-scale map visualization systems play an increasingly important role in presenting geographic datasets to end-users. Since these datasets can be extremely large, a map rendering system often needs to select a small fraction of the data to visualize them in a limited space. This article addresses the fundamental challenge of thinning: determining appropriate samples of data to be shown on specific geographical regions and zoom levels. Other than the sheer scale of the data, the thinning problem is challenging because of a number of other reasons: (1) data can consist of complex geographical shapes, (2) rendering of data needs to satisfy certain constraints, such as data being preserved across zoom levels and adjacent regions, and (3) after satisfying the constraints, an optimal solution needs to be chosen based on objectives such as maximality, fairness, and importance of data.\u0000 This article formally defines and presents a complete solution to the thinning problem. First, we express the problem as an integer programming formulation that efficiently solves thinning for desired objectives. Second, we present more efficient solutions for maximality, based on DFS traversal of a spatial tree. Third, we consider the common special case of point datasets, and present an even more efficient randomized algorithm. Fourth, we show that contiguous regions are tractable for a general version of maximality for which arbitrary regions are intractable. Fifth, we examine the structure of our integer programming formulation and show that for point datasets, our program is integral. Finally, we have implemented all techniques from this article in Google Maps [Google 2005] visualizations of fusion tables [Gonzalez et al. 2010], and we describe a set of experiments that demonstrate the trade-offs among the algorithms.","PeriodicalId":50915,"journal":{"name":"ACM Transactions on Database Systems","volume":"38 1","pages":"22"},"PeriodicalIF":1.8,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78969822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We study the problem of validating XML documents of size N against general DTDs in the context of streaming algorithms. The starting point of this work is a well-known space lower bound. There are XML documents and DTDs for which p-pass streaming algorithms require Ω(N/p) space. We show that when allowing access to external memory, there is a deterministic streaming algorithm that solves this problem with memory space &Order;(log2 N), a constant number of auxiliary read/write streams, and &Order;(log N) total number of passes on the XML document and auxiliary streams. An important intermediate step of this algorithm is the computation of the First-Child-Next-Sibling (FCNS) encoding of the initial XML document in a streaming fashion. We study this problem independently, and we also provide memory-efficient streaming algorithms for decoding an XML document given in its FCNS encoding. Furthermore, validating XML documents encoding binary trees against any DTD in the usual streaming model without external memory can be done with sublinear memory. There is a one-pass algorithm using &Order;(√N log N) space, and a bidirectional two-pass algorithm using &Order;(log2 N) space which perform this task.
{"title":"Validating XML documents in the streaming model with external memory","authors":"C. Konrad, F. Magniez","doi":"10.1145/2504590","DOIUrl":"https://doi.org/10.1145/2504590","url":null,"abstract":"We study the problem of validating XML documents of size N against general DTDs in the context of streaming algorithms. The starting point of this work is a well-known space lower bound. There are XML documents and DTDs for which p-pass streaming algorithms require Ω(N/p) space. We show that when allowing access to external memory, there is a deterministic streaming algorithm that solves this problem with memory space &Order;(log2 N), a constant number of auxiliary read/write streams, and &Order;(log N) total number of passes on the XML document and auxiliary streams. An important intermediate step of this algorithm is the computation of the First-Child-Next-Sibling (FCNS) encoding of the initial XML document in a streaming fashion. We study this problem independently, and we also provide memory-efficient streaming algorithms for decoding an XML document given in its FCNS encoding. Furthermore, validating XML documents encoding binary trees against any DTD in the usual streaming model without external memory can be done with sublinear memory. There is a one-pass algorithm using &Order;(√N log N) space, and a bidirectional two-pass algorithm using &Order;(log2 N) space which perform this task.","PeriodicalId":50915,"journal":{"name":"ACM Transactions on Database Systems","volume":"29 1","pages":"27"},"PeriodicalIF":1.8,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89108634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
P. Agarwal, Graham Cormode, Zengfeng Huang, J. M. Phillips, Zhewei Wei, K. Yi
We study the mergeability of data summaries. Informally speaking, mergeability requires that, given two summaries on two datasets, there is a way to merge the two summaries into a single summary on the two datasets combined together, while preserving the error and size guarantees. This property means that the summaries can be merged in a way akin to other algebraic operators such as sum and max, which is especially useful for computing summaries on massive distributed data. Several data summaries are trivially mergeable by construction, most notably all the sketches that are linear functions of the datasets. But some other fundamental ones, like those for heavy hitters and quantiles, are not (known to be) mergeable. In this article, we demonstrate that these summaries are indeed mergeable or can be made mergeable after appropriate modifications. Specifically, we show that for ϵ-approximate heavy hitters, there is a deterministic mergeable summary of size O(1/ϵ); for ϵ-approximate quantiles, there is a deterministic summary of size O((1/ϵ) log(ϵ n)) that has a restricted form of mergeability, and a randomized one of size O((1/ϵ) log3/2(1/ϵ)) with full mergeability. We also extend our results to geometric summaries such as ϵ-approximations which permit approximate multidimensional range counting queries. While most of the results in this article are theoretical in nature, some of the algorithms are actually very simple and even perform better than the previously best known algorithms, which we demonstrate through experiments in a simulated sensor network. We also achieve two results of independent interest: (1) we provide the best known randomized streaming bound for ϵ-approximate quantiles that depends only on ϵ, of size O((1/ϵ) log3/2(1/ϵ)), and (2) we demonstrate that the MG and the SpaceSaving summaries for heavy hitters are isomorphic.
{"title":"Mergeable summaries","authors":"P. Agarwal, Graham Cormode, Zengfeng Huang, J. M. Phillips, Zhewei Wei, K. Yi","doi":"10.1145/2500128","DOIUrl":"https://doi.org/10.1145/2500128","url":null,"abstract":"We study the mergeability of data summaries. Informally speaking, mergeability requires that, given two summaries on two datasets, there is a way to merge the two summaries into a single summary on the two datasets combined together, while preserving the error and size guarantees. This property means that the summaries can be merged in a way akin to other algebraic operators such as sum and max, which is especially useful for computing summaries on massive distributed data. Several data summaries are trivially mergeable by construction, most notably all the sketches that are linear functions of the datasets. But some other fundamental ones, like those for heavy hitters and quantiles, are not (known to be) mergeable. In this article, we demonstrate that these summaries are indeed mergeable or can be made mergeable after appropriate modifications. Specifically, we show that for ϵ-approximate heavy hitters, there is a deterministic mergeable summary of size O(1/ϵ); for ϵ-approximate quantiles, there is a deterministic summary of size O((1/ϵ) log(ϵ n)) that has a restricted form of mergeability, and a randomized one of size O((1/ϵ) log3/2(1/ϵ)) with full mergeability. We also extend our results to geometric summaries such as ϵ-approximations which permit approximate multidimensional range counting queries. While most of the results in this article are theoretical in nature, some of the algorithms are actually very simple and even perform better than the previously best known algorithms, which we demonstrate through experiments in a simulated sensor network.\u0000 We also achieve two results of independent interest: (1) we provide the best known randomized streaming bound for ϵ-approximate quantiles that depends only on ϵ, of size O((1/ϵ) log3/2(1/ϵ)), and (2) we demonstrate that the MG and the SpaceSaving summaries for heavy hitters are isomorphic.","PeriodicalId":50915,"journal":{"name":"ACM Transactions on Database Systems","volume":"9 1","pages":"26"},"PeriodicalIF":1.8,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87896232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Bonifati, M. Goodfellow, I. Manolescu, Domenica Sileo
Materialized views can bring important performance benefits when querying XML documents. In the presence of XML document changes, materialized views need to be updated to faithfully reflect the changed document. In this work, we present an algebraic approach for propagating source updates to XML materialized views expressed in a powerful XML tree pattern formalism. Our approach differs from the state-of-the-art in the area in two important ways. First, it relies on set-oriented, algebraic operations, to be contrasted with node-based previous approaches. Second, it exploits state-of-the-art features of XML stores and XML query evaluation engines, notably XML structural identifiers and associated structural join algorithms. We present algorithms for determining how updates should be propagated to views, and highlight the benefits of our approach over existing algorithms through a series of experiments.
{"title":"Algebraic incremental maintenance of XML views","authors":"A. Bonifati, M. Goodfellow, I. Manolescu, Domenica Sileo","doi":"10.1145/2508020.2508021","DOIUrl":"https://doi.org/10.1145/2508020.2508021","url":null,"abstract":"Materialized views can bring important performance benefits when querying XML documents. In the presence of XML document changes, materialized views need to be updated to faithfully reflect the changed document. In this work, we present an algebraic approach for propagating source updates to XML materialized views expressed in a powerful XML tree pattern formalism. Our approach differs from the state-of-the-art in the area in two important ways. First, it relies on set-oriented, algebraic operations, to be contrasted with node-based previous approaches. Second, it exploits state-of-the-art features of XML stores and XML query evaluation engines, notably XML structural identifiers and associated structural join algorithms. We present algorithms for determining how updates should be propagated to views, and highlight the benefits of our approach over existing algorithms through a series of experiments.","PeriodicalId":50915,"journal":{"name":"ACM Transactions on Database Systems","volume":"11 1","pages":"14"},"PeriodicalIF":1.8,"publicationDate":"2013-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76420974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Graph pattern matching is commonly used in a variety of emerging applications such as social network analysis. These applications highlight the need for studying the following two issues. First, graph pattern matching is traditionally defined in terms of subgraph isomorphism or graph simulation. These notions, however, often impose too strong a topological constraint on graphs to identify meaningful matches. Second, in practice a graph is typically large, and is frequently updated with small changes. It is often prohibitively expensive to recompute matches starting from scratch via batch algorithms when the graph is updated. This article studies these two issues. (1) We propose to define graph pattern matching based on a notion of bounded simulation, which extends graph simulation by specifying the connectivity of nodes in a graph within a predefined number of hops. We show that bounded simulation is able to find sensible matches that the traditional matching notions fail to catch. We also show that matching via bounded simulation is in cubic time, by giving such an algorithm. (2) We provide an account of results on incremental graph pattern matching, for matching defined with graph simulation, bounded simulation, and subgraph isomorphism. We show that the incremental matching problem is unbounded, that is, its cost is not determined alone by the size of the changes in the input and output, for all these matching notions. Nonetheless, when matching is defined in terms of simulation or bounded simulation, incremental matching is semibounded, that is, its worst-time complexity is bounded by a polynomial in the size of the changes in the input, output, and auxiliary information that is necessarily maintained to reuse previous computation, and the size of graph patterns. We also develop incremental matching algorithms for graph simulation and bounded simulation, by minimizing unnecessary recomputation. In contrast, matching based on subgraph isomorphism is neither bounded nor semibounded. (3) We experimentally verify the effectiveness and efficiency of these algorithms, and show that: (a) the revised notion of graph pattern matching allows us to identify communities commonly found in real-life networks, and (b) the incremental algorithms substantially outperform their batch counterparts in response to small changes. These suggest a promising framework for real-life graph pattern matching.
{"title":"Incremental graph pattern matching","authors":"Wenfei Fan, Xin Wang, Yinghui Wu","doi":"10.1145/2489791","DOIUrl":"https://doi.org/10.1145/2489791","url":null,"abstract":"Graph pattern matching is commonly used in a variety of emerging applications such as social network analysis. These applications highlight the need for studying the following two issues. First, graph pattern matching is traditionally defined in terms of subgraph isomorphism or graph simulation. These notions, however, often impose too strong a topological constraint on graphs to identify meaningful matches. Second, in practice a graph is typically large, and is frequently updated with small changes. It is often prohibitively expensive to recompute matches starting from scratch via batch algorithms when the graph is updated.\u0000 This article studies these two issues. (1) We propose to define graph pattern matching based on a notion of bounded simulation, which extends graph simulation by specifying the connectivity of nodes in a graph within a predefined number of hops. We show that bounded simulation is able to find sensible matches that the traditional matching notions fail to catch. We also show that matching via bounded simulation is in cubic time, by giving such an algorithm. (2) We provide an account of results on incremental graph pattern matching, for matching defined with graph simulation, bounded simulation, and subgraph isomorphism. We show that the incremental matching problem is unbounded, that is, its cost is not determined alone by the size of the changes in the input and output, for all these matching notions. Nonetheless, when matching is defined in terms of simulation or bounded simulation, incremental matching is semibounded, that is, its worst-time complexity is bounded by a polynomial in the size of the changes in the input, output, and auxiliary information that is necessarily maintained to reuse previous computation, and the size of graph patterns. We also develop incremental matching algorithms for graph simulation and bounded simulation, by minimizing unnecessary recomputation. In contrast, matching based on subgraph isomorphism is neither bounded nor semibounded. (3) We experimentally verify the effectiveness and efficiency of these algorithms, and show that: (a) the revised notion of graph pattern matching allows us to identify communities commonly found in real-life networks, and (b) the incremental algorithms substantially outperform their batch counterparts in response to small changes. These suggest a promising framework for real-life graph pattern matching.","PeriodicalId":50915,"journal":{"name":"ACM Transactions on Database Systems","volume":"8 1","pages":"18"},"PeriodicalIF":1.8,"publicationDate":"2013-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85079316","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Justin J. Levandoski, A. Eldawy, M. Mokbel, Mohamed E. Khalefa
Personalized database systems give users answers tailored to their personal preferences. While numerous preference evaluation methods for databases have been proposed (e.g., skyline, top-k, k-dominance, k-frequency), the implementation of these methods at the core of a database system is a double-edged sword. Core implementation provides efficient query processing for arbitrary database queries, however, this approach is not practical since each existing (and future) preference method requires implementation within the database engine. To solve this problem, this article introduces FlexPref, a framework for extensible preference evaluation in database systems. FlexPref, implemented in the query processor, aims to support a wide array of preference evaluation methods in a single extensible code base. Integration with FlexPref is simple, involving the registration of only three functions that capture the essence of the preference method. Once integrated, the preference method “lives” at the core of the database, enabling the efficient execution of preference queries involving common database operations. This article also provides a query optimization framework for FlexPref, as well as a theoretical framework that defines the properties a preference method must exhibit to be implemented in FlexPref. To demonstrate the extensibility of FlexPref, this article also provides case studies detailing the implementation of seven state-of-the-art preference evaluation methods within FlexPref. We also experimentally study the strengths and weaknesses of an implementation of FlexPref in PostgreSQL over a range of single-table and multitable preference queries.
{"title":"Flexible and extensible preference evaluation in database systems","authors":"Justin J. Levandoski, A. Eldawy, M. Mokbel, Mohamed E. Khalefa","doi":"10.1145/2493268","DOIUrl":"https://doi.org/10.1145/2493268","url":null,"abstract":"Personalized database systems give users answers tailored to their personal preferences. While numerous preference evaluation methods for databases have been proposed (e.g., skyline, top-k, k-dominance, k-frequency), the implementation of these methods at the core of a database system is a double-edged sword. Core implementation provides efficient query processing for arbitrary database queries, however, this approach is not practical since each existing (and future) preference method requires implementation within the database engine. To solve this problem, this article introduces FlexPref, a framework for extensible preference evaluation in database systems. FlexPref, implemented in the query processor, aims to support a wide array of preference evaluation methods in a single extensible code base. Integration with FlexPref is simple, involving the registration of only three functions that capture the essence of the preference method. Once integrated, the preference method “lives” at the core of the database, enabling the efficient execution of preference queries involving common database operations. This article also provides a query optimization framework for FlexPref, as well as a theoretical framework that defines the properties a preference method must exhibit to be implemented in FlexPref. To demonstrate the extensibility of FlexPref, this article also provides case studies detailing the implementation of seven state-of-the-art preference evaluation methods within FlexPref. We also experimentally study the strengths and weaknesses of an implementation of FlexPref in PostgreSQL over a range of single-table and multitable preference queries.","PeriodicalId":50915,"journal":{"name":"ACM Transactions on Database Systems","volume":"40 1","pages":"17"},"PeriodicalIF":1.8,"publicationDate":"2013-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89286713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
G. Karvounarakis, Todd J. Green, Z. Ives, V. Tannen
Recent work [Ives et al. 2005] proposed a new class of systems for supporting data sharing among scientific and other collaborations: this new collaborative data sharing system connects heterogeneous logical peers using a network of schema mappings. Each peer has a locally controlled and edited database instance, but wants to incorporate related data from other peers as well. To achieve this, every peer's data and updates propagate along the mappings to the other peers. However, this operation, termed update exchange, is filtered by trust conditions—expressing what data and sources a peer judges to be authoritative—which may cause a peer to reject another's updates. In order to support such filtering, updates carry provenance information. This article develops methods for realizing such systems: we build upon techniques from data integration, data exchange, incremental view maintenance, and view update to propagate updates along mappings, both to derived and optionally to source instances. We incorporate a novel model for tracking data provenance, such that curators may filter updates based on trust conditions over this provenance. We implement our techniques in a layer above an off-the-shelf RDBMS, and we experimentally demonstrate the viability of these techniques in the Orchestra prototype system.
最近的工作[Ives et al. 2005]提出了一类新的系统，用于支持科学和其他协作之间的数据共享:这种新的协作数据共享系统使用模式映射网络连接异构逻辑对等体。每个对等点都有一个本地控制和编辑的数据库实例，但也希望合并来自其他对等点的相关数据。为了实现这一点，每个对等点的数据和更新沿着映射传播到其他对等点。然而，这种称为更新交换的操作是通过信任条件(表示对等方判断哪些数据和数据源是权威的)过滤的，这可能导致对等方拒绝另一方的更新。为了支持这种过滤，更新带有来源信息。本文开发了实现这类系统的方法:我们建立在数据集成、数据交换、增量视图维护和视图更新等技术的基础上，以沿着映射将更新传播到派生实例和可选的源实例。我们采用了一种新颖的模型来跟踪数据来源，这样管理员就可以根据对该来源的信任条件过滤更新。我们在一个现成的RDBMS之上的一层实现了我们的技术，并且我们通过实验证明了这些技术在Orchestra原型系统中的可行性。
{"title":"Collaborative data sharing via update exchange and provenance","authors":"G. Karvounarakis, Todd J. Green, Z. Ives, V. Tannen","doi":"10.1145/2500127","DOIUrl":"https://doi.org/10.1145/2500127","url":null,"abstract":"Recent work [Ives et al. 2005] proposed a new class of systems for supporting data sharing among scientific and other collaborations: this new collaborative data sharing system connects heterogeneous logical peers using a network of schema mappings. Each peer has a locally controlled and edited database instance, but wants to incorporate related data from other peers as well. To achieve this, every peer's data and updates propagate along the mappings to the other peers. However, this operation, termed update exchange, is filtered by trust conditions—expressing what data and sources a peer judges to be authoritative—which may cause a peer to reject another's updates. In order to support such filtering, updates carry provenance information.\u0000 This article develops methods for realizing such systems: we build upon techniques from data integration, data exchange, incremental view maintenance, and view update to propagate updates along mappings, both to derived and optionally to source instances. We incorporate a novel model for tracking data provenance, such that curators may filter updates based on trust conditions over this provenance. We implement our techniques in a layer above an off-the-shelf RDBMS, and we experimentally demonstrate the viability of these techniques in the Orchestra prototype system.","PeriodicalId":50915,"journal":{"name":"ACM Transactions on Database Systems","volume":"146 1","pages":"19"},"PeriodicalIF":1.8,"publicationDate":"2013-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79948417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Dario Colazzo, G. Ghelli, Luca Pardini, C. Sartiani
Type inclusion is a fundamental operation in every type-checking compiler, but it is quite expensive for XML manipulation languages. A polynomial inclusion checking algorithm for an expressive family of XML type languages is known, but it runs in quadratic time both in the best and in the worst cases. We present here an algorithm that has a linear-time backbone, and resorts to the quadratic approach for some specific parts of the compared types. Our experiments show that the new algorithm is much faster than the quadratic one, and that it typically runs in linear time, hence it can be used as a building block for a practical type-checking compiler.
{"title":"Almost-linear inclusion for XML regular expression types","authors":"Dario Colazzo, G. Ghelli, Luca Pardini, C. Sartiani","doi":"10.1145/2508020.2508022","DOIUrl":"https://doi.org/10.1145/2508020.2508022","url":null,"abstract":"Type inclusion is a fundamental operation in every type-checking compiler, but it is quite expensive for XML manipulation languages. A polynomial inclusion checking algorithm for an expressive family of XML type languages is known, but it runs in quadratic time both in the best and in the worst cases. We present here an algorithm that has a linear-time backbone, and resorts to the quadratic approach for some specific parts of the compared types. Our experiments show that the new algorithm is much faster than the quadratic one, and that it typically runs in linear time, hence it can be used as a building block for a practical type-checking compiler.","PeriodicalId":50915,"journal":{"name":"ACM Transactions on Database Systems","volume":"33 1","pages":"15"},"PeriodicalIF":1.8,"publicationDate":"2013-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89201595","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：