In em monotone classification, the input is a set P of n points in d-dimensional space, where each point carries a label 0 or 1. A point p em dominates another point q if the coordinate of p is at least that of q on every dimension. A em monotone classifier is a function h mapping each d-dimensional point to $0, 1 $, subject to the condition that $h(p) ge h(q)$ holds whenever p dominates q. The classifier h em mis-classifies a point $p in P$ if $h(p)$ is different from the label of p. The em error of h is the number of points in P mis-classified by h. The objective is to find a monotone classifier with a small error. The problem is fundamental to numerous database applications in entity matching, record linkage, and duplicate detection. This paper studies two variants of the problem. In the first em active version, all the labels are hidden in the beginning; an algorithm must pay a unit cost to em probe (i.e., reveal) the label of a point in P. We prove that $Ømega(n)$ probes are necessary to find an optimal classifier even in one-dimensional space ($d=1$). On the other hand, given an arbitrary $eps > 0$, we show how to obtain (with high probability) a monotone classifier whose error is worse than the optimum by at most a $1 + eps$ factor, while probing $tO(w/eps^2)$ labels, where w is the dominance width of P and $tO(.)$ hides a polylogarithmic factor. For constant $eps$, the probing cost matches an existing lower bound up to an $tO(1)$ factor. In the second em passive version, the point labels in P are explicitly given; the goal is to minimize CPU computation in finding an optimal classifier. We show that the problem can be settled in time polynomial to both d and n.
在单调分类中，输入是d维空间中n个点的集合P，其中每个点带有一个标签0或1。点p em优于另一个点q，如果p的坐标在每个维度上至少是q的坐标。一个em单调分类器是一个函数h，将每个d维点映射到$ 0,1 $，条件是当p优于q时，$h(p) ge h(q)$成立。如果$h(p)$与p的标签不同，分类器h em对p $中的点$p 进行错误分类。h的em误差是p中被h错误分类的点的数量。目标是找到一个误差小的单调分类器。这个问题是实体匹配、记录链接和重复检测中许多数据库应用程序的基础。本文研究了该问题的两个变体。在第一个em活动版本中，所有标签都隐藏在开始;我们证明了$Ømega(n)$探针对于找到最优分类器是必要的，即使在一维空间($d=1$)中。另一方面，给定任意$eps > 0$，我们展示了如何(以高概率)获得一个单调分类器，其误差最多比最优值差$1 + eps$因子，同时探测$ to (w/eps^2)$标签，其中w是P的优势宽度，$ to(.)$隐藏了一个多对数因子。对于常数$eps$，探测成本匹配到$ to(1)$因子的现有下界。在第二个被动版本中，P中的点标签被显式给出;目标是在寻找最优分类器时最小化CPU计算。我们证明了这个问题可以用d和n的时间多项式来解决。
{"title":"New Algorithms for Monotone Classification","authors":"Yufei Tao, Yu Wang","doi":"10.1145/3452021.3458324","DOIUrl":"https://doi.org/10.1145/3452021.3458324","url":null,"abstract":"In em monotone classification, the input is a set P of n points in d-dimensional space, where each point carries a label 0 or 1. A point p em dominates another point q if the coordinate of p is at least that of q on every dimension. A em monotone classifier is a function h mapping each d-dimensional point to $0, 1 $, subject to the condition that $h(p) ge h(q)$ holds whenever p dominates q. The classifier h em mis-classifies a point $p in P$ if $h(p)$ is different from the label of p. The em error of h is the number of points in P mis-classified by h. The objective is to find a monotone classifier with a small error. The problem is fundamental to numerous database applications in entity matching, record linkage, and duplicate detection. This paper studies two variants of the problem. In the first em active version, all the labels are hidden in the beginning; an algorithm must pay a unit cost to em probe (i.e., reveal) the label of a point in P. We prove that $Ømega(n)$ probes are necessary to find an optimal classifier even in one-dimensional space ($d=1$). On the other hand, given an arbitrary $eps > 0$, we show how to obtain (with high probability) a monotone classifier whose error is worse than the optimum by at most a $1 + eps$ factor, while probing $tO(w/eps^2)$ labels, where w is the dominance width of P and $tO(.)$ hides a polylogarithmic factor. For constant $eps$, the probing cost matches an existing lower bound up to an $tO(1)$ factor. In the second em passive version, the point labels in P are explicitly given; the goal is to minimize CPU computation in finding an optimal classifier. We show that the problem can be settled in time polynomial to both d and n.","PeriodicalId":405398,"journal":{"name":"Proceedings of the 40th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129858584","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}
One of the greatest successes of computational complexity theory is the classification of countless fundamental computational problems into polynomial-time and NP-hard ones, two classes that are often referred to as tractable and intractable, respectively. However, this crude distinction of algorithmic efficiency is clearly insufficient when handling today's large scale of data. We need a finer-grained design and analysis of algorithms that pinpoints the exact exponent of polynomial running time, and a better understanding of when a speed-up is not possible. Based on stronger complexity assumptions than P vs NP, like the Strong Exponential Time Hypothesis, recently conditional lower bounds for a variety of fundamental problems in P have been proposed. Unfortunately, these conditional lower bounds often break down when one may settle for a near-optimal solution. Indeed, approximation algorithms can play a significant role when designing fast algorithms not just for traditional NP Hard problems, but also for polynomial time problems. For some applications arising in machine learning, the time complexity of the underlying algorithms is not sufficient to ensure a fast solution. It is often needed to collect side information about the data to ensure high accuracy. This requires low query complexity. In this presentation, we will cover new facets of fast algorithm design for large scale data analysis that emphasizes on the role of developing approximation algorithms for better polynomial time/query complexity.
计算复杂性理论最大的成功之一是将无数的基本计算问题分类为多项式时间问题和np困难问题，这两类问题通常分别被称为易处理和难处理。然而，在处理今天的大规模数据时，这种对算法效率的粗略区分显然是不够的。我们需要对算法进行更细粒度的设计和分析，以确定多项式运行时间的确切指数，并更好地理解何时不可能进行加速。基于比P vs NP更强的复杂性假设，如强指数时间假设，最近提出了P中各种基本问题的条件下界。不幸的是，这些条件下界往往打破了当一个人可能满足于一个接近最优的解决方案。事实上，近似算法在设计快速算法时可以发挥重要作用，不仅适用于传统的NP困难问题，也适用于多项式时间问题。对于机器学习中出现的一些应用，底层算法的时间复杂度不足以确保快速解决。通常需要收集数据的侧面信息，以确保数据的高准确性。这需要较低的查询复杂度。在本次演讲中，我们将介绍大规模数据分析快速算法设计的新方面，重点是开发近似算法的作用，以提高多项式时间/查询复杂性。
{"title":"Approximation Algorithms for Large Scale Data Analysis","authors":"B. Saha","doi":"10.1145/3452021.3458813","DOIUrl":"https://doi.org/10.1145/3452021.3458813","url":null,"abstract":"One of the greatest successes of computational complexity theory is the classification of countless fundamental computational problems into polynomial-time and NP-hard ones, two classes that are often referred to as tractable and intractable, respectively. However, this crude distinction of algorithmic efficiency is clearly insufficient when handling today's large scale of data. We need a finer-grained design and analysis of algorithms that pinpoints the exact exponent of polynomial running time, and a better understanding of when a speed-up is not possible. Based on stronger complexity assumptions than P vs NP, like the Strong Exponential Time Hypothesis, recently conditional lower bounds for a variety of fundamental problems in P have been proposed. Unfortunately, these conditional lower bounds often break down when one may settle for a near-optimal solution. Indeed, approximation algorithms can play a significant role when designing fast algorithms not just for traditional NP Hard problems, but also for polynomial time problems. For some applications arising in machine learning, the time complexity of the underlying algorithms is not sufficient to ensure a fast solution. It is often needed to collect side information about the data to ensure high accuracy. This requires low query complexity. In this presentation, we will cover new facets of fast algorithm design for large scale data analysis that emphasizes on the role of developing approximation algorithms for better polynomial time/query complexity.","PeriodicalId":405398,"journal":{"name":"Proceedings of the 40th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126640121","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}
This paper presents an algorithm to process a multi-way join with load $tO(n/p^2/(α φ) )$ under the MPC model, where n is the number of tuples in the input relations, α the maximum arity of those relations, p the number of machines, and φ a newly introduced parameter called the em generalized vertex packing number. The algorithm owes to two new findings. The first is a em two-attribute skew free technique to partition the join result for parallel computation. The second is an em isolated cartesian product theorem, which provides fresh graph-theoretic insights on joins with α ge 3$ and generalizes an existing theorem on α = 2$.
本文在MPC模型下提出了一种处理负载$ to (n/p^2/(α φ))$的多路连接的算法，其中n为输入关系中的元组个数，α为这些关系的最大次数，p为机器数量，φ为新引入的参数em广义顶点填充数。该算法得益于两项新发现。第一种是一种无双属性倾斜的技术，用于为并行计算划分连接结果。二是孤立笛卡尔积定理，它提供了关于α = 3$连接的新的图论见解，并推广了关于α = 2$的已有定理。
{"title":"Two-Attribute Skew Free, Isolated CP Theorem, and Massively Parallel Joins","authors":"Miao Qiao, Yufei Tao","doi":"10.1145/3452021.3458321","DOIUrl":"https://doi.org/10.1145/3452021.3458321","url":null,"abstract":"This paper presents an algorithm to process a multi-way join with load $tO(n/p^2/(α φ) )$ under the MPC model, where n is the number of tuples in the input relations, α the maximum arity of those relations, p the number of machines, and φ a newly introduced parameter called the em generalized vertex packing number. The algorithm owes to two new findings. The first is a em two-attribute skew free technique to partition the join result for parallel computation. The second is an em isolated cartesian product theorem, which provides fresh graph-theoretic insights on joins with α ge 3$ and generalizes an existing theorem on α = 2$.","PeriodicalId":405398,"journal":{"name":"Proceedings of the 40th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133465356","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}
This paper considers the worst-case complexity of multi-round join evaluation in the Massively Parallel Computation (MPC) model. Unlike the sequential RAM model, in which there is a unified optimal algorithm based on the AGM bound for all join queries, worst-case optimal algorithms have been achieved on a very restrictive class of joins in the MPC model. The only known lower bound is still derived from the AGM bound, in terms of the optimal fractional edge covering number of the query. In this work, we make efforts towards bridging this gap. We design an instance-dependent algorithm for the class of α-acyclic join queries. In particular, when the maximum size of input relations is bounded, this complexity has a closed form in terms of the optimal fractional edge covering number of the query, which is worst-case optimal. Beyond acyclic joins, we surprisingly find that the optimal fractional edge covering number does not lead to a tight lower bound. More specifically, we prove for a class of cyclic joins a higher lower bound in terms of the optimal fractional edge packing number of the query, which is matched by existing algorithms, thus optimal. This new result displays a significant distinction for join evaluation, not only between acyclic and cyclic joins, but also between the fine-grained RAM and coarse-grained MPC model.
{"title":"Cover or Pack: New Upper and Lower Bounds for Massively Parallel Joins","authors":"Xiao Hu","doi":"10.1145/3452021.3458319","DOIUrl":"https://doi.org/10.1145/3452021.3458319","url":null,"abstract":"This paper considers the worst-case complexity of multi-round join evaluation in the Massively Parallel Computation (MPC) model. Unlike the sequential RAM model, in which there is a unified optimal algorithm based on the AGM bound for all join queries, worst-case optimal algorithms have been achieved on a very restrictive class of joins in the MPC model. The only known lower bound is still derived from the AGM bound, in terms of the optimal fractional edge covering number of the query. In this work, we make efforts towards bridging this gap. We design an instance-dependent algorithm for the class of α-acyclic join queries. In particular, when the maximum size of input relations is bounded, this complexity has a closed form in terms of the optimal fractional edge covering number of the query, which is worst-case optimal. Beyond acyclic joins, we surprisingly find that the optimal fractional edge covering number does not lead to a tight lower bound. More specifically, we prove for a class of cyclic joins a higher lower bound in terms of the optimal fractional edge packing number of the query, which is matched by existing algorithms, thus optimal. This new result displays a significant distinction for join evaluation, not only between acyclic and cyclic joins, but also between the fine-grained RAM and coarse-grained MPC model.","PeriodicalId":405398,"journal":{"name":"Proceedings of the 40th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems","volume":"66 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114125004","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}
S. Kikot, Á. Kurucz, V. Podolskii, M. Zakharyaschev
We show that deciding boundedness (aka FO-rewritability) of monadic single rule datalog programs (sirups) is 2Exp-hard, which matches the upper bound known since 1988 and finally settles a long-standing open problem. We obtain this result as a byproduct of an attempt to classify monadic 'disjunctive sirups'---Boolean conjunctive queries $q$ with unary and binary predicates mediated by a disjunctive rule $T(x) łor F(x) łeftarrow A(x)$---according to the data complexity of their evaluation. Apart from establishing that deciding FO-rewritability of disjunctive sirups with a dag-shaped $q$ is also 2Exp-hard, we make substantial progress towards obtaining a complete FO/Ł-hardness dichotomy of disjunctive sirups with ditree-shaped $q$.
我们证明了一元单规则数据程序(sirups)的有界性(又名fo -可重写性)的判定是2Exp-hard的，它与1988年以来已知的上界相匹配，最终解决了一个长期存在的开放问题。我们获得了这个结果，作为尝试分类一元“析取sirups”的副产品-布尔合取查询$q$与一元和二元谓词由析取规则$T(x) łor F(x) łeftarrow a (x)$调解-根据其评估的数据复杂性。除了证明具有d形$q$的析取小环的FO-可重写性也是2 e-难的之外，我们在获得具有异形$q$的析取小环的完整FO/Ł-hardness二分法方面取得了实质性进展。
{"title":"Deciding Boundedness of Monadic Sirups","authors":"S. Kikot, Á. Kurucz, V. Podolskii, M. Zakharyaschev","doi":"10.1145/3452021.3458332","DOIUrl":"https://doi.org/10.1145/3452021.3458332","url":null,"abstract":"We show that deciding boundedness (aka FO-rewritability) of monadic single rule datalog programs (sirups) is 2Exp-hard, which matches the upper bound known since 1988 and finally settles a long-standing open problem. We obtain this result as a byproduct of an attempt to classify monadic 'disjunctive sirups'---Boolean conjunctive queries $q$ with unary and binary predicates mediated by a disjunctive rule $T(x) łor F(x) łeftarrow A(x)$---according to the data complexity of their evaluation. Apart from establishing that deciding FO-rewritability of disjunctive sirups with a dag-shaped $q$ is also 2Exp-hard, we make substantial progress towards obtaining a complete FO/Ł-hardness dichotomy of disjunctive sirups with ditree-shaped $q$.","PeriodicalId":405398,"journal":{"name":"Proceedings of the 40th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129397897","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}
We consider tuple-independent probabilistic databases in a dynamic setting, where tuples can be inserted or deleted. In this context we are interested in efficient data structures for maintaining the query result of Boolean as well as non-Boolean queries. For Boolean queries, we show how the known lifted inference rules can be made dynamic, so that they support single-tuple updates with only a constant number of arithmetic operations. As a consequence, we obtain that the probability of every safe UCQ can be maintained with constant update time. For non-Boolean queries, our task is to enumerate all result tuples ranked by their probability. We develop lifted inference rules for non-Boolean queries, and, based on these rules, provide a dynamic data structure that allows both log-time updates and ranked enumeration with logarithmic delay. As an application, we identify a fragment of non-repeating conjunctive queries that supports log-time updates as well as log-delay ranked enumeration. This characterisation is tight under the OMv-conjecture.
{"title":"Probabilistic Databases under Updates: Boolean Query Evaluation and Ranked Enumeration","authors":"Christoph Berkholz, M. Merz","doi":"10.1145/3452021.3458326","DOIUrl":"https://doi.org/10.1145/3452021.3458326","url":null,"abstract":"We consider tuple-independent probabilistic databases in a dynamic setting, where tuples can be inserted or deleted. In this context we are interested in efficient data structures for maintaining the query result of Boolean as well as non-Boolean queries. For Boolean queries, we show how the known lifted inference rules can be made dynamic, so that they support single-tuple updates with only a constant number of arithmetic operations. As a consequence, we obtain that the probability of every safe UCQ can be maintained with constant update time. For non-Boolean queries, our task is to enumerate all result tuples ranked by their probability. We develop lifted inference rules for non-Boolean queries, and, based on these rules, provide a dynamic data structure that allows both log-time updates and ranked enumeration with logarithmic delay. As an application, we identify a fragment of non-repeating conjunctive queries that supports log-time updates as well as log-delay ranked enumeration. This characterisation is tight under the OMv-conjecture.","PeriodicalId":405398,"journal":{"name":"Proceedings of the 40th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems","volume":"230 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131539482","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}
Processing tree-structured data in the streaming model is a challenge: capturing regular properties of streamed trees by means of a stack is costly in memory, but falling back to finite-state automata drastically limits the computational power. We propose an intermediate stackless model based on register automata equipped with a single counter, used to maintain the current depth in the tree. We explore the power of this model to validate and query streamed trees. Our main result is an effective characterization of regular path queries (RPQs) that can be evaluated stacklessly---with and without registers. In particular, we confirm the conjectured characterization of tree languages defined by DTDs that are recognizable without registers, by Segoufin and Vianu (2002), in the special case of tree languages defined by means of an RPQ.
{"title":"Stackless Processing of Streamed Trees","authors":"Corentin Barloy, Filip Murlak, Charles Paperman","doi":"10.1145/3452021.3458320","DOIUrl":"https://doi.org/10.1145/3452021.3458320","url":null,"abstract":"Processing tree-structured data in the streaming model is a challenge: capturing regular properties of streamed trees by means of a stack is costly in memory, but falling back to finite-state automata drastically limits the computational power. We propose an intermediate stackless model based on register automata equipped with a single counter, used to maintain the current depth in the tree. We explore the power of this model to validate and query streamed trees. Our main result is an effective characterization of regular path queries (RPQs) that can be evaluated stacklessly---with and without registers. In particular, we confirm the conjectured characterization of tree languages defined by DTDs that are recognizable without registers, by Segoufin and Vianu (2002), in the special case of tree languages defined by means of an RPQ.","PeriodicalId":405398,"journal":{"name":"Proceedings of the 40th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123929039","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}
This is the companion paper of a talk in the Gems of PODS series, that reviews the development, starting at PODS 1988, of a family of Datalog-like languages with procedural, forward chaining semantics, providing an alternative to the classical declarative, model-theoretic semantics. These languages also provide a unified formalism that can express important classes of queries including fixpoint, while, and all computable queries. They can also incorporate in a natural fashion updates and nondeterminism. Datalog variants with forward chaining semantics have been adopted in a variety of settings, including active databases, production systems, distributed data exchange, and data-driven reactive systems.
{"title":"Datalog Unchained","authors":"V. Vianu","doi":"10.1145/3452021.3458815","DOIUrl":"https://doi.org/10.1145/3452021.3458815","url":null,"abstract":"This is the companion paper of a talk in the Gems of PODS series, that reviews the development, starting at PODS 1988, of a family of Datalog-like languages with procedural, forward chaining semantics, providing an alternative to the classical declarative, model-theoretic semantics. These languages also provide a unified formalism that can express important classes of queries including fixpoint, while, and all computable queries. They can also incorporate in a natural fashion updates and nondeterminism. Datalog variants with forward chaining semantics have been adopted in a variety of settings, including active databases, production systems, distributed data exchange, and data-driven reactive systems.","PeriodicalId":405398,"journal":{"name":"Proceedings of the 40th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134061260","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}
Consistent query answering (CQA) aims to deliver meaningful answers when queries are evaluated over inconsistent databases. Such answers must be certainly true in all repairs, which are consistent databases whose difference from the inconsistent one is somehow minimal. Although CQA provides a clean framework for querying inconsistent databases, it is arguably more informative to compute the percentage of repairs in which a candidate answer is true, instead of simply saying that is true in all repairs, or is false in at least one repair. It should not be surprising, though, that computing this percentage is computationally hard. On the other hand, for practically relevant settings such as conjunctive queries and primary keys, there are data-efficient randomized approximation schemes for approximating this percentage. Our goal is to perform a thorough experimental evaluation and comparison of those approximation schemes. Our analysis provides new insights on which technique is indicated depending on key characteristics of the input, and it further provides evidence that making approximate CQA as described above feasible in practice is not an unrealistic goal.
{"title":"Benchmarking Approximate Consistent Query Answering","authors":"M. Calautti, Marco Console, Andreas Pieris","doi":"10.1145/3452021.3458309","DOIUrl":"https://doi.org/10.1145/3452021.3458309","url":null,"abstract":"Consistent query answering (CQA) aims to deliver meaningful answers when queries are evaluated over inconsistent databases. Such answers must be certainly true in all repairs, which are consistent databases whose difference from the inconsistent one is somehow minimal. Although CQA provides a clean framework for querying inconsistent databases, it is arguably more informative to compute the percentage of repairs in which a candidate answer is true, instead of simply saying that is true in all repairs, or is false in at least one repair. It should not be surprising, though, that computing this percentage is computationally hard. On the other hand, for practically relevant settings such as conjunctive queries and primary keys, there are data-efficient randomized approximation schemes for approximating this percentage. Our goal is to perform a thorough experimental evaluation and comparison of those approximation schemes. Our analysis provides new insights on which technique is indicated depending on key characteristics of the input, and it further provides evidence that making approximate CQA as described above feasible in practice is not an unrealistic goal.","PeriodicalId":405398,"journal":{"name":"Proceedings of the 40th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127683956","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. Alur, Phillip Hilliard, Z. Ives, Konstantinos Kallas, Konstantinos Mamouras, Filip Niksic, C. Stanford, V. Tannen, Anton Xue
We present a type-theoretic framework for data stream processing for real-time decision making, where the desired computation involves a mix of sequential computation, such as smoothing and detection of peaks and surges, and naturally parallel computation, such as relational operations, key-based partitioning, and map-reduce. Our framework unifies sequential (ordered) and relational (unordered) data models. In particular, we define synchronization schemas as types, and series-parallel streams (SPS) as objects of these types. A synchronization schema imposes a hierarchical structure over relational types that succinctly captures ordering and synchronization requirements among different kinds of data items. Series-parallel streams naturally model objects such as relations, sequences, sequences of relations, sets of streams indexed by key values, time-based and event-based windows, and more complex structures obtained by nesting of these. We introduce series-parallel stream transformers (SPST) as a domain-specific language for modular specification of deterministic transformations over such streams. SPSTs provably specify only monotonic transformations allowing streamability, have a modular structure that can be exploited for correct parallel implementation, and are composable allowing specification of complex queries as a pipeline of transformations.
{"title":"Synchronization Schemas","authors":"R. Alur, Phillip Hilliard, Z. Ives, Konstantinos Kallas, Konstantinos Mamouras, Filip Niksic, C. Stanford, V. Tannen, Anton Xue","doi":"10.1145/3452021.3458317","DOIUrl":"https://doi.org/10.1145/3452021.3458317","url":null,"abstract":"We present a type-theoretic framework for data stream processing for real-time decision making, where the desired computation involves a mix of sequential computation, such as smoothing and detection of peaks and surges, and naturally parallel computation, such as relational operations, key-based partitioning, and map-reduce. Our framework unifies sequential (ordered) and relational (unordered) data models. In particular, we define synchronization schemas as types, and series-parallel streams (SPS) as objects of these types. A synchronization schema imposes a hierarchical structure over relational types that succinctly captures ordering and synchronization requirements among different kinds of data items. Series-parallel streams naturally model objects such as relations, sequences, sequences of relations, sets of streams indexed by key values, time-based and event-based windows, and more complex structures obtained by nesting of these. We introduce series-parallel stream transformers (SPST) as a domain-specific language for modular specification of deterministic transformations over such streams. SPSTs provably specify only monotonic transformations allowing streamability, have a modular structure that can be exploited for correct parallel implementation, and are composable allowing specification of complex queries as a pipeline of transformations.","PeriodicalId":405398,"journal":{"name":"Proceedings of the 40th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122819801","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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