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GEqO: ML-Accelerated semantic Equivalence Detection

Proceedings of the ACM on Management of Data 2023年第4期1卷 1-25页

作者： Brandon Haynes Rana Alotaibi Anna Pavlenko Jyoti Leeka Alekh Jindal Yuanyuan Tian Microsoft Gray Systems Lab Redmond WA USA Microsoft Redmond WA USA SmartApps Bellevue WA USA

Large scale analytics engines have become a core dependency for modern data-driven enterprises to derive business insights and drive actions. These engines support a large number of analytic jobs processing huge volumes of data on a daily basis, and workloads are often inundated with overlapping computations across multiple jobs. Reusing common computation is crucial for efficient cluster resource utilization and reducing job execution time. Detecting common computation is the first and key step for reducing this computational redundancy. However, detecting equivalence on large-scale analytics engines requires efficient and scalable solutions that are fully automated. In addition, to maximize computation reuse, equivalence needs to be detected at the semantic level instead of just the syntactic level (i.e., the ability to detect semantic equivalence of seemingly different-looking queries). Unfortunately, existing solutions fall short of satisfying these *** this paper, we take a major step towards filling this gap by proposing GEqO, a portable and lightweight machine-learning-based framework for efficiently identifying semantically equivalent computations at scale. GEqO introduces two machine-learning-based filters that quickly prune out nonequivalent subexpressions and employs a semi-supervised learning feedback loop to iteratively improve its model with an intelligent sampling mechanism. Further, with its novel database-agnostic featurization method, GEqO can transfer the learning from one workload and database to another. Our extensive empirical evaluation shows that, on TPC-DS-like queries, GEqO yields significant performance gains-up to 200x faster than automated verifiers-and finds up to 2x more equivalences than optimizer and signature-based equivalence detection approaches.

关键词： machine learning semantic query optimization

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The backchase revisited

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VLDB JOURNAL 2014年第3期23卷 495-516页

作者： Meier, Michael Fluid Operat AG D-69190 Walldorf Germany

semantic query optimization is the process of finding equivalent rewritings of an input query given constraints that hold in a database instance. In this paper, we report about a Chase & Backchase (C&B) algorithm strategy that generalizes and improves on well-known methods in the field. The implementation of our approach, the Pegasussystem, outperforms existing C&B systems an average by two orders of magnitude. This gain in performance is due to a combination of novel methods that lower the complexity in practical situations significantly.

关键词： semantic query optimization Chase Backchase Core Conjunctive queries Constraints

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semantic query optimization on object-oriented database

Semantic query optimization on object-oriented database

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13th ISSAT International Conference on Reliabitity and Quality in Design

作者： Wang, Mei-Tzu Chinese Culture Univ Dept Informat Management Taipei Taiwan

ISBN: (纸本)9780976348627

In this paper we discuss the problem of query optimization on object-oriented database. Rich semantic knowledge in terms of class hierarchy, aggregation hierarchy, and integrity constraints are considered in this work. In the effort of exploring the quantification of query performance, we develop a theorem to compute the maximum number of access in checking a predicate involving a nested attribute. From its corollary, we find that the decreased number of access of objects in earlier classes of the path have more effect on the total number of the access of objects under the assumption that all objects of all classes are uniformly distributed among all values of all attributes. Using this fact, we suggest that the predicate with a path of shorter length should be evaluated prior to another predicate with a path of longer length, if one path of the two is a sub path of the other. In the process of exploration, we conclude some guided rules and define efficiency ratio as measurement for quantifying query performance. Finally, a simple and easy-to-use algorithm is suggested for rewriting queries in order to achieve higher performance.

关键词： object-oriented database integrity constraint semantic query optimization schema class

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semantic query optimization: Correctness and Control

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JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS 2006年第3期10卷 270-280页

作者： Chippimolchai, Pongtawat Akama, Kiyoshi Wuwongse, Vilas Asian Inst Technol Comp Sci & Informat Management Program Km 42Paholyothin Highway Klongluang 12120 Pathumthani Thailand Hokkaido Univ Div Large Scale Computat Syst Informat Initiat Ct Kita Ku Sapporo Hokkaido 0600811 Japan

We developed a semantic query optimization framework for deductive databases based on equivalent transformation (ET) rules. ET rules, prepared from the semantic knowledge of databases, such as integrity constraints, transform given queries into syntactically different but semantically equivalent and more efficient forms. We formally prove the correctness of query transformations by ET rules. For efficiency, we propose a two-phase heuristic-based strategy to guide query transformations and introduce a condition-based control strategy to prevent unwanted, unnecessary transformations. We give examples demonstrating the possible optimization.

关键词： semantic query optimization deductive database integrity constraint equivalent transformation semantic preservation

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A constraint-aware query optimizer for web-based data integration

A constraint-aware query optimizer for web-based data integr...

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4th International Conference on Web Information Systems and Technologies

作者： Lu, Jing Mitschang, Bernhard Univ Stuttgart IPVS Stuttgart Germany

ISBN: (纸本)9789898111265

Web has brought forth opportunities to connect information sources across all types of boundaries. Data integration is to combine data residing at different sources and providing the user with a unified view of these data. Currently users are expecting more efficient services from such data integration systems. This paper describes a query optimizer, which uses constraints to semantically optimize the queries. The optimizer first translates constraints from data sources into constraints expressed at the global level and stores them in the constraint repository. Then the optimizer can use semantic query optimization technologies including detection of empty results, join elimination, and predicate elimination to generate a more efficient but semantically equivalent query for the user. The optimizer is published as a web service and can be invoked by many data integration systems. We carry out experiments and first results show that performance can be greatly improved.

关键词： XML Xquery data integration constraints semantic query optimization

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Intelligent query answering with data mining techniques

Intelligent query answering with data mining techniques

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International Conference on Computer Engineering and Systems (ICCES 07)

作者： Mohammed, H. K. Soliman, A. F. Ain Shams Univ Dept Comp & Syst Engn Cairo Egypt

ISBN: (纸本)9781424413652

Data mining in databases is an important issue in the development of data and knowledge-base systems. It facilitates querying database knowledge and semantic query optimization. The aim of the work is to use data mining tools for Intelligent query Answering in database systems, which include generalization, data summarization and rule discovery. We used a model for a knowledge-rich database, which consists not only of the components from a deductive database but also the components relevant to knowledge discovery tools. The discovered rule set constitutes a graph whose edges are the rules. This Condition Dependency graph provides a map of possible query reformulation operations so that semantic query optimization could be performed. semantic knowledge is needed to optimize queries. semantic knowledge may be in the form of generalized rules or association rules. Both will be applied to semantic query optimization system.

关键词： data mining intelligent query answering semantic query optimization discovered rules rule graph association rules

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Application semantics in query optimization for WSNs 07

Application Semantics in Query Optimization for WSNs

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5th ACM Conference on Embedded Networked Sensor Systems

作者： Tanin, Egemen Chen, Songting Tatemura, Junichi Hsiung, Wang-Pin NEC Laboratories America and University of Melbourne NEC Laboratories America

ISBN: (纸本)9781595937636

Efficient data acquisition in WSNs has attracted significant interest. For example, TinyDB [2] introduced query dissemination and data aggregation trees. Later, a probabilistic model of the physical world is used in [1]. Recently, [3] argues that probabilistic models of the physical world used in acquisition may miss outliers and introduces spatio-temporal suppression-based methods. We classify these established approaches as query-and-data centric approaches for optimizing the data acquisition process.

关键词： semantic query optimization sensor data management

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Description logics for semantic query optimization in object-oriented database systems

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ACM TRANSACTIONS ON DATABASE SYSTEMS 2003年第1期28卷 1-50页

作者： Beneventano, D Bergamaschi, S Sartori, C Univ Modena & Reggio Emilia Modena Italy CNR CSITE I-00185 Rome Italy Univ Bologna I-40126 Bologna Italy

semantic query optimization uses semantic knowledge (i.e., integrity constraints) to transform a query into an equivalent one that may be answered more efficiently. This article proposes a general method for semantic query optimization in the framework of Object-Oriented Database Systems. The method is effective for a large class of queries, including conjunctive recursive queries expressed with regular path expressions and is based on three ingredients. The first is a Description Logic, ODLRE, providing a type system capable of expressing: class descriptions, queries, views, integrity constraint rules and inference techniques, such as incoherence detection and subsumption computation. The second is a semantic expansion function for queries, which incorporates restrictions logically implied by the query and the schema (classes + rules) in one query. The third is an optimal rewriting method of a query with respect to the schema classes that rewrites a query into an equivalent one, by determining more specialized classes to be accessed and by reducing the number of factors. We implemented the method in a tool providing an ODMG-compliant interface that allows a full interaction with OQL queries, wrapping underlying Description Logic representation and techniques to the user.

关键词： algorithms management languages theory semantic query optimization query rewriting method integrity constraints rules semantic expansion of a query description logics subsumption

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A semantic approach to optimize linear datalog programs

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ACTA INFORMATICA 2006年第5期43卷 341-370页

作者： Parama, Jose R. Brisaboa, Nieves R. Penabad, Miguel R. Places, Angeles S. Univ A Coruna Fac Informat Dept Comp Sci Database Lab La Coruna Spain

In this work, we present a semantic query optimization approach to improve the efficiency of the evaluation of a subset of SQL:1999 recursive queries. Using datalog notation, we can state our main contribution as an algorithm that builds a program P' equivalent to a given program P, when both are applied over a database d satisfying a set of functional dependencies. The input program P is a linear recursive datalog program. The new program P' has less different variables and, sometimes, less atoms in rules, thus it is cheaper to evaluate. Using CORAL and IBM DB2, P' is empirically shown to be more efficient than the original program.

关键词： deductive databases semantic query optimization SQL : 1999 recursion

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Global semantic query optimizer in multidatabase systems

Global semantic query optimizer in multidatabase systems

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10th World Multi-Conference on Systemics, Cybernetics and Informatics/12th International Conference on Information Systems Analysis and Synthesis

作者： Rachburi, Nachirat Chittayasothorn, Suphamit King Mongkuts Inst Technol Dept Comp Engn Bangkok 10520 Thailand King Mongkuts Inst Technol Ladkrabang Dept Comp Engn Fac Engn Bangkok 10520 Thailand

ISBN: (纸本)9789806560666

At present, multidatabase systems provide access to local databases via gateway protocols. Users have to be aware of product-specific features of local database management systems. query optimization in multidatabase systems are normally based on statistics collected at local sites. This paper describes a multidatabase system that supports global schemas, fragmentation schemas and allocation schemas together with the semantic query optimization capability. The system also supports data manipulations on global databases with mixed fragmentation. The semantic query optimization feature proved to be very useful and helps reduce response time of global queries.

关键词： multidatabase semantic query optimization global schema fragmentation allocation

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