• 제목/요약/키워드: Query efficiency

검색결과 260건 처리시간 0.019초

Query Optimization on Large Scale Nested Data with Service Tree and Frequent Trajectory

  • Wang, Li;Wang, Guodong
    • Journal of Information Processing Systems
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    • 제17권1호
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    • pp.37-50
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    • 2021
  • Query applications based on nested data, the most commonly used form of data representation on the web, especially precise query, is becoming more extensively used. MapReduce, a distributed architecture with parallel computing power, provides a good solution for big data processing. However, in practical application, query requests are usually concurrent, which causes bottlenecks in server processing. To solve this problem, this paper first combines a column storage structure and an inverted index to build index for nested data on MapReduce. On this basis, this paper puts forward an optimization strategy which combines query execution service tree and frequent sub-query trajectory to reduce the response time of frequent queries and further improve the efficiency of multi-user concurrent queries on large scale nested data. Experiments show that this method greatly improves the efficiency of nested data query.

An Efficient Indexing Structure for Multidimensional Categorical Range Aggregation Query

  • Yang, Jian;Zhao, Chongchong;Li, Chao;Xing, Chunxiao
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권2호
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    • pp.597-618
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    • 2019
  • Categorical range aggregation, which is conceptually equivalent to running a range aggregation query separately on multiple datasets, returns the query result on each dataset. The challenge is when the number of dataset is as large as hundreds or thousands, it takes a lot of computation time and I/O. In previous work, only a single dimension of the range restriction has been solved, and in practice, more applications are being used to calculate multiple range restriction statistics. We proposed MCRI-Tree, an index structure designed to solve multi-dimensional categorical range aggregation queries, which can utilize main memory to maximize the efficiency of CRA queries. Specifically, the MCRI-Tree answers any query in $O(nk^{n-1})$ I/Os (where n is the number of dimensions, and k denotes the maximum number of pages covered in one dimension among all the n dimensions during a query). The practical efficiency of our technique is demonstrated with extensive experiments.

질의로그 데이터에 기반한 특허 및 상표검색에 관한 연구 (Analysis of Korean Patent & Trademark Retrieval Query Log to Improve Retrieval and Query Reformulation Efficiency)

  • 이지연;백우진
    • 정보관리학회지
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    • 제23권2호
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    • pp.61-79
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    • 2006
  • 본 연구는 특허 및 상표 검색 개선을 위한 방법을 제안하고자 하는 목적에서 출발하였다. 이를 위해 193일간 한국 특허정보원의 특허기술정보서비스를 이용한 17,559명의 이용자가 작성한 100,016개의 질의문에 대한 로그 데이터를 분석하였다. 개별적인 질의로그 분석 이외에, 2,202개의 복수 질의문을 이용한 탐색세션을 분석함으로써 검색 개선을 위한 추가적인 단서를 발견하였다. 분석결과에 의하면, 특허 및 상표검색은 일반적인 웹 검색의 유형과 유사한데, 특히 질의문의 길이가 짧다는 측면에서 매우 흡사하다. 그러나 특히 및 상표검색의 경우, 일반 웹 검색보다 불리언 연산자를 많이 사용하고 있었다. 복수 질의문 분석을 통해 이용자들이 질의문을 재작성하는데 도움이 될 수 있는 탐색기능을 제안할 수 있었다. 복수의 질의문으로 구성된 탐색세션을 분석한 결과, 이용자들은 질의문을 재작성하기 위하여 부연하기, 특정화하기, 일반화하기, 교체하기, 중단하기와 같은 방법을 사용하고 있음을 알 수 있었다.

A Prediction-based Energy-conserving Approximate Storage and Query Processing Schema in Object-Tracking Sensor Networks

  • Xie, Yi;Xiao, Weidong;Tang, Daquan;Tang, Jiuyang;Tang, Guoming
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제5권5호
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    • pp.909-937
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    • 2011
  • Energy efficiency is one of the most critical issues in the design of wireless sensor networks. In object-tracking sensor networks, the data storage and query processing should be energy-conserving by decreasing the message complexity. In this paper, a Prediction-based Energy-conserving Approximate StoragE schema (P-EASE) is proposed, which can reduce the query error of EASE by changing its approximate area and adopting predicting model without increasing the cost. In addition, focusing on reducing the unnecessary querying messages, P-EASE enables an optimal query algorithm to taking into consideration to query the proper storage node, i.e., the nearer storage node of the centric storage node and local storage node. The theoretical analysis illuminates the correctness and efficiency of the P-EASE. Simulation experiments are conducted under semi-random walk and random waypoint mobility. Compared to EASE, P-EASE performs better at the query error, message complexity, total energy consumption and hotspot energy consumption. Results have shown that P-EASE is more energy-conserving and has higher location precision than EASE.

Energy Join Quality Aware Real-time Query Scheduling Algorithm for Wireless Sensor Networks

  • Phuong, Luong Thi Thu;Lee, Sung-Young;Lee, Young-Koo
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2011년도 춘계학술발표대회
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    • pp.92-96
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    • 2011
  • Nowadays, the researches study high rate and real-time query applications seem to be real-time query scheduling protocols and energy aware real time query protocols. Also the WSNs should provide the quality of data in real time query applications that is more and more popular for wireless sensor networks (WSNs). Thus we propose the quality of data function to merge into energy efficiency called energy join quality aware realtime query scheduling (EJQRTQ). Our work calculate the energy ratio that considers interference of queries, and then compute the expected quality of query and allocate slots to real-time preemptive query scheduler.

온톨로지-DTD 정합에 의한 XML 질의 확장 (XML Query-Expansion by Ontology-DTD Match)

  • 김명숙;공용해
    • 정보처리학회논문지D
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    • 제12D권5호
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    • pp.773-780
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    • 2005
  • XML 질의를 온톨로지 기반으로 확장하면 보다 폭넓은 정보검색이 가능해지는 반면에, 대상 문서의 구조에 부적합하게 확장된 질의들은 검색의 효율을 저하시킬 수 있다. 본 연구는 은톨로지와 대상 문서의 DTD를 정합한 결과인 축소된 온톨로지를 기반으로 질의를 확장함으로써 질의의 적합도를 향상시키는 방법을 제안한다. 온톨로지 개념과 DTD 엘리먼트 정합 및 온톨로지와 DTD 속성 정합에 의해 한번 축소된 온톨로지는 질의의 적중률을 높일 수 있을 뿐만 아니라 동일한 구조를 가지는 문서 집단에 재사용될 수 있으므로 검색의 효율을 향상시킬 수 있다.

Equivalence Heuristics for Malleability-Aware Skylines

  • Lofi, Christoph;Balke, Wolf-Tilo;Guntzer, Ulrich
    • Journal of Computing Science and Engineering
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    • 제6권3호
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    • pp.207-218
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    • 2012
  • In recent years, the skyline query paradigm has been established as a reliable method for database query personalization. While early efficiency problems have been solved by sophisticated algorithms and advanced indexing, new challenges in skyline retrieval effectiveness continuously arise. In particular, the rise of the Semantic Web and linked open data leads to personalization issues where skyline queries cannot be applied easily. We addressed the special challenges presented by linked open data in previous work; and now further extend this work, with a heuristic workflow to boost efficiency. This is necessary; because the new view on linked open data dominance has serious implications for the efficiency of the actual skyline computation, since transitivity of the dominance relationships is no longer granted. Therefore, our contributions in this paper can be summarized as: we present an intuitive skyline query paradigm to deal with linked open data; we provide an effective dominance definition, and establish its theoretical properties; we develop innovative skyline algorithms to deal with the resulting challenges; and we design efficient heuristics for the case of predicate equivalences that may often happen in linked open data. We extensively evaluate our new algorithms with respect to performance, and the enriched skyline semantics.

Efficient Continuous Skyline Query Processing Scheme over Large Dynamic Data Sets

  • Li, He;Yoo, Jaesoo
    • ETRI Journal
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    • 제38권6호
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    • pp.1197-1206
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    • 2016
  • Performing continuous skyline queries of dynamic data sets is now more challenging as the sizes of data sets increase and as they become more volatile due to the increase in dynamic updates. Although previous work proposed support for such queries, their efficiency was restricted to small data sets or uniformly distributed data sets. In a production database with many concurrent queries, the execution of continuous skyline queries impacts query performance due to update requirements to acquire exclusive locks, possibly blocking other query threads. Thus, the computational costs increase. In order to minimize computational requirements, we propose a method based on a multi-layer grid structure. First, relational data object, elements of an initial data set, are processed to obtain the corresponding multi-layer grid structure and the skyline influence regions over the data. Then, the dynamic data are processed only when they are identified within the skyline influence regions. Therefore, a large amount of computation can be pruned by adopting the proposed multi-layer grid structure. Using a variety of datasets, the performance evaluation confirms the efficiency of the proposed method.

컴포넌트 검색에서 퍼지 시소러스를 이용한 효율적인 질의확장 방법 (Efficient Query Expansion Method using Fuzzy Thesaurus in Component Retrieval)

  • 김귀정;한정수
    • 한국콘텐츠학회논문지
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    • 제4권1호
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    • pp.76-82
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    • 2004
  • 본 논문은 사용자 질의가 가지는 특정 클래스로부터 개념적으로 서로 연관있는 컴포넌트를 검색하기 위하여 퍼지 시소러스를 통한 질의 확장 방법을 제안하였다. 사용자 질의는 퍼지 불리언 형태로 표현되며, 퍼지 시소러스에 의한 유의어 테이블에 의해 질의 확장된다. 시소러스에 의한 사용자 질의확장은 용어 불일치 문제를 해결함으로써 검색에 대한 일정한 정확도를 보장하면서 재현율을 향상시킬 수 있게 한다. 질의 확장과정의 효율성을 평가하기 위하여 시뮬레이션을 통한 최적의 검색 효율을 나타내는 임계치를 설정하고 재현율 과 정확도를 비교하였다.

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사전 의미 기반의 질의확장 검색에서 추가 용어 가중치 최적화 (Optimizing the Additional Term Weight Ratio in Query Expansion Search based on Dictionary Definition)

  • 최영란;전유정;박순철
    • 한국산업정보학회논문지
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    • 제8권2호
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    • pp.45-53
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    • 2003
  • 본 연구가 갖는 중요성은 두 가지로 요약된다. 첫째는 질의 확장 검색 방법으로 사전에서 나타나는 용어를 질의의 추가용어로 채택하는 것이다. 이 방법은 기존의 피드백 확정 방법이 갖는 2차적 검색 과정을 줄인다. 둘째는 초기 질의어와 추가용어 사이에 가중치를 달리 적용하여 재현율과 정확률을 동시에 높일 수 있는 최적의 모델을 제시하였다. 이렇게 함으로써 정보 검색의 성능을 크게 향상시킬 수 있는 방법을 제시하고 있다.

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