This paper concentrates on the problem of embedded database query optimization, which is a crucial problem in embedded system design. Firstly, we describe the structure of the embedded database system, in which the da...
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ISBN:
(纸本)9781467371438
This paper concentrates on the problem of embedded database query optimization, which is a crucial problem in embedded system design. Firstly, we describe the structure of the embedded database system, in which the database engine is a key module in the database system, and it can ensure the database system correctly and efficiently work. Secondly, the embedded database query optimization algorithm based on an improved particle swarm optimization is given. The main innovations of this paper lie in the following aspects: 1) a high inertia weight is used to find new searching space, 2) inertia weight decreases in terms of paths of different values of particle number, 3) final inertia weight is obtained after executing the max number of iterations. Thirdly, to test the effectiveness of our algorithm, we construct an experimental embedded system platform. Compared with the B+Tree, our proposed algorithm can achieve better performance in both space utilization and time cost.
Faced with massive data and the complexity of query requirements, how to improve the query speed of database has become a research hotspot. This paper analyses the artificial intelligence algorithms, genetic ant colon...
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ISBN:
(纸本)9781450362788
Faced with massive data and the complexity of query requirements, how to improve the query speed of database has become a research hotspot. This paper analyses the artificial intelligence algorithms, genetic ant colony algorithm (GA-ACA), which is used for database query optimization. The GA-ACA is prone to decrease the diversity in multi-connection search of database, which results in inefficiency and local extremum. To solve this problem, our paper proposes an improvement algorithm on multi-connection query. Based on the premise of population diversity, the algorithm analyses the population entropy and variance. And it chooses the equal probability crossover or the unequal probability crossover according to the evolutionary state, which effectively avoids the phenomenon of local optimum due to the iteration of similar individuals. This paper improves the crossover operation and redefines the generation mode of new population. Experiments show that the improved algorithm avoids the local optimal solution to some extent, meanwhile shortens the searching time.
queryoptimization is considered to be one of the most important challenges in database management. Existing built-in query optimizers are very complex and rely on various approximations and hand-picked rules. The ris...
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queryoptimization is considered to be one of the most important challenges in database management. Existing built-in query optimizers are very complex and rely on various approximations and hand-picked rules. The rise of deep learning and deep reinforcement learning has aided many scientific and industrial fields, providing an opportunity to develop a learnable query optimizer. In this paper, we analyse and improve the state-of-the-art learned query optimizer, Neo for the JOB benchmark on two database systems: PostgreSQL and Huawei GaussDB. We describe our methods, based on combination of Neo, Tree-Transformers, auxiliary tasks, reward weighting. Combinations of these methods improve latency of the found query execution plans. We also conduct a thorough analysis of the resulting execution plans and devise a set of decision-based rules to indicate the cases when the learned optimizer will outperform the built-in one. We also provide a source code for the proposed methods and experiments. Finally, we provide possible directions for further improvement in this field.
Optimizing queries in real-world situations under imperfect conditions is still a problem that has not been fully solved. We consider finding the optimal order in which to execute a given set of selection operators un...
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The research objective is to develop indexing data algorithm to reduce database searching time by using multithreaded frameworks. In this article the indexing data algorithm in a tree form which is called CW-tree is s...
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ISBN:
(纸本)9781728169491
The research objective is to develop indexing data algorithm to reduce database searching time by using multithreaded frameworks. In this article the indexing data algorithm in a tree form which is called CW-tree is supposed. Traversing through CW-tree occurs asynchronously with help additional start nodes. Compared to existing analogs of tree-based algorithms, the CW-tree has some advantages, the main of which is full parallelization both on the levels of branches and on the levels of leaves. To confirm benefits from using of CW-tree algorithm, comparison test between reading data with help B-tree and reading data with CW-tree was conducted. Result of test described in chapter 4 and shows that reading data time with CW-tree less than reading with B-tree.
As the primary approach to deriving decision-support insights, automated recurring routine analytic jobs account for a major part of cluster resource usages in modern enterprise data warehouses. These recurring routin...
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ISBN:
(纸本)9781450367356
As the primary approach to deriving decision-support insights, automated recurring routine analytic jobs account for a major part of cluster resource usages in modern enterprise data warehouses. These recurring routine jobs usually have stringent schedule and deadline determined by external business logic, and thus cause dreadful resource skew and severe resource over-provision in the cluster. In this paper, we present Grosbeak, a novel data warehouse that supports resource-aware incremental computing to process recurring routine jobs, smooths the resource skew, and optimizes the resource usage. Unlike batch processing in traditional data warehouses, Grosbeak leverages the fact that data is continuously ingested. It breaks an analysis job into small batches that incrementally process the progressively available data, and schedules these small-batch jobs intelligently when the cluster has free resources. In this demonstration, we showcase Grosbeak using real-world analysis pipelines. Users can interact with the data warehouse by registering recurring queries and observing the incremental scheduling behavior and smoothed resource usage pattern.
database index can be regarded as a data structure that speed up the data retrieval operations on a database table. The cost of indexing in database is additional writes and storage space to maintain the data structur...
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database index can be regarded as a data structure that speed up the data retrieval operations on a database table. The cost of indexing in database is additional writes and storage space to maintain the data structure. The created data structures in database are used to quickly query data without having to search every row of table in most relational database management system (RDBMS). The read and write performance of database is elevated by bringing in appropriate indexing technique, given the specific data type. As a result, indexing technique plays a significant role in database applications. After index is built completely, database will be able to answer the query. Generally, a query is a request for information from a database. It can be as simple as "finding the address of the headquater of company ZZ,'' or more complex like "finding the average total amount of penalties for football players who live in Auburn or Opelika, incur more than 3 penalties, and captain less than 2 teams.'' In order to quickly resolve the query result, we raise the definition of queryoptimization. The queryoptimization techniques try to determine the most efficient way to execute a specific query by considering all the possible query strategies. The goal of the queryoptimization is to find the way to process a given query in minimum time. The main contribution of this dissertation is to explore and study out efficient indexing and queryoptimization techniques regarding the specific problem. Three concrete database applications will be analyzed and explored, and indexing and querying techniques will be proposed respectively in order to enhance the database performance. First, two watchtower-based parameter-tunable indexing methods are introduced for efficient spatial processing with sparse distributions of Points of Interest (POIs) by exploiting mobile users' check-in data collected from the location-aware social networks. In the proposed frameworks, the network traversal can te
We consider a problem arising in database query optimization [R. Guravannavar, S. Sudarshan, Reducing order enforcement cost in complex query plans, in: Proceedings of the 23rd IEEE International Conference on Data En...
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We consider a problem arising in database query optimization [R. Guravannavar, S. Sudarshan, Reducing order enforcement cost in complex query plans, in: Proceedings of the 23rd IEEE International Conference on Data Engineering, ICDE-2007, pp. 856-865;R. Guravannavar, S. Sudarshan, A.A. Diwan, Ch. Sobhan Babu, Reducing order enforcement cost in complex query plans, Manuscript, November 2006. Available at http://***/abs/***/0611094], which we call as The Common Prefix Problem. We present a PTAS for this problem, when the underlying graph is a tree with the degrees of the vertices bounded by a constant, e.g. binary tree. We then use a result of Feige and Kogan [U. Feige, S. Kogan, Hardness of approximation of the balanced complete bipartite subgraph problem, Technical report MCS04-04, Department of Computer Science and Applied Mathematics, The Weizmann Institute of Science, 2004] to show that even on star graphs the problem is hard to approximate. (C) 2007 Elsevier B.V. All rights reserved.
Designing complex distributed client/server applications that meet performance requirements may prove extremely difficult in practice if software developers are not willing or do not have the time to help software per...
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Designing complex distributed client/server applications that meet performance requirements may prove extremely difficult in practice if software developers are not willing or do not have the time to help software performance analysts. This paper advocates the need to integrate both design and performance modeling activities so that one can help the other. We present a method developed and used by the authors in the design of a fairly large and complex client/server application. The method is based on a software performance engineering language developed by one of the authors. Use cases ware developed and mapped to a performance modeling specification using the language. A compiler for the language generates an analytic performance model for the system. Service demand parameters at servers, storage boxes, and networks are derived by the compiler from the system specification. A detailed model of DBMS query optimizers allows the compiler to estimate the number of I/Os and CPU time for SQL statements. The paper concludes with some results of the application that prompted the development of the method and language.
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