Query optimization is an important part of database management system. In this paper, through the research on query optimization technology, based on a number of optimization algorithms commonly used in distributed qu...
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ISBN:
(纸本)9781424455379
Query optimization is an important part of database management system. In this paper, through the research on query optimization technology, based on a number of optimization algorithms commonly used in distributed query, a new algorithm is designed, and experiments show that this algorithm can significantly reduce the amount of intermediate result data, effectively reduce the network communication cost, to improve the optimization efficiency.
Electricity Cost Remote Control in Marketing Business has been playing an important role in the business management of electricity information collection. Through analysis on the information about electricity cost rem...
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ISBN:
(纸本)9781510829039
Electricity Cost Remote Control in Marketing Business has been playing an important role in the business management of electricity information collection. Through analysis on the information about electricity cost remote control, it can study the cost control data and provide the real-time estimation on energy consumption so as to establish the interaction with the customers and put forward the remote control mode by analyzing the data processing from data classification, storage, distribution and circulation, which will be greatly improved electricity information collection system.
This dissertation proposes a new algorithm of distributed mining association rules using the improved Apriori algorithm, based on analyses and introduction of the basic concepts and algorithms of mining association ru...
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ISBN:
(纸本)9781424451944
This dissertation proposes a new algorithm of distributed mining association rules using the improved Apriori algorithm, based on analyses and introduction of the basic concepts and algorithms of mining association rules and mining association rules in distributed databases. Using improved Apriori algorithm to directly produce all of local frequent itemset in each crunode, rather than iteratively selecting candidate itemset. Then gather all of local multifarious itemset to broadcast to the general node, producing the global frequent itemset of association rules. In the process, the data is no longer saved with the affair ID as the key word. We take the item ID as the new key word. The performance of the improved Apriori algorithm has been improved through cutting down the store space. While the general node gathers all of local frequent itemset to select the global frequent itemset, it needs only a broadcast probably, needing three broadcasts worst. This raised the efficiency of the new algorithm of Association Rules in distributed database System.
In this study, we propose a reconfigurable sensor network emulator (ReSNE) that realizes a virtual large-scale sensor network environment by combining pseudo sensor/network devices and real ones. This is necessary as ...
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ISBN:
(纸本)9781467385800
In this study, we propose a reconfigurable sensor network emulator (ReSNE) that realizes a virtual large-scale sensor network environment by combining pseudo sensor/network devices and real ones. This is necessary as it is difficult to evaluate nationwide sensor networks using a real environment because of the need for a large number of real sensor nodes and related devices such as base stations, in addition to a large dedicated communication network. To emulate sensor network traffic, we also use a sensor data generator that generates sensed data packets in the network based on specific user-defined parameters. Furthermore, we develop an auto-configuration tool to enable us to set up the environment quickly. Here, we discuss details of the proposed ReSNE architecture and present some of the evaluation results obtained.
In the current distributed database system architecture enterprise-class, the massively parallel processing architecture is used frequently. This method can be used to carry out large-scale analysis of data through di...
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In the current distributed database system architecture enterprise-class, the massively parallel processing architecture is used frequently. This method can be used to carry out large-scale analysis of data through distributed across multiple nodes and storage and query process, from its scope of application produce simple reports to perform complex analytics workloads. However, due to the characteristics of shared-nothing MPP technology, to carry out large-scale data analysis query and maintain data consistency there are some difficulties. In this paper, a relational SQL-based query parsing distributed MPP data distribution and parallel processing technology, the goal is to maintain and improve the consistency of distributed data query speed. First SQL query analysis section, according to the syntax analysis, semantic analysis and sentence parsing steps such order;in the form of work distribution node/data node in the data distribution phase, all tasks emanating from the work of a distribution node, all need to treated results are returned to the node;when parallel processing, each node needs to store a copy of the lookup table, and on each node concurrent execution of SQL statements for each query. Experimental results show that the proposed MPP data distribution and parallel processing scheme can support large volume of data processing, ensuring data consistency in the premise of improving query processing speed.
In this paper, we study the problem of mass data storage and encountered in its process. We choose D3 Base, one of distributed database products, to compare with the Oracle, and do relevant testing work. The deploymen...
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ISBN:
(纸本)9781510829039
In this paper, we study the problem of mass data storage and encountered in its process. We choose D3 Base, one of distributed database products, to compare with the Oracle, and do relevant testing work. The deployment of distributed database products and the construction of network environment are also discussed.
In this paper, we present an innovative system, coined as DISTROD (a.k.a distributed Outlier Detector), for detecting outliers, namely abnormal instances or observations, from multiple large distributed databases. DIS...
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In this paper, we present an innovative system, coined as DISTROD (a.k.a distributed Outlier Detector), for detecting outliers, namely abnormal instances or observations, from multiple large distributed databases. DISTROD is able to effectively detect the so-called global outliers from distributed databases that are consistent with those produced by the centralized detection paradigm. DISTROD is equipped with a number of optimization/boosting strategies which empower it to significantly enhance its speed performance and reduce its communication overhead. Experimental evaluation demonstrates the good performance of DISTROD in terms of speed and communication overhead.
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