• Journal of the Korea Society of Computer and Information
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• v.16 no.8
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• pp.29-38
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• 2011

Unlike in traditional row-oriented database systems, a column-oriented database system stores data in column-oriented and not row-oriented order. Recently, research results revealed the effectiveness of column-oriented databases for applications such as data warehouse and decision support systems that access large volumes of data in a read only manner. In this paper, we investigate the join strategies for column-oriented databases and prove the effectiveness of column-oriented databases in data warehouse systems. For unbiased comparison, the two database systems are analyzed using the star schema benchmark and the performance analysis of a star schema join query is carried out. We experimented with well-known join algorithms and considered early materialization and late materialization join strategies for column-oriented databases. The performance results confirm that star schema join queries perform better in terms of disk I/O cost in column-oriented databases than in row-oriented databases. In addition, the late materialization strategy showed more performance gain than the early materialization strategy in column-oriented databases.

• Journal of Internet Computing and Services
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• v.13 no.3
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• pp.83-91
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• 2012

Recently, column-oriented storage has become a progressive model for high-speed database systems because of its superior I/O performance. In this paper, we analysis traditional raw-oriented storage model and then propose a new column-aware storage management model using flash memory drive and assist drive to improve the effective performance of the high-speed column-oriented database system. Our storage management scheme called column-aware polarization improves the performance of update operation by dividing and compressing table columns into active-columns or inactive-columns, and balancing congested update operations using a assist drive in high workload periods. The results obtained from experimental tests show that our scheme improves the update throughput of column-oriented storage by 19 percent, and the response time by up to 49 percent.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.1
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• pp.393-401
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• 2013

Most traditional databases exploit record-oriented storage model where the attributes of a record are placed contiguously in hard disk to achieve high performance writes. However, for search-mostly datawarehouse systems, column-oriented storage has become a proper model because of its superior read performance. Today, flash memory is largely recognized as the preferred storage media for high-speed database systems. In this paper, we introduce fast column-oriented database model and then propose a new column-aware index management scheme for the high-speed column-oriented datawarehouse system. Our index management scheme which is based on enhanced $B^+$-Tree achieves high search performance by embedded flash index and unused space compression in internal and leaf nodes. Based on the results of the performance evaluation, we conclude that our index management scheme outperforms the traditional scheme in the respect of the search throughput and response time.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.4
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• pp.2784-2790
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• 2015

The column-oriented database storage is a very advanced model for large-volume data transactions because of its superior I/O performance. Traditional data storages exploit row-oriented storage where the attributes of a record are placed contiguously in hard disk for fast write operations. However, for search-mostly data warehouse systems, column-oriented storage has become a more proper model because of its superior read performance. Recently, solid state drive using flash memory is largely recognized as the preferred storage media for high-speed data analysis systems. In this research, we propose a new transaction recovery scheme for a column-oriented database environment which is based on a flash media file system. We improved traditional shadow paging schemes by reusing old data pages which are supposed to be invalidated in the course of writing a new data page in the flash file system environment. In order to reuse these data pages, we exploit reused shadow list structure in our column-oriented shadow recovery(CoSR) scheme. CoSR scheme minimizes the additional storage overhead for keeping shadow pages and minimizes the I/O performance degradation caused by column data compression of traditional recovery schemes. Based on the results of the performance evaluation, we conclude that CoSR outperforms the traditional schemes by 17%.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.5
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• pp.2449-2456
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• 2013

The column-oriented database storage is a very advanced model for large-volume data analysis systems because of its superior I/O performance. Traditional data storages exploit row-oriented storage where the attributes of a record are placed contiguously in hard disk for fast write operations. However, for search-mostly datawarehouse systems, column-oriented storage has become a more proper model because of its superior read performance. Recently, solid state drive using MLC flash memory is largely recognized as the preferred storage media for high-speed data analysis systems. In this paper, we introduce fast column-oriented data storage model and then propose a new storage management scheme using a cross compressed replication for the high-speed column-oriented datawarehouse system. Our storage management scheme which is based on two MLC SSD achieves superior performance and reliability by the cross replication of the uncompressed segment and the compressed segment under high workloads of CPU and I/O. Based on the results of the performance evaluation, we conclude that our storage management scheme outperforms the traditional scheme in the respect of update throughput and response time of the column segments.

• Smart Media Journal
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• v.8 no.3
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• pp.88-94
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• 2019

Livestock disease is a very important issue in the livestock industry because if livestock disease is not responded quickly enough, its damage can be devastating. To solve the issues involving the occurrence of livestock disease, it is necessary to diagnose in advance the status of livestock disease and develop systematic and scientific livestock feeding technologies. However, there is a lack of domestic studies on such technologies in Korea. This paper, therefore, proposes Livestock Disease Forecasting and Livestock Farm Integrated Control System using Cloud Computing to quickly manage livestock disease. The proposed system collects a variety of livestock data from wireless sensor networks and application. Moreover, it saves and manages the data with the use of the column-oriented database Hadoop HBase, a column-oriented database management system. This provides livestock disease forecasting and livestock farm integrated controlling service through MapReduce Model-based parallel data processing. Lastly, it also provides REST-based web service so that users can receive the service on various platforms, such as PCs or mobile devices.

• Journal of the Korea Concrete Institute
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• v.14 no.3
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• pp.291-298
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• 2002

Recently, construction of reinforced concrete tall buildings is widely increased according to the improvement of material quality and design technology. Therefore, differential shortenings of columns due to elastic, creep, and shrinkage have been an important issue. But it has been neglected to predict the Inelastic behavior of RC structures even though those deformations make a serious problem on the partition wall, external cladding, duct, etc. In this paper, analysis system for prediction and compensation of the differential column shortenings considering time-dependent deformations and construction sequence is developed using the objected-oriented technique. Developed analysis system considers the construction sequence, especially time-dependent deformation in early days, and is composed of input module, database module, database store module, analysis module, and analysis result generation module. Graphic user interface(GUI) is supported for user's convenience. After performing the analysis, the output results like deflections and member forces according to the time can be observed in the generation module using the graphic diagram, table, and chart supported by the integrated environment.

• Korean Institute of Interior Design Journal
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• no.19
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• pp.30-37
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• 1999

This study presents a methods on the construction of integrated system for the purpose of automation of design plans, calculation of quantity of materials and estimation by abstracting information on building materials which is produced on the course of three dimension modeling by using computer. Therefore, an object oriented methodology is introduced to compose design informations in three dimension, space for unifying building informations, and expressing properties of building factors and materials, and to construct a database for computers to recognize architecture informations. An object indicates a conceptual individual existing in real world or existence of individual and necessity in composing a building could be called as objects such as column, wall, beam, slab, door and window and these contain materiality and immateriality. It is systemized to which properties of these building's objects are installed by the user of computer and by API(Application Programming Interface), chosen informations automatically converse to each unit work such as design plan structure plan, calculation of amount of materials, etc.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.3
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• pp.591-596
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• 2012

Recently, the efficient management system for photovoltaic power plants has been required due to the continuously increasing construction of photovoltaic power plants. In this paper, we propose a cloud-based intelligent management system for many photovoltaic power plants. The proposed system stores the measured data of power plants using Hadoop HBase which is a column-oriented database, and processes the calculations of performance, efficiency, and prediction the amount of power generation by parallel processing based on Map-Reduce model. And, Web-based data visualization module allows the administrator to provide information in various forms.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.6
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• pp.672-677
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• 2010

Recently, the efficient management system for large-scale sensor data has been required due to the increasing deployment of large-scale sensor networks. In this paper, we propose a cloud-based sensor data management system with low cast, high scalability, and efficiency. Sensor data in sensor networks are transmitted to the cloud through a cloud-gateway. At this point, outlier detection and event processing is performed. Transmitted sensor data are stored in the Hadoop HBase, distributed column-oriented database, and processed in parallel by query processing module designed as the MapReduce model. The proposed system can be work with the application of a variety of platforms, because processed results are provided through REST-based web service.