There are several indexing techniques that can optimize system performances. The choice of the right index type in a schema can improve the DB performances by up to 80%. Unfortunately the illustrations of the various ...There are several indexing techniques that can optimize system performances. The choice of the right index type in a schema can improve the DB performances by up to 80%. Unfortunately the illustrations of the various techniques are scattered over a number of texts and manuals, and the courses for database designers are often somewhat incomplete. The present paper shows a didactical experience which tackles this kind of limitations. In particular, the authors have prepared a textbook that includes twenty-one different index formats; it discusses advantages and disadvantages of each indexing technique, and has been positively validated during advanced courses on relational database design.展开更多
通过分析SQL查询的相似性,提出了一种新的SQL查询的距离函数.通过该距离函数对SQL负载集合进行聚类,并且提取具有代表性的SQL子集,达到减小SQL集合的目的,从而提高基于负载分析的性能优化工具(以物理设计优化为例)的扩展性,同时又不会...通过分析SQL查询的相似性,提出了一种新的SQL查询的距离函数.通过该距离函数对SQL负载集合进行聚类,并且提取具有代表性的SQL子集,达到减小SQL集合的目的,从而提高基于负载分析的性能优化工具(以物理设计优化为例)的扩展性,同时又不会大幅度降低优化的结果.分别采用TPC-H负载和客户数据库的实际负载作为SQL负载集合,通过算法实现和在DB2上进行Index A dv isor实验证实:该算法可以裁剪SQL负载到原有负载的65%和43%;减少Index A dv isor的运行时间达到63%和72%;同时性能的损失分别是8%和4%,证明本算法是行之有效的.展开更多
Data is humongous today because of the extensive use of World WideWeb, Social Media and Intelligent Systems. This data can be very important anduseful if it is harnessed carefully and correctly. Useful information can...Data is humongous today because of the extensive use of World WideWeb, Social Media and Intelligent Systems. This data can be very important anduseful if it is harnessed carefully and correctly. Useful information can beextracted from this massive data using the Data Mining process. The informationextracted can be used to make vital decisions in various industries. Clustering is avery popular Data Mining method which divides the data points into differentgroups such that all similar data points form a part of the same group. Clusteringmethods are of various types. Many parameters and indexes exist for the evaluationand comparison of these methods. In this paper, we have compared partitioningbased methods K-Means, Fuzzy C-Means (FCM), Partitioning AroundMedoids (PAM) and Clustering Large Application (CLARA) on secure perturbeddata. Comparison and identification has been done for the method which performsbetter for analyzing the data perturbed using Extended NMF on the basis of thevalues of various indexes like Dunn Index, Silhouette Index, Xie-Beni Indexand Davies-Bouldin Index.展开更多
Water is an important component in agricultural production for both yield quantity and quality. Although all weather conditions are driving factors in the agricultural sector, the precipitation in rainfed agriculture ...Water is an important component in agricultural production for both yield quantity and quality. Although all weather conditions are driving factors in the agricultural sector, the precipitation in rainfed agriculture is the most limiting weather parameter. Water deficit may occur continuously over the total growing period or during any particular growth stage of the crop. Optical remote sensing is very useful but, in cloudy days it becomes useless. Radar penetrates the cloud and collects information through the backscattering data. Normalized Difference Vegetation Index (NDVI) was extracted from Landsat 8 satellite data and used to calculate Crop Coefficient (Kc). The FAO-Penman-Monteith equation was used to calculate reference evapotranspiration (ETo). NDVI and Land Surface Temperature (LST) were calculated from satellite data and integrated with air temperature measurements to estimate Crop Water Stress Index (CWSI). Then, both CWSI and potential crop evapotranspiration (ETc) were used to calculate actual evapotranspiration (ETa). Sentinel-1 radar data were calibrated using SNAP software. The relation between backscattering (dB) and CWSI was an inverse relationship and R2 was as high as 0.82.展开更多
文摘There are several indexing techniques that can optimize system performances. The choice of the right index type in a schema can improve the DB performances by up to 80%. Unfortunately the illustrations of the various techniques are scattered over a number of texts and manuals, and the courses for database designers are often somewhat incomplete. The present paper shows a didactical experience which tackles this kind of limitations. In particular, the authors have prepared a textbook that includes twenty-one different index formats; it discusses advantages and disadvantages of each indexing technique, and has been positively validated during advanced courses on relational database design.
文摘通过分析SQL查询的相似性,提出了一种新的SQL查询的距离函数.通过该距离函数对SQL负载集合进行聚类,并且提取具有代表性的SQL子集,达到减小SQL集合的目的,从而提高基于负载分析的性能优化工具(以物理设计优化为例)的扩展性,同时又不会大幅度降低优化的结果.分别采用TPC-H负载和客户数据库的实际负载作为SQL负载集合,通过算法实现和在DB2上进行Index A dv isor实验证实:该算法可以裁剪SQL负载到原有负载的65%和43%;减少Index A dv isor的运行时间达到63%和72%;同时性能的损失分别是8%和4%,证明本算法是行之有效的.
文摘Data is humongous today because of the extensive use of World WideWeb, Social Media and Intelligent Systems. This data can be very important anduseful if it is harnessed carefully and correctly. Useful information can beextracted from this massive data using the Data Mining process. The informationextracted can be used to make vital decisions in various industries. Clustering is avery popular Data Mining method which divides the data points into differentgroups such that all similar data points form a part of the same group. Clusteringmethods are of various types. Many parameters and indexes exist for the evaluationand comparison of these methods. In this paper, we have compared partitioningbased methods K-Means, Fuzzy C-Means (FCM), Partitioning AroundMedoids (PAM) and Clustering Large Application (CLARA) on secure perturbeddata. Comparison and identification has been done for the method which performsbetter for analyzing the data perturbed using Extended NMF on the basis of thevalues of various indexes like Dunn Index, Silhouette Index, Xie-Beni Indexand Davies-Bouldin Index.
文摘Water is an important component in agricultural production for both yield quantity and quality. Although all weather conditions are driving factors in the agricultural sector, the precipitation in rainfed agriculture is the most limiting weather parameter. Water deficit may occur continuously over the total growing period or during any particular growth stage of the crop. Optical remote sensing is very useful but, in cloudy days it becomes useless. Radar penetrates the cloud and collects information through the backscattering data. Normalized Difference Vegetation Index (NDVI) was extracted from Landsat 8 satellite data and used to calculate Crop Coefficient (Kc). The FAO-Penman-Monteith equation was used to calculate reference evapotranspiration (ETo). NDVI and Land Surface Temperature (LST) were calculated from satellite data and integrated with air temperature measurements to estimate Crop Water Stress Index (CWSI). Then, both CWSI and potential crop evapotranspiration (ETc) were used to calculate actual evapotranspiration (ETa). Sentinel-1 radar data were calibrated using SNAP software. The relation between backscattering (dB) and CWSI was an inverse relationship and R2 was as high as 0.82.
