{"title":"对斗式排序进行了详细的实验分析","authors":"Neetu Faujdar, Shipra Saraswat","doi":"10.1109/CONFLUENCE.2017.7943114","DOIUrl":null,"url":null,"abstract":"The bucket sort is a non-comparison sorting algorithm in which elements are scattered over the buckets. We have concluded, based on state-of-art that most of the researchers have been using the insertion sort within buckets. The other sorting technique is also used in many papers over the buckets. From the state-of-art of bucket sort, we have analyzed that insertion sort is preferable in case of low volume of data to be sorted. In this work, authors have used the merge, count and insertion sort separately over the buckets and the results are compared with each other. The sorting benchmark has been used to test the algorithms. For testing the algorithms, sorting benchmark has been used. We have defined the threshold (τ) defined the threshold for saving the time and space of the algorithms. Results indicate that, count sort comes out to be more efficient within the buckets for every type of dataset.","PeriodicalId":6651,"journal":{"name":"2017 7th International Conference on Cloud Computing, Data Science & Engineering - Confluence","volume":"1 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"The detailed experimental analysis of bucket sort\",\"authors\":\"Neetu Faujdar, Shipra Saraswat\",\"doi\":\"10.1109/CONFLUENCE.2017.7943114\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The bucket sort is a non-comparison sorting algorithm in which elements are scattered over the buckets. We have concluded, based on state-of-art that most of the researchers have been using the insertion sort within buckets. The other sorting technique is also used in many papers over the buckets. From the state-of-art of bucket sort, we have analyzed that insertion sort is preferable in case of low volume of data to be sorted. In this work, authors have used the merge, count and insertion sort separately over the buckets and the results are compared with each other. The sorting benchmark has been used to test the algorithms. For testing the algorithms, sorting benchmark has been used. We have defined the threshold (τ) defined the threshold for saving the time and space of the algorithms. Results indicate that, count sort comes out to be more efficient within the buckets for every type of dataset.\",\"PeriodicalId\":6651,\"journal\":{\"name\":\"2017 7th International Conference on Cloud Computing, Data Science & Engineering - Confluence\",\"volume\":\"1 1\",\"pages\":\"1-6\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 7th International Conference on Cloud Computing, Data Science & Engineering - Confluence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CONFLUENCE.2017.7943114\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 7th International Conference on Cloud Computing, Data Science & Engineering - Confluence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CONFLUENCE.2017.7943114","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The bucket sort is a non-comparison sorting algorithm in which elements are scattered over the buckets. We have concluded, based on state-of-art that most of the researchers have been using the insertion sort within buckets. The other sorting technique is also used in many papers over the buckets. From the state-of-art of bucket sort, we have analyzed that insertion sort is preferable in case of low volume of data to be sorted. In this work, authors have used the merge, count and insertion sort separately over the buckets and the results are compared with each other. The sorting benchmark has been used to test the algorithms. For testing the algorithms, sorting benchmark has been used. We have defined the threshold (τ) defined the threshold for saving the time and space of the algorithms. Results indicate that, count sort comes out to be more efficient within the buckets for every type of dataset.