{"title":"基于缓存的冰山查询评估","authors":"V. Shankar, C. V. Guru Rao","doi":"10.1109/ICCCT2.2014.7066694","DOIUrl":null,"url":null,"abstract":"Nowadays, it is more demanded for techniques that are efficient in retrieval of small results from large data sets. Iceberg queries are such a kind of queries which accepts large data as input and process them for retrieve small results upon user specified threshold (T). Earlier, the iceberg queries are processed by many ways but are compromised in speed with which the data is retrieved. Thus lots of researchers are concentrating on improvement of iceberg query evaluation methods. Compressed bitmap index is an efficient technique which is developed recently to answer iceberg queries. In this paper, we proposed “Cache Based Evaluation of Iceberg Queries”. An iceberg query is evaluated using compressed bitmap index technique for threshold equals to 1, save results in cache memory for future reference. For further evaluation of an iceberg query thresholds greater than 1 are just picking the results from the cache memory instead of executing once again on the database table. Thus strategy clearly stating that, an execution time of IBQ is improved by avoiding repetition of an evaluation process by multiple times. Experimental results are demonstrating our cache based evaluation strategy is better than existing strategy.","PeriodicalId":6860,"journal":{"name":"2021 RIVF International Conference on Computing and Communication Technologies (RIVF)","volume":"2021 1","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Cache based evaluation of iceberg queries\",\"authors\":\"V. Shankar, C. V. Guru Rao\",\"doi\":\"10.1109/ICCCT2.2014.7066694\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Nowadays, it is more demanded for techniques that are efficient in retrieval of small results from large data sets. Iceberg queries are such a kind of queries which accepts large data as input and process them for retrieve small results upon user specified threshold (T). Earlier, the iceberg queries are processed by many ways but are compromised in speed with which the data is retrieved. Thus lots of researchers are concentrating on improvement of iceberg query evaluation methods. Compressed bitmap index is an efficient technique which is developed recently to answer iceberg queries. In this paper, we proposed “Cache Based Evaluation of Iceberg Queries”. An iceberg query is evaluated using compressed bitmap index technique for threshold equals to 1, save results in cache memory for future reference. For further evaluation of an iceberg query thresholds greater than 1 are just picking the results from the cache memory instead of executing once again on the database table. Thus strategy clearly stating that, an execution time of IBQ is improved by avoiding repetition of an evaluation process by multiple times. Experimental results are demonstrating our cache based evaluation strategy is better than existing strategy.\",\"PeriodicalId\":6860,\"journal\":{\"name\":\"2021 RIVF International Conference on Computing and Communication Technologies (RIVF)\",\"volume\":\"2021 1\",\"pages\":\"1-5\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 RIVF International Conference on Computing and Communication Technologies (RIVF)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCCT2.2014.7066694\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 RIVF International Conference on Computing and Communication Technologies (RIVF)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCT2.2014.7066694","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Nowadays, it is more demanded for techniques that are efficient in retrieval of small results from large data sets. Iceberg queries are such a kind of queries which accepts large data as input and process them for retrieve small results upon user specified threshold (T). Earlier, the iceberg queries are processed by many ways but are compromised in speed with which the data is retrieved. Thus lots of researchers are concentrating on improvement of iceberg query evaluation methods. Compressed bitmap index is an efficient technique which is developed recently to answer iceberg queries. In this paper, we proposed “Cache Based Evaluation of Iceberg Queries”. An iceberg query is evaluated using compressed bitmap index technique for threshold equals to 1, save results in cache memory for future reference. For further evaluation of an iceberg query thresholds greater than 1 are just picking the results from the cache memory instead of executing once again on the database table. Thus strategy clearly stating that, an execution time of IBQ is improved by avoiding repetition of an evaluation process by multiple times. Experimental results are demonstrating our cache based evaluation strategy is better than existing strategy.