{"title":"缓存的正确性","authors":"Aspen Olmsted","doi":"10.23919/i-society.2017.8354686","DOIUrl":null,"url":null,"abstract":"In this paper, we investigate the problem of providing application scalability through the caching of data persisted in a database system. We develop algorithms for ensuring the cache remains semantically fresh while providing high availability. We utilize memory tables and hashmap indexes on the server to decrease access time to the data in the server.","PeriodicalId":285075,"journal":{"name":"2017 International Conference on Information Society (i-Society)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Cache correctness\",\"authors\":\"Aspen Olmsted\",\"doi\":\"10.23919/i-society.2017.8354686\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we investigate the problem of providing application scalability through the caching of data persisted in a database system. We develop algorithms for ensuring the cache remains semantically fresh while providing high availability. We utilize memory tables and hashmap indexes on the server to decrease access time to the data in the server.\",\"PeriodicalId\":285075,\"journal\":{\"name\":\"2017 International Conference on Information Society (i-Society)\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Conference on Information Society (i-Society)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/i-society.2017.8354686\",\"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 International Conference on Information Society (i-Society)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/i-society.2017.8354686","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper, we investigate the problem of providing application scalability through the caching of data persisted in a database system. We develop algorithms for ensuring the cache remains semantically fresh while providing high availability. We utilize memory tables and hashmap indexes on the server to decrease access time to the data in the server.