{"title":"多MapReduce和衍生投影数据库:支持PrefixSpan可扩展性的新方法","authors":"P. N. Sabrina, G. A. Putri Saptawati","doi":"10.1109/ICODSE.2015.7436988","DOIUrl":null,"url":null,"abstract":"To support PrefixSpan scalability, there exits two problems regarding its implementation in MapReduce framework. The first problem is related to parsing & analyzing big data, while the second one is related to managing projected databases. In this paper, we propose two methods i.e. Multiple MapReduce and Derivative Projected Database to overcome the first and the second problems. Our experiments show that those proposed method can significantly reduce execution time in supporting the scalability of PrefixSpan.","PeriodicalId":374006,"journal":{"name":"2015 International Conference on Data and Software Engineering (ICoDSE)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Multiple MapReduce and derivative projected database: New approach for supporting PrefixSpan scalability\",\"authors\":\"P. N. Sabrina, G. A. Putri Saptawati\",\"doi\":\"10.1109/ICODSE.2015.7436988\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To support PrefixSpan scalability, there exits two problems regarding its implementation in MapReduce framework. The first problem is related to parsing & analyzing big data, while the second one is related to managing projected databases. In this paper, we propose two methods i.e. Multiple MapReduce and Derivative Projected Database to overcome the first and the second problems. Our experiments show that those proposed method can significantly reduce execution time in supporting the scalability of PrefixSpan.\",\"PeriodicalId\":374006,\"journal\":{\"name\":\"2015 International Conference on Data and Software Engineering (ICoDSE)\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Conference on Data and Software Engineering (ICoDSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICODSE.2015.7436988\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Data and Software Engineering (ICoDSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICODSE.2015.7436988","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multiple MapReduce and derivative projected database: New approach for supporting PrefixSpan scalability
To support PrefixSpan scalability, there exits two problems regarding its implementation in MapReduce framework. The first problem is related to parsing & analyzing big data, while the second one is related to managing projected databases. In this paper, we propose two methods i.e. Multiple MapReduce and Derivative Projected Database to overcome the first and the second problems. Our experiments show that those proposed method can significantly reduce execution time in supporting the scalability of PrefixSpan.
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