Yidan Wang, M. HoseinyFarahabady, Z. Tari, Albert Y. Zomaya
{"title":"大数据流处理","authors":"Yidan Wang, M. HoseinyFarahabady, Z. Tari, Albert Y. Zomaya","doi":"10.1049/PBPC015E_CH7","DOIUrl":null,"url":null,"abstract":"At the beginning of twenty-first century, the research interest of a new model of streamlined data processing has been arising, involving a huge volume of data in today's market that makes it impossible to store and process data along with the traditional way. Data stream processing (DSP) is a data computational paradigm that enables the real-time processing of continuous data streams instead of maintaining the static relationship among them. In this model, a large volume of raw tuple of data enters in a rapid, continuous, and streaming manner to the ecosystem. Such a set of streams is unbounded in size, while the data arrival time and data processing time have an online nature.","PeriodicalId":30498,"journal":{"name":"International Journal of Open Information Technologies","volume":"1 1","pages":"139-158"},"PeriodicalIF":0.0000,"publicationDate":"2018-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"56","resultStr":"{\"title\":\"Big Data stream processing\",\"authors\":\"Yidan Wang, M. HoseinyFarahabady, Z. Tari, Albert Y. Zomaya\",\"doi\":\"10.1049/PBPC015E_CH7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"At the beginning of twenty-first century, the research interest of a new model of streamlined data processing has been arising, involving a huge volume of data in today's market that makes it impossible to store and process data along with the traditional way. Data stream processing (DSP) is a data computational paradigm that enables the real-time processing of continuous data streams instead of maintaining the static relationship among them. In this model, a large volume of raw tuple of data enters in a rapid, continuous, and streaming manner to the ecosystem. Such a set of streams is unbounded in size, while the data arrival time and data processing time have an online nature.\",\"PeriodicalId\":30498,\"journal\":{\"name\":\"International Journal of Open Information Technologies\",\"volume\":\"1 1\",\"pages\":\"139-158\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-03-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"56\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Open Information Technologies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1049/PBPC015E_CH7\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Open Information Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1049/PBPC015E_CH7","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
At the beginning of twenty-first century, the research interest of a new model of streamlined data processing has been arising, involving a huge volume of data in today's market that makes it impossible to store and process data along with the traditional way. Data stream processing (DSP) is a data computational paradigm that enables the real-time processing of continuous data streams instead of maintaining the static relationship among them. In this model, a large volume of raw tuple of data enters in a rapid, continuous, and streaming manner to the ecosystem. Such a set of streams is unbounded in size, while the data arrival time and data processing time have an online nature.