{"title":"实时大数据可视化分析的增量方法","authors":"I. García, Ruben Casado, A. Bouchachia","doi":"10.1109/W-FiCloud.2016.46","DOIUrl":null,"url":null,"abstract":"In the age of Big Data, the real-time interactive visualization is a challenge due to latency of executing calculation over terabytes (even, petabytes) datasets. The execution of an operation has to finish before its outcome is displayed, which would be an issue in those scenarios where low-latency responses are required. To address such a requirement, this paper introduces a new approach for real-time visualization of extremely large data-at-rest as well as data-in-motion by showing intermediate results as soon as they become available. This should allow the data analyst to take decisions in real-time.","PeriodicalId":441441,"journal":{"name":"2016 IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"An Incremental Approach for Real-Time Big Data Visual Analytics\",\"authors\":\"I. García, Ruben Casado, A. Bouchachia\",\"doi\":\"10.1109/W-FiCloud.2016.46\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the age of Big Data, the real-time interactive visualization is a challenge due to latency of executing calculation over terabytes (even, petabytes) datasets. The execution of an operation has to finish before its outcome is displayed, which would be an issue in those scenarios where low-latency responses are required. To address such a requirement, this paper introduces a new approach for real-time visualization of extremely large data-at-rest as well as data-in-motion by showing intermediate results as soon as they become available. This should allow the data analyst to take decisions in real-time.\",\"PeriodicalId\":441441,\"journal\":{\"name\":\"2016 IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW)\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/W-FiCloud.2016.46\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE 4th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/W-FiCloud.2016.46","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Incremental Approach for Real-Time Big Data Visual Analytics
In the age of Big Data, the real-time interactive visualization is a challenge due to latency of executing calculation over terabytes (even, petabytes) datasets. The execution of an operation has to finish before its outcome is displayed, which would be an issue in those scenarios where low-latency responses are required. To address such a requirement, this paper introduces a new approach for real-time visualization of extremely large data-at-rest as well as data-in-motion by showing intermediate results as soon as they become available. This should allow the data analyst to take decisions in real-time.