简要介绍使用apache AsterixDB进行地理空间大数据分析

Akil Sevim, Mehnaz Tabassum Mahin, Tin Vu, Ian Maxon, A. Eldawy, M. Carey, V. Tsotras
{"title":"简要介绍使用apache AsterixDB进行地理空间大数据分析","authors":"Akil Sevim, Mehnaz Tabassum Mahin, Tin Vu, Ian Maxon, A. Eldawy, M. Carey, V. Tsotras","doi":"10.1145/3486189.3490018","DOIUrl":null,"url":null,"abstract":"There is immense potential with spatial data, which is even more significant when combined with temporal or textual features, or both. However, it is expensive to store and analyze spatial data, and it is even more challenging with the combined features due to the additional optimization requirements. There are numerous successful solutions for big spatial data management, but they do not well support non-spatial operations. The options for the systems are even smaller for the open sources systems, and there are not a handful of options that provide good coverage of care about the spatial and non-spatial operations. This tutorial introduces Apache AsterixDB, a scalable open-source Big Data Management System, which supports standard vector spatial data types as well as non-spatial attributes, e.g., numerical, temporal, and textual. The participants will get hands-on experience on how Apache AsterixDB can efficiently process complex SQL++ queries that require multiple special handling by a team from its kitchen.","PeriodicalId":258964,"journal":{"name":"Proceedings of the 3rd ACM SIGSPATIAL International Workshop on APIs and Libraries for Geospatial Data Science","volume":"71 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A brief introduction to geospatial big data analytics with apache AsterixDB\",\"authors\":\"Akil Sevim, Mehnaz Tabassum Mahin, Tin Vu, Ian Maxon, A. Eldawy, M. Carey, V. Tsotras\",\"doi\":\"10.1145/3486189.3490018\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"There is immense potential with spatial data, which is even more significant when combined with temporal or textual features, or both. However, it is expensive to store and analyze spatial data, and it is even more challenging with the combined features due to the additional optimization requirements. There are numerous successful solutions for big spatial data management, but they do not well support non-spatial operations. The options for the systems are even smaller for the open sources systems, and there are not a handful of options that provide good coverage of care about the spatial and non-spatial operations. This tutorial introduces Apache AsterixDB, a scalable open-source Big Data Management System, which supports standard vector spatial data types as well as non-spatial attributes, e.g., numerical, temporal, and textual. The participants will get hands-on experience on how Apache AsterixDB can efficiently process complex SQL++ queries that require multiple special handling by a team from its kitchen.\",\"PeriodicalId\":258964,\"journal\":{\"name\":\"Proceedings of the 3rd ACM SIGSPATIAL International Workshop on APIs and Libraries for Geospatial Data Science\",\"volume\":\"71 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 3rd ACM SIGSPATIAL International Workshop on APIs and Libraries for Geospatial Data Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3486189.3490018\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 3rd ACM SIGSPATIAL International Workshop on APIs and Libraries for Geospatial Data Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3486189.3490018","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

摘要

空间数据具有巨大的潜力,当与时间或文本特征或两者结合使用时,这种潜力更加显著。然而,存储和分析空间数据的成本很高,并且由于额外的优化要求,使用组合功能更具挑战性。有许多成功的大空间数据管理解决方案,但它们不能很好地支持非空间操作。对于开放源代码系统,系统的选项甚至更少,并且没有几个选项可以很好地覆盖空间和非空间操作。本教程介绍Apache AsterixDB,一个可扩展的开源大数据管理系统,它支持标准的矢量空间数据类型以及非空间属性,如数字、时间和文本。参与者将获得实践经验,了解Apache AsterixDB如何有效地处理复杂的SQL++查询,这些查询需要团队从其厨房进行多次特殊处理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A brief introduction to geospatial big data analytics with apache AsterixDB
There is immense potential with spatial data, which is even more significant when combined with temporal or textual features, or both. However, it is expensive to store and analyze spatial data, and it is even more challenging with the combined features due to the additional optimization requirements. There are numerous successful solutions for big spatial data management, but they do not well support non-spatial operations. The options for the systems are even smaller for the open sources systems, and there are not a handful of options that provide good coverage of care about the spatial and non-spatial operations. This tutorial introduces Apache AsterixDB, a scalable open-source Big Data Management System, which supports standard vector spatial data types as well as non-spatial attributes, e.g., numerical, temporal, and textual. The participants will get hands-on experience on how Apache AsterixDB can efficiently process complex SQL++ queries that require multiple special handling by a team from its kitchen.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信