{"title":"Ganos Aero:用于大栅格数据管理和处理的云原生系统","authors":"Fei Xiao, Jiong Xie, Zhida Chen, Feifei Li, Zhen Chen, Jianwei Liu, Yinpei Liu","doi":"10.14778/3611540.3611597","DOIUrl":null,"url":null,"abstract":"The development of Earth Observation technology contributes to the production of massive raster data. It is vital to manage and conduct analytical tasks on the raster data. Existing solutions employ dedicated systems for the raster data management and processing, respectively, incurring problems such as data redundancy, difficulty in updating, expensive data transferring and transformation, etc. To cope with these limitations, this demonstration presents Ganos Aero, a cloud-native system for big raster data management and processing. Ganos Aero proposes a unified raster data model for both the data management and processing, which stores a single copy of the raster data and without performing an expensive tiling procedure, and thus achieves significant improvement in the storage and updating efficiency. To enable efficient query and batch task processing, Ganos Aero implements an on-the-fly tile production mechanism, and optimizes its performance using the cloud features including decoupling compute from storage and pushing costly operations closer to the storage layer. Since deployed in Alibaba Cloud in 2022, Ganos Aero has been playing a critical role in many real applications including the modern agriculture, environment monitoring and protection, et al.","PeriodicalId":54220,"journal":{"name":"Proceedings of the Vldb Endowment","volume":"47 1","pages":"0"},"PeriodicalIF":2.6000,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Ganos Aero: A Cloud-Native System for Big Raster Data Management and Processing\",\"authors\":\"Fei Xiao, Jiong Xie, Zhida Chen, Feifei Li, Zhen Chen, Jianwei Liu, Yinpei Liu\",\"doi\":\"10.14778/3611540.3611597\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The development of Earth Observation technology contributes to the production of massive raster data. It is vital to manage and conduct analytical tasks on the raster data. Existing solutions employ dedicated systems for the raster data management and processing, respectively, incurring problems such as data redundancy, difficulty in updating, expensive data transferring and transformation, etc. To cope with these limitations, this demonstration presents Ganos Aero, a cloud-native system for big raster data management and processing. Ganos Aero proposes a unified raster data model for both the data management and processing, which stores a single copy of the raster data and without performing an expensive tiling procedure, and thus achieves significant improvement in the storage and updating efficiency. To enable efficient query and batch task processing, Ganos Aero implements an on-the-fly tile production mechanism, and optimizes its performance using the cloud features including decoupling compute from storage and pushing costly operations closer to the storage layer. Since deployed in Alibaba Cloud in 2022, Ganos Aero has been playing a critical role in many real applications including the modern agriculture, environment monitoring and protection, et al.\",\"PeriodicalId\":54220,\"journal\":{\"name\":\"Proceedings of the Vldb Endowment\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2023-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Vldb Endowment\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.14778/3611540.3611597\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Vldb Endowment","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14778/3611540.3611597","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Ganos Aero: A Cloud-Native System for Big Raster Data Management and Processing
The development of Earth Observation technology contributes to the production of massive raster data. It is vital to manage and conduct analytical tasks on the raster data. Existing solutions employ dedicated systems for the raster data management and processing, respectively, incurring problems such as data redundancy, difficulty in updating, expensive data transferring and transformation, etc. To cope with these limitations, this demonstration presents Ganos Aero, a cloud-native system for big raster data management and processing. Ganos Aero proposes a unified raster data model for both the data management and processing, which stores a single copy of the raster data and without performing an expensive tiling procedure, and thus achieves significant improvement in the storage and updating efficiency. To enable efficient query and batch task processing, Ganos Aero implements an on-the-fly tile production mechanism, and optimizes its performance using the cloud features including decoupling compute from storage and pushing costly operations closer to the storage layer. Since deployed in Alibaba Cloud in 2022, Ganos Aero has been playing a critical role in many real applications including the modern agriculture, environment monitoring and protection, et al.
期刊介绍:
The Proceedings of the VLDB (PVLDB) welcomes original research papers on a broad range of research topics related to all aspects of data management, where systems issues play a significant role, such as data management system technology and information management infrastructures, including their very large scale of experimentation, novel architectures, and demanding applications as well as their underpinning theory. The scope of a submission for PVLDB is also described by the subject areas given below. Moreover, the scope of PVLDB is restricted to scientific areas that are covered by the combined expertise on the submission’s topic of the journal’s editorial board. Finally, the submission’s contributions should build on work already published in data management outlets, e.g., PVLDB, VLDBJ, ACM SIGMOD, IEEE ICDE, EDBT, ACM TODS, IEEE TKDE, and go beyond a syntactic citation.