{"title":"使用NotaQL进行跨系统NoSQL数据转换","authors":"Johannes Schildgen, Thomas Lottermann, S. Deßloch","doi":"10.1145/2926534.2926535","DOIUrl":null,"url":null,"abstract":"The rising adoption of NoSQL technology in enterprises causes a heterogeneous landscape of different data stores. Different stores provide distinct advantages and disadvantages, making it necessary for enterprises to facilitate multiple systems for specific purposes. This resulting polyglot persistence is difficult to handle for developers since some data needs to be replicated and aggregated between different and within the same stores. Currently, there are no uniform tools to perform these data transformations since all stores feature different APIs and data models. In this paper, we present the transformation language NotaQL that allows cross-system data transformations. These transformations are output-oriented, meaning that the structure of a transformation script is similar to that of the output. Besides, we provide an aggregation-centric approach, which makes aggregation operations as easy as possible.","PeriodicalId":393776,"journal":{"name":"Proceedings of the 3rd ACM SIGMOD Workshop on Algorithms and Systems for MapReduce and Beyond","volume":"223 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Cross-system NoSQL data transformations with NotaQL\",\"authors\":\"Johannes Schildgen, Thomas Lottermann, S. Deßloch\",\"doi\":\"10.1145/2926534.2926535\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The rising adoption of NoSQL technology in enterprises causes a heterogeneous landscape of different data stores. Different stores provide distinct advantages and disadvantages, making it necessary for enterprises to facilitate multiple systems for specific purposes. This resulting polyglot persistence is difficult to handle for developers since some data needs to be replicated and aggregated between different and within the same stores. Currently, there are no uniform tools to perform these data transformations since all stores feature different APIs and data models. In this paper, we present the transformation language NotaQL that allows cross-system data transformations. These transformations are output-oriented, meaning that the structure of a transformation script is similar to that of the output. Besides, we provide an aggregation-centric approach, which makes aggregation operations as easy as possible.\",\"PeriodicalId\":393776,\"journal\":{\"name\":\"Proceedings of the 3rd ACM SIGMOD Workshop on Algorithms and Systems for MapReduce and Beyond\",\"volume\":\"223 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-06-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 3rd ACM SIGMOD Workshop on Algorithms and Systems for MapReduce and Beyond\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2926534.2926535\",\"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 SIGMOD Workshop on Algorithms and Systems for MapReduce and Beyond","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2926534.2926535","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Cross-system NoSQL data transformations with NotaQL
The rising adoption of NoSQL technology in enterprises causes a heterogeneous landscape of different data stores. Different stores provide distinct advantages and disadvantages, making it necessary for enterprises to facilitate multiple systems for specific purposes. This resulting polyglot persistence is difficult to handle for developers since some data needs to be replicated and aggregated between different and within the same stores. Currently, there are no uniform tools to perform these data transformations since all stores feature different APIs and data models. In this paper, we present the transformation language NotaQL that allows cross-system data transformations. These transformations are output-oriented, meaning that the structure of a transformation script is similar to that of the output. Besides, we provide an aggregation-centric approach, which makes aggregation operations as easy as possible.