{"title":"通过即时编译加速数组查询处理","authors":"C. Jucovschi, P. Baumann, Sorin Stancu-Mara","doi":"10.1109/ICDMW.2008.73","DOIUrl":null,"url":null,"abstract":"Interpreted languages frequently suffer from higher processing times as compared to compiled approaches. Typically this happens when complex computations are performed. Array DBMSs, which extend database functionality with multidimensional array modeling and query support, find themselves in exactly this situation: queries often involve a large number of operations, and each such operation is applied to a large number of array elements.In this paper, we propose just-in-time compilation as an optimization method for an interpreted array query language. This is achieved by grouping suitable query nodes into complex operation nodes, for which C code is generated, compiled, and loaded during runtime.We present our approach based on the array DBMS rasdaman, discuss its benefits and its embedding into the rasdaman query evaluation, and show initial, rather promising benchmark results.","PeriodicalId":175955,"journal":{"name":"2008 IEEE International Conference on Data Mining Workshops","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Speeding up Array Query Processing by Just-In-Time Compilation\",\"authors\":\"C. Jucovschi, P. Baumann, Sorin Stancu-Mara\",\"doi\":\"10.1109/ICDMW.2008.73\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Interpreted languages frequently suffer from higher processing times as compared to compiled approaches. Typically this happens when complex computations are performed. Array DBMSs, which extend database functionality with multidimensional array modeling and query support, find themselves in exactly this situation: queries often involve a large number of operations, and each such operation is applied to a large number of array elements.In this paper, we propose just-in-time compilation as an optimization method for an interpreted array query language. This is achieved by grouping suitable query nodes into complex operation nodes, for which C code is generated, compiled, and loaded during runtime.We present our approach based on the array DBMS rasdaman, discuss its benefits and its embedding into the rasdaman query evaluation, and show initial, rather promising benchmark results.\",\"PeriodicalId\":175955,\"journal\":{\"name\":\"2008 IEEE International Conference on Data Mining Workshops\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-12-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 IEEE International Conference on Data Mining Workshops\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDMW.2008.73\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE International Conference on Data Mining Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDMW.2008.73","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Speeding up Array Query Processing by Just-In-Time Compilation
Interpreted languages frequently suffer from higher processing times as compared to compiled approaches. Typically this happens when complex computations are performed. Array DBMSs, which extend database functionality with multidimensional array modeling and query support, find themselves in exactly this situation: queries often involve a large number of operations, and each such operation is applied to a large number of array elements.In this paper, we propose just-in-time compilation as an optimization method for an interpreted array query language. This is achieved by grouping suitable query nodes into complex operation nodes, for which C code is generated, compiled, and loaded during runtime.We present our approach based on the array DBMS rasdaman, discuss its benefits and its embedding into the rasdaman query evaluation, and show initial, rather promising benchmark results.