{"title":"数据库查询处理中的偏移值编码","authors":"G. Graefe, Thanh Do","doi":"10.48550/arXiv.2210.00034","DOIUrl":null,"url":null,"abstract":"Recent work shows how offset-value coding speeds up database query execution, not only sorting but also duplicate removal and grouping (aggregation) in sorted streams, order-preserving exchange (shuffle), merge join, and more. It already saves thousands of CPUs in Google's Napa and F1 Query systems, e.g., in grouping algorithms and in log-structured merge-forests. In order to realize the full benefit of interesting orderings, however, query execution algorithms must not only consume and exploit offset-value codes but also produce offset-value codes for the next operator in the pipeline. Our research has sought ways to produce offset-value codes without comparing successive output rows one-by-one, column-by-column. This short paper introduces a new theorem and, based on its proof and a simple corollary, describes in detail how order-preserving algorithms (from filter to merge join and even shuffle) can compute offset-value codes for their outputs. These computations are surprisingly simple and very efficient.","PeriodicalId":88813,"journal":{"name":"Advances in database technology : proceedings. International Conference on Extending Database Technology","volume":"5 1","pages":"464-470"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Offset-value coding in database query processing\",\"authors\":\"G. Graefe, Thanh Do\",\"doi\":\"10.48550/arXiv.2210.00034\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recent work shows how offset-value coding speeds up database query execution, not only sorting but also duplicate removal and grouping (aggregation) in sorted streams, order-preserving exchange (shuffle), merge join, and more. It already saves thousands of CPUs in Google's Napa and F1 Query systems, e.g., in grouping algorithms and in log-structured merge-forests. In order to realize the full benefit of interesting orderings, however, query execution algorithms must not only consume and exploit offset-value codes but also produce offset-value codes for the next operator in the pipeline. Our research has sought ways to produce offset-value codes without comparing successive output rows one-by-one, column-by-column. This short paper introduces a new theorem and, based on its proof and a simple corollary, describes in detail how order-preserving algorithms (from filter to merge join and even shuffle) can compute offset-value codes for their outputs. These computations are surprisingly simple and very efficient.\",\"PeriodicalId\":88813,\"journal\":{\"name\":\"Advances in database technology : proceedings. International Conference on Extending Database Technology\",\"volume\":\"5 1\",\"pages\":\"464-470\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-09-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advances in database technology : proceedings. International Conference on Extending Database Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.48550/arXiv.2210.00034\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in database technology : proceedings. International Conference on Extending Database Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.48550/arXiv.2210.00034","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Recent work shows how offset-value coding speeds up database query execution, not only sorting but also duplicate removal and grouping (aggregation) in sorted streams, order-preserving exchange (shuffle), merge join, and more. It already saves thousands of CPUs in Google's Napa and F1 Query systems, e.g., in grouping algorithms and in log-structured merge-forests. In order to realize the full benefit of interesting orderings, however, query execution algorithms must not only consume and exploit offset-value codes but also produce offset-value codes for the next operator in the pipeline. Our research has sought ways to produce offset-value codes without comparing successive output rows one-by-one, column-by-column. This short paper introduces a new theorem and, based on its proof and a simple corollary, describes in detail how order-preserving algorithms (from filter to merge join and even shuffle) can compute offset-value codes for their outputs. These computations are surprisingly simple and very efficient.