{"title":"信息过滤器的批处理","authors":"Peter M. Fischer, Donald Kossmann","doi":"10.1109/ICDE.2005.25","DOIUrl":null,"url":null,"abstract":"This paper describes batching, a novel technique in order to improve the throughput of an information filter (e.g. message broker or publish & subscribe system). Rather than processing each message individually, incoming messages are reordered, grouped and a whole group of similar messages is processed. This paper presents alternative strategies to do batching. Extensive performance experiments are conducted on those strategies in order to compare their tradeoffs.","PeriodicalId":297231,"journal":{"name":"21st International Conference on Data Engineering (ICDE'05)","volume":"529 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"22","resultStr":"{\"title\":\"Batched processing for information filters\",\"authors\":\"Peter M. Fischer, Donald Kossmann\",\"doi\":\"10.1109/ICDE.2005.25\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes batching, a novel technique in order to improve the throughput of an information filter (e.g. message broker or publish & subscribe system). Rather than processing each message individually, incoming messages are reordered, grouped and a whole group of similar messages is processed. This paper presents alternative strategies to do batching. Extensive performance experiments are conducted on those strategies in order to compare their tradeoffs.\",\"PeriodicalId\":297231,\"journal\":{\"name\":\"21st International Conference on Data Engineering (ICDE'05)\",\"volume\":\"529 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-04-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"22\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"21st International Conference on Data Engineering (ICDE'05)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDE.2005.25\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"21st International Conference on Data Engineering (ICDE'05)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDE.2005.25","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper describes batching, a novel technique in order to improve the throughput of an information filter (e.g. message broker or publish & subscribe system). Rather than processing each message individually, incoming messages are reordered, grouped and a whole group of similar messages is processed. This paper presents alternative strategies to do batching. Extensive performance experiments are conducted on those strategies in order to compare their tradeoffs.