{"title":"并行处理器上连接性能的限制因素","authors":"M. Lakshmi, Philip S. Yu","doi":"10.1109/ICDE.1989.47254","DOIUrl":null,"url":null,"abstract":"The effectiveness of parallel processing of relational join operations is examined. The skew in the distribution of join attribute values and the stochastic nature of the task processing times are identified as the major factors that can affect the effective utilization of parallelism. When many small processors are used in the parallel architecture, the skew can result in some processors becoming sources of bottleneck while other processors are being under utilized. Even in the absence of skew, the variations in the processing times of the parallel tasks belonging to a query can lead to high task synchronization delay and impact the maximum speedup achievable through parallel execution. Analytic expressions for join execution time are developed for different task time distributions with or without skew.<<ETX>>","PeriodicalId":329505,"journal":{"name":"[1989] Proceedings. Fifth International Conference on Data Engineering","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1989-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"27","resultStr":"{\"title\":\"Limiting factors of join performance on parallel processors\",\"authors\":\"M. Lakshmi, Philip S. Yu\",\"doi\":\"10.1109/ICDE.1989.47254\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The effectiveness of parallel processing of relational join operations is examined. The skew in the distribution of join attribute values and the stochastic nature of the task processing times are identified as the major factors that can affect the effective utilization of parallelism. When many small processors are used in the parallel architecture, the skew can result in some processors becoming sources of bottleneck while other processors are being under utilized. Even in the absence of skew, the variations in the processing times of the parallel tasks belonging to a query can lead to high task synchronization delay and impact the maximum speedup achievable through parallel execution. Analytic expressions for join execution time are developed for different task time distributions with or without skew.<<ETX>>\",\"PeriodicalId\":329505,\"journal\":{\"name\":\"[1989] Proceedings. Fifth International Conference on Data Engineering\",\"volume\":\"41 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1989-02-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"27\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[1989] Proceedings. Fifth International Conference on Data Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDE.1989.47254\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1989] Proceedings. Fifth International Conference on Data Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDE.1989.47254","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Limiting factors of join performance on parallel processors
The effectiveness of parallel processing of relational join operations is examined. The skew in the distribution of join attribute values and the stochastic nature of the task processing times are identified as the major factors that can affect the effective utilization of parallelism. When many small processors are used in the parallel architecture, the skew can result in some processors becoming sources of bottleneck while other processors are being under utilized. Even in the absence of skew, the variations in the processing times of the parallel tasks belonging to a query can lead to high task synchronization delay and impact the maximum speedup achievable through parallel execution. Analytic expressions for join execution time are developed for different task time distributions with or without skew.<>