Prajakta Kalmegh, Harrison Lundberg, Frederick Xu, Shivnath Babu, Sudeepa Roy
{"title":"iQCAR:集群计算框架内查询争用分析器的演示。","authors":"Prajakta Kalmegh, Harrison Lundberg, Frederick Xu, Shivnath Babu, Sudeepa Roy","doi":"10.1145/3183713.3193567","DOIUrl":null,"url":null,"abstract":"<p><p>Unpredictability in query runtimes can arise in a shared cluster as a result of resource contentions caused by inter-query interactions. iQCAR - <i>i</i>nter <b>Q</b>uery <b>C</b>ontention <b>A</b>nalyze<b>R</b> is a system that formally models these interferences between concurrent queries and provides a framework to attribute blame for contentions. iQCAR leverages a multi-level directed acyclic graph called iQC-Graph to diagnose the aberrations in query schedules that lead to these resource contentions. The demonstration will enable users to perform a step-wise deep exploration of such resource contentions faced by a query at various stages of its execution. The interface will allow users to identify top-<i>k</i> victims and sources of contentions, diagnose high-contention nodes and resources in the cluster, and rank their impacts on the performance of a query. Users will also be able to navigate through a set of rules recommended by iQCAR to compare how application of each rule by the cluster scheduler resolves the contentions in subsequent executions.</p>","PeriodicalId":87344,"journal":{"name":"Proceedings. ACM-SIGMOD International Conference on Management of Data","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/3183713.3193567","citationCount":"6","resultStr":"{\"title\":\"iQCAR: A Demonstration of an Inter-Query Contention Analyzer for Cluster Computing Frameworks.\",\"authors\":\"Prajakta Kalmegh, Harrison Lundberg, Frederick Xu, Shivnath Babu, Sudeepa Roy\",\"doi\":\"10.1145/3183713.3193567\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Unpredictability in query runtimes can arise in a shared cluster as a result of resource contentions caused by inter-query interactions. iQCAR - <i>i</i>nter <b>Q</b>uery <b>C</b>ontention <b>A</b>nalyze<b>R</b> is a system that formally models these interferences between concurrent queries and provides a framework to attribute blame for contentions. iQCAR leverages a multi-level directed acyclic graph called iQC-Graph to diagnose the aberrations in query schedules that lead to these resource contentions. The demonstration will enable users to perform a step-wise deep exploration of such resource contentions faced by a query at various stages of its execution. The interface will allow users to identify top-<i>k</i> victims and sources of contentions, diagnose high-contention nodes and resources in the cluster, and rank their impacts on the performance of a query. Users will also be able to navigate through a set of rules recommended by iQCAR to compare how application of each rule by the cluster scheduler resolves the contentions in subsequent executions.</p>\",\"PeriodicalId\":87344,\"journal\":{\"name\":\"Proceedings. ACM-SIGMOD International Conference on Management of Data\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1145/3183713.3193567\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. ACM-SIGMOD International Conference on Management of Data\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3183713.3193567\",\"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. ACM-SIGMOD International Conference on Management of Data","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3183713.3193567","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
iQCAR: A Demonstration of an Inter-Query Contention Analyzer for Cluster Computing Frameworks.
Unpredictability in query runtimes can arise in a shared cluster as a result of resource contentions caused by inter-query interactions. iQCAR - inter Query Contention AnalyzeR is a system that formally models these interferences between concurrent queries and provides a framework to attribute blame for contentions. iQCAR leverages a multi-level directed acyclic graph called iQC-Graph to diagnose the aberrations in query schedules that lead to these resource contentions. The demonstration will enable users to perform a step-wise deep exploration of such resource contentions faced by a query at various stages of its execution. The interface will allow users to identify top-k victims and sources of contentions, diagnose high-contention nodes and resources in the cluster, and rank their impacts on the performance of a query. Users will also be able to navigate through a set of rules recommended by iQCAR to compare how application of each rule by the cluster scheduler resolves the contentions in subsequent executions.