Name
Abstract | ||
|---|---|---|
Resource interferences caused by concurrent queries is one of the key reasons for unpredictable performance and missed workload SLAs in cluster computing systems. Analyzing these inter-query resource interactions is critical in order to answer time-sensitive questions like 'who is creating resource conflicts to my query'. More importantly, diagnosing whether the resource blocked times of a 'victim' query are caused by other queries or some other external factor can help the database administrator narrow down the many possibilities of query performance degradation. We introduce iQCAR, an inter-Query Contention Analyzer, that attributes blame for the slowdown of a query to concurrent queries. iQCAR models the resource conflicts using a multi-level directed acyclic graph that can help administrators compare impacts from concurrent queries, identify most contentious queries, resources and hosts in an online execution for a selected time window. Our experiments using TPCDS queries on Apache Spark show that our approach is substantially more accurate than other methods based on overlap time between concurrent queries.
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Year | DOI | Venue |
|---|---|---|
2019 | 10.1145/3299869.3319904 | Proceedings of the 2019 International Conference on Management of Data |
Keywords | Field | DocType |
blame attribution, contention analysis, data analytics frameworks, performance evaluation, resource interference | Data analysis,Computer science,Spectrum analyzer,Database | Conference |
Volume | ISSN | ISBN |
2019 | 0730-8078 | 978-1-4503-5643-5 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Prajakta Kalmegh | 1 | 9 | 2.68 |
| Shivnath Babu | 2 | 4770 | 277.85 |
| Sudeepa Roy | 3 | 268 | 30.95 |