Analysis of database performance with dynamic locking
Journal of the ACM (JACM)
On the analytical modeling of database concurrency control
Journal of the ACM (JACM)
The dangers of replication and a solution
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
A mean value performance model for locking in databases: the waiting case
PODS '84 Proceedings of the 3rd ACM SIGACT-SIGMOD symposium on Principles of database systems
On a More Realistic Lock Contention Model and Its Analysis
Proceedings of the Tenth International Conference on Data Engineering
Analysis of locking behavior in three real database systems
The VLDB Journal — The International Journal on Very Large Data Bases
Kernel independent component analysis
The Journal of Machine Learning Research
BI batch manager: a system for managing batch workloads on enterprise data-warehouses
EDBT '08 Proceedings of the 11th international conference on Extending database technology: Advances in database technology
PQR: Predicting Query Execution Times for Autonomous Workload Management
ICAC '08 Proceedings of the 2008 International Conference on Autonomic Computing
Predicting Multiple Metrics for Queries: Better Decisions Enabled by Machine Learning
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Proceedings of the first joint WOSP/SIPEW international conference on Performance engineering
Update rewriting and integrity constraint maintenance in a schema evolution support system: PRISM++
Proceedings of the VLDB Endowment
Predicting completion times of batch query workloads using interaction-aware models and simulation
Proceedings of the 14th International Conference on Extending Database Technology
Predicting system performance for multi-tenant database workloads
Proceedings of the Fourth International Workshop on Testing Database Systems
Workload-aware database monitoring and consolidation
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Performance prediction for concurrent database workloads
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Multi-query SQL progress indicators
EDBT'06 Proceedings of the 10th international conference on Advances in Database Technology
Modelling database lock-contention in architecture-level performance simulation
Proceedings of the 5th ACM/SPEC international conference on Performance engineering
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Database administrators of Online Transaction Processing (OLTP) systems constantly face difficult questions. For example, "What is the maximum throughput I can sustain with my current hardware?", "How much disk I/O will my system perform if the requests per second double?", or "What will happen if the ratio of transactions in my system changes?". Resource prediction and performance analysis are both vital and difficult in this setting. Here the challenge is due to high degrees of concurrency, competition for resources, and complex interactions between transactions, all of which non-linearly impact performance. Although difficult, such analysis is a key component in enabling database administrators to understand which queries are eating up the resources, and how their system would scale under load. In this paper, we introduce our framework, called DBSeer, that addresses this problem by employing statistical models that provide resource and performance analysis and prediction for highly concurrent OLTP workloads. Our models are built on a small amount of training data from standard log information collected during normal system operation. These models are capable of accurately measuring several performance metrics, including resource consumption on a per-transaction-type basis, resource bottlenecks, and throughput at different load levels. We have validated these models on MySQL/Linux with numerous experiments on standard benchmarks (TPC-C) and real workloads (Wikipedia), observing high accuracy (within a few percent error) when predicting all of the above metrics.