Conflict-driven load control for the avoidance of data-contention thrashing

Moenkeberg, Axel; Weikum, Gerhard

doi:10.1109/icde.1991.131512

Cited by 34 publications

(43 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Work in this area includes techniques for admission control and setting the multi-programming level of the database system [24,[29][30][31]. The proposed techniques perform load control, reacting in different ways to deviations of workload performance metrics from the desired range.…”

Section: Related Workmentioning

confidence: 99%

Interaction-aware scheduling of report-generation workloads

et al. 2011

View full text Add to dashboard Cite

The typical workload in a database system consists of a mix of multiple queries of different types that run concurrently. Interactions among the different queries in a query mix can have a significant impact on database performance. Hence, optimizing database performance requires reasoning about query mixes rather than considering queries individually. Current database systems lack the ability to do such reasoning. We propose a new approach based on planning experiments and statistical modeling to capture the impact of query interactions. Our approach requires no prior assumptions about the internal workings of the database system or the nature and cause of query interactions; making it portable across systems.To demonstrate the potential of modeling and exploiting query interactions, we have developed a novel interactionaware query scheduler for report-generation workloads. Our scheduler, called QShuffler, uses two query scheduling algorithms that leverage models of query interactions. The first algorithm is optimized for workloads where queries are submitted in large batches. The second algorithm targets workloads where queries arrive continuously, and scheduling decisions have to be made on-line. We report an experimental evaluation of QShuffler using TPC-H workloads running on IBM DB2. The evaluation shows that QShuffler, by modeling and exploiting query interactions, can consistently out-

show abstract

Section: Related Workmentioning

confidence: 99%

Interaction-aware scheduling of report-generation workloads

et al. 2011

View full text Add to dashboard Cite

show abstract

“…Load control has been traditionally static requiring tuning by an experienced administrator [20]. Adaptation can be used to perform this tuning automatically.…”

Section: Related Workmentioning

confidence: 99%

“…Adaptation can be used to perform this tuning automatically. In [20] adaptive load control is used to prevent data contention thrashing. The undertaken approach is enacted by monitoring the transaction conflict rate and reducing the degree of concurrency when conflicts go beyond a given threshold.…”

Section: Related Workmentioning

confidence: 99%

“…We use an approach adapted from [11] that only requires to monitor the database load and the achieved throughput in order to adapt the MPL appropriately. Other approaches that we are aware of [20,6] require a deeper knowledge of the database internals, and hence are not appropriate. But even [11] is designed for database internal adaptation.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Adaptive Middleware for Data Replication

et al. 2004

View full text Add to dashboard Cite

Abstract. Dynamically adaptive systems sense their environment and adjust themselves to accommodate to changes in order to maximize performance. Depending on the type of change (e.g., modifications of the load, the type of workload, the available resources, the client distribution, etc.), different adjustments have to be made. Coordinating them is already difficult in a centralized system. Doing so in the currently prevalent component-based distributed systems is even more challenging. In this paper, we present an adaptive distributed middleware for data replication that is able to adjust to changes in the amount of load submitted to the different replicas and to the type of workload submitted. Its novelty lies in combining load-balancing techniques with feedback driven adjustments of multiprogramming levels (number of transactions that are allowed to execute concurrently). An extensive performance analysis shows that the proposed adaptive replication solution can provide high throughput, good scalability, and low response times for changing loads and workloads with little overhead.

show abstract

“…The conflict ratio, which is defined as the ratio of the total number of locks held by txns and the total number of locks held by active txns [Moenkeberg and Weikum 1992;Weikum et al 1994], is related to as conflict ratio ϭ 1/(1 Ϫ ) or conversely ϭ 1 Ϫ 1/conflict ratio.…”

Section: Analysis With Different Per-step Processing Times the Mean mentioning

confidence: 99%

Concurrency control

Thomasian

1998

ACM Comput. Surv.

View full text Add to dashboard Cite

Standard locking (two-phase locking with on-demand lock requests and blocking upon lock conflict) is the primary concurrency control (CC) method for centralized databases. The main source of performance degradation with standard locking is blocking, whereas transaction (txn) restarts to resolve deadlocks have a secondary effect on performance. We provide a performance analysis of standard locking that accurately estimates its performance degradation leading to thrashing. We next introduce two sets of methods to cope with its performance limitations. Restartoriented locking methods selectively abort txns to increase the level of concurrency for active txns with respect to standard locking in high-contention environments. For example, the running-priority method aborts blocked txns based on the essential blocking principle, which only allows blocking by active txns. The waitdepth-limited (WDL) method further minimizes wasted processing by basing abort decisions on the progress made by a txn. Restart waiting serves as a load-control mechanism by deferring the restart of an aborted txn until conflicting txns have left the system. These two methods have performance superior to other restartoriented methods and standard locking in high-contention environments. In twophase processing methods an aborted txn may continue its first phase of execution in "virtual" mode, that is, without requesting any locks, prefetching data for its second execution phase. The second execution phase is shorter since no disk I/O is required, resulting in a lower effective degree of txn concurrency and less data contention. This method is effective provided access invariance prevails; that is, txns access the same set of objects in the second phase as they did in the first. The optimistic die method is appropriate for the first phase and the optimistic kill method for further phases. Lock preclaiming instead of the optimistic kill method in the second phase prevents further restarts, which is a weak point of the optimistic CC method due to the quadratic effect, that is, the probability of failed validation increases as the square of txn size. Several two-phase processing methods are described and shown to outperform restart-oriented locking methods in high-contention environments provided adequate hardware resources are available. This tutorial reviews CC methods based on standard locking, restartoriented locking methods, two-phase processing methods including optimistic CC, and hybrid methods (combining optimistic CC and locking) in centralized systems. Its main goals are as follows: (i) succinctly specify CC methods of interest; (ii) describe models for performance evaluation of CC methods, including new models that alleviate some of the shortcomings of models used in earlier studies; (iii) compare the performance of CC methods; (iv) list insights gained from analytic and simulation studies; (v) review methods to relieve the level of lock contention: special methods for indices and aggregate data; modified txn structures; and relaxed level...

show abstract

Conflict-driven load control for the avoidance of data-contention thrashing

Cited by 34 publications

References 7 publications

Interaction-aware scheduling of report-generation workloads

Interaction-aware scheduling of report-generation workloads

Adaptive Middleware for Data Replication

Concurrency control

Contact Info

Product

Resources

About