Concurrency control and recovery in database systems
Concurrency control and recovery in database systems
The dangers of replication and a solution
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Replication management using the state-machine approach
Distributed systems (2nd Ed.)
The Database State Machine Approach
Distributed and Parallel Databases
Don't Be Lazy, Be Consistent: Postgres-R, A New Way to Implement Database Replication
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Performance Analysis of Java Group Toolkits: A Case Study
FIDJI '01 Revised Papers from the International Workshop on Scientific Engineering for Distributed Java Applications
Partial Replication in the Database State Machine
NCA '01 Proceedings of the IEEE International Symposium on Network Computing and Applications (NCA'01)
Ganymed: scalable replication for transactional web applications
Proceedings of the 5th ACM/IFIP/USENIX international conference on Middleware
Adaptive middleware for data replication
Proceedings of the 5th ACM/IFIP/USENIX international conference on Middleware
Middleware based data replication providing snapshot isolation
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
DSN '05 Proceedings of the 2005 International Conference on Dependable Systems and Networks
How to Determine a Good Multi-Programming Level for External Scheduling
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Revisiting 1-copy equivalence in clustered databases
Proceedings of the 2006 ACM symposium on Applied computing
C-JDBC: flexible database clustering middleware
ATEC '04 Proceedings of the annual conference on USENIX Annual Technical Conference
Open versus closed: a cautionary tale
NSDI'06 Proceedings of the 3rd conference on Networked Systems Design & Implementation - Volume 3
Serpentine: adaptive middleware for complex heterogeneous distributed systems
Proceedings of the 2008 ACM symposium on Applied computing
Group-Based replication of on-line transaction processing servers
LADC'05 Proceedings of the Second Latin-American conference on Dependable Computing
A simple approach to shared storage database servers
Proceedings of the Third Workshop on Dependable Distributed Data Management
Evaluating Throughput Stability of Protocols for Distributed Middleware
OTM '09 Proceedings of the Confederated International Conferences, CoopIS, DOA, IS, and ODBASE 2009 on On the Move to Meaningful Internet Systems: Part I
Practical database replication
Replication
Improving transaction abort rates without compromising throughput through judicious scheduling
Proceedings of the 28th Annual ACM Symposium on Applied Computing
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Shared-nothing clusters are a well known and cost-effective approach to database server scalability, in particular, with highly intensive read-only workloads typical of many 3-tier web-based applications. The common reliance on a centralized component and a simplistic propagation strategy employed by mainstream solutions however conduct to poor scalability with traditional on-line transaction processing (OLTP), where the update ratio is high. Such approaches also pose an additional obstacle to high availability while introducing a single point of failure. More recently, database replication protocols based on group communication have been shown to overcome such limitations, expanding the applicability of shared-nothing clusters to more demanding transactional workloads. These take simultaneous advantage of total order multicast and transactional semantics to improve on mainstream solutions. However, none has already been widely deployed in a general purpose database management system. In this paper, we argue that a major hurdle for their acceptance is that these proposals have disappointing performance with specific subsets of real-world workloads. Such limitations are deep-rooted and working around them requires in-depth understanding of protocols and changes to applications. We address this issue with a novel protocol that combines multiple transaction execution mechanisms and replication techniques and then show how it avoids the identified pitfalls. Experimental results are obtained with a workload based on the industry standard TPC-C benchmark.