Replication in the harp file system
SOSP '91 Proceedings of the thirteenth ACM symposium on Operating systems principles
ACM Transactions on Database Systems (TODS)
The dangers of replication and a solution
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Transaction Processing: Concepts and Techniques
Transaction Processing: Concepts and Techniques
The ClustRa Telecom Database: High Availability, High Throughput, and Real-Time Response
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Parallel Processing with Autonomous Databases in a Cluster System
On the Move to Meaningful Internet Systems, 2002 - DOA/CoopIS/ODBASE 2002 Confederated International Conferences DOA, CoopIS and ODBASE 2002
Database Replication Techniques: A Three Parameter Classification
SRDS '00 Proceedings of the 19th IEEE Symposium on Reliable Distributed Systems
Non-Intrusive, Parallel Recovery of Replicated Data
SRDS '02 Proceedings of the 21st IEEE Symposium on Reliable Distributed Systems
Optimized Data Loading for a Multi-Terabyte Sky Survey Repository
SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
An integrated approach to recovery and high availability in an updatable, distributed data warehouse
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Remembrance of streams past: overload-sensitive management of archived streams
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
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Some burgeoning web applications, such as web search engines, need to track, store and analyze massive real-time users' access logs with high availability of 24*7. The traditional high availability approaches towards general-purpose transaction applications are always not efficient enough to store these high-rate insertion-only archived streams. This paper presents an integrated approach to store these archived streams in a database cluster and recover it quickly. This approach is based on our simplified replication protocol and high performance data loading and query strategy. The experiments show that our approach can reach efficient data loading and query and get shorter recovery time than the traditional database cluster recovery methods.