Snapshot isolation and integrity constraints in replicated databases

Database replication is widely used for fault tolerance and performance. However, it requires replica control to keep data copies consistent despite updates. The traditional correctness criterion for the concurrent execution of transactions in a replicated database is 1-copy-serializability. It is based on serializability, the strongest isolation level in a nonreplicated system. In recent years, however, Snapshot Isolation (SI), a slightly weaker isolation level, has become popular in commercial database systems. There exist already several replica control protocols that provide SI in a replicated system. However, most of the correctness reasoning for these protocols has been rather informal. Additionally, most of the work so far ignores the issue of integrity constraints. In this article, we provide a formal definition of 1-copy-SI using and extending a well-established definition of SI in a nonreplicated system. Our definition considers integrity constraints in a way that conforms to the way integrity constraints are handled in commercial systems. We discuss a set of necessary and sufficient conditions for a replicated history to be producible under 1-copy-SI. This makes our formalism a convenient tool to prove the correctness of replica control algorithms.

[1]  Rachid Guerraoui,et al.  The Database State Machine Approach , 2003, Distributed and Parallel Databases.

[2]  H SchollMarc,et al.  Transactional information systems , 2001 .

[3]  Alan L. Cox,et al.  Distributed Versioning: Consistent Replication for Scaling Back-End Databases of Dynamic Content Web Sites , 2003, Middleware.

[4]  Idit Keidar,et al.  Group communication specifications: a comprehensive study , 2001, CSUR.

[5]  Patrick E. O'Neil,et al.  Generalized isolation level definitions , 2000, Proceedings of 16th International Conference on Data Engineering (Cat. No.00CB37073).

[6]  Rajeev Rastogi,et al.  Update propagation protocols for replicated databates , 1999, SIGMOD '99.

[7]  Patrick Valduriez,et al.  The leganet system: Freshness-aware transaction routing in a database cluster , 2007, Inf. Syst..

[8]  Gerhard Weikum,et al.  ACM Transactions on Database Systems , 2005 .

[9]  Bettina Kemme,et al.  Postgres-R(SI): combining replica control with concurrency control based on snapshot isolation , 2005, 21st International Conference on Data Engineering (ICDE'05).

[10]  Divyakant Agrawal,et al.  Epidemic Algorithms for Replicated Databases , 2003, IEEE Trans. Knowl. Data Eng..

[11]  Ricardo Jiménez-Peris,et al.  Middleware based data replication providing snapshot isolation , 2005, SIGMOD '05.

[12]  Kenneth Salem,et al.  Lazy database replication with snapshot isolation , 2006, VLDB.

[13]  Gustavo Alonso,et al.  MIDDLE-R: Consistent database replication at the middleware level , 2005, TOCS.

[14]  S. S. Ravi,et al.  Deferred updates and data placement in distributed databases , 1996, Proceedings of the Twelfth International Conference on Data Engineering.

[15]  Gustavo Alonso,et al.  Extending DBMSs with satellite databases , 2008, The VLDB Journal.

[16]  Jim Gray,et al.  A critique of ANSI SQL isolation levels , 1995, SIGMOD '95.

[17]  Henry F. Korth,et al.  Replication and consistency: being lazy helps sometimes , 1997, PODS.

[18]  Fernando Pedone,et al.  Database replication using generalized snapshot isolation , 2005, 24th IEEE Symposium on Reliable Distributed Systems (SRDS'05).

[19]  Barbara Liskov,et al.  Weak Consistency: A Generalized Theory and Optimistic Implementations for Distributed Transactions , 1999 .

[20]  Luis Irún-Briz,et al.  Managing Transaction Conflicts in Middleware-based Database Replication Architectures , 2006, 2006 25th IEEE Symposium on Reliable Distributed Systems (SRDS'06).

[21]  KeidarIdit,et al.  Group communication specifications , 2001 .

[22]  Heiko Schuldt,et al.  FAS - A Freshness-Sensitive Coordination Middleware for a Cluster of OLAP Components , 2002, VLDB.

[23]  Gustavo Alonso,et al.  Ganymed: Scalable Replication for Transactional Web Applications , 2004, Middleware.

[24]  Miron Livny,et al.  Conflict detection tradeoffs for replicated data , 1991, TODS.

[25]  Marc H. Scholl,et al.  Transactional information systems: theory, algorithms, and the practice of concurrency control and recovery , 2001, SGMD.

[26]  Gustavo Alonso,et al.  A new approach to developing and implementing eager database replication protocols , 2000, TODS.

[27]  Philip A. Bernstein,et al.  Relaxed-currency serializability for middle-tier caching and replication , 2006, SIGMOD Conference.

[28]  Ricardo Jiménez-Peris,et al.  Consistent and Scalable Cache Replication for Multi-tier J2EE Applications , 2007, Middleware.

[29]  Willy Zwaenepoel,et al.  C-JDBC: Flexible Database Clustering Middleware , 2004, USENIX Annual Technical Conference, FREENIX Track.

[30]  Gerhard Weikum,et al.  Federated Transaction Management with Snapshot Isolation , 1999, FMLDO.

[31]  Michael J. Cahill.  Serializable isolation for snapshot databases , 2009, TODS.

[32]  Esther Pacitti,et al.  Fast Algorithms for Maintaining Replica Consistency in Lazy Master Replicated Databases , 1999, VLDB.

[33]  Alan Fekete,et al.  The Cost of Serializability on Platforms That Use Snapshot Isolation , 2008, 2008 IEEE 24th International Conference on Data Engineering.

[34]  Dennis Shasha,et al.  Making snapshot isolation serializable , 2005, TODS.