Query Processing in a Fragmented Relational Distributed System: Mermaid
IEEE Transactions on Software Engineering - Annals of discrete mathematics, 24
Data access for the masses through OLE DB
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Microsoft universal data access platform
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Query processing in a system for distributed databases (SDD-1)
ACM Transactions on Database Systems (TODS)
Enabling component databases with OLE DB
Component database systems
Essential COM
IEEE Annals of the History of Computing
OLE DB: A Component DBMS Architecture
ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
Optimizing Queries Across Diverse Data Sources
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
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RIDE '95 Proceedings of the 5th International Workshop on Research Issues in Data Engineering-Distributed Object Management (RIDE-DOM'95)
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SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Extending postgreSQL to support distributed/heterogeneous query processing
DASFAA'07 Proceedings of the 12th international conference on Database systems for advanced applications
Cluster-and-conquer: hierarchical multi-metric query processing in large-scale database federations
Proceedings of the Fourteenth International Database Engineering & Applications Symposium
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Proceedings of the first international workshop on Network-aware data management
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This paper presents an architecture overview of the distributed, heterogeneous query processor (DHQP) in the Microsoft SQL Server database system to enable queries over a large collection of diverse data sources. The paper highlights three salient aspects of the architecture. First, the system introduces well-defined abstractions such as connections, commands, and rowsets that enable sources to plug into the system. These abstractions are formalized by the OLE DB data access interfaces. The generality of OLE DB and its broad industry adoption enables our system to reach a very large collection of diverse data sources ranging from personal productivity tools, to database management systems, to file system data. Second, the DHQP is built-in to the relational optimizer and execution engine of the system. This enables DH queries and updates to benefit from the cost-based algebraic transformations and execution strategies available in the system. Finally, the architecture is inherently extensible to support new data sources as they emerge as well as serves as a key extensibility point for the relational engine to add new features such as full-text search and distributed partitioned views.