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Hongfei Guo

Praveen Seshadri

Ciprian Gerea

James Kelsey Howey

Michiel Johannes Wories

James A Holt

Daniel T Jones

Grigory Pogulsky

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Jonathan David Goldstein

Oscar Gerardo Naim

Raghu Ramakrishnan

Per-Åke Larson

Maciek Sarnowicz

Vipul M Shah

User productivity can be facilitated by providing an interface between a high-level intent and low-level settings that should be configured to achieve the intent. The intent can be expressed in declarative language. The intent can be verified to determine if it conforms to a target, a policy, or both. Policy binding can provide a relationship between the target and the policy. An application view can be provided that allows the user to view a server having one or more databases.

Declarative management framework

Currency and consistency requirements are specified as part of a query against a database that may contain replicated data that is updated asynchronously and therefore may not be completely up to date. The database system constructs query execution plans that include an input selection operator that verifies the currency of a replica and selects a subplan using the replica for execution only when the replica meets the query's currency constraints. It checks possible query execution plans at construction time against the query's consistency constraints and any plans that may produce a result not meeting the consistency constraints are rejected. In this way, the query result is guaranteed to satisfy the query's currency and consistency requirements.

Enforcing currency and consistency constraints in database query processing

Automated sampling and aggregation of performance or other dynamically varying data facilitates user productivity by making data available for a wide range of uses. An automated sampling and aggregration system includes one or more types of data collectors, including a dedicated data collector per machine, multiple data collectors per machine, or an instance-less data collector.

Extensible data collectors

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