Teradata Us, Inc.

Ncr Corporation

Teradota Us, Inc.

Stephen Andrew Brobst

Douglas Paul Brown

Bhashyam Ramesh

Anita Richards

Todd A Walter

Louis Martin Burger

Frank Roderic Vandervort

Jaiprakash G Chimanchode

Awny Kayed Al-Omari

Donald Raymond Pederson

Hoa Thu Tran

Sai Pavan Kumar Pakala

Pieter Lessing

Ojustwin Naik

Oliver Ratzesberger

Louis Benton Landry

Pratik Patodi

Dhrubajyoti Roy

Mark Crosby

Naveen Thaliyil Sankaran

Edwina R Redd

Lovlean Arora

Sourabh Maity

Kim Nguyen Hargett

William A Matera

Lily W Young

A computer system executes a database management system (DBMS). The DBMS manages a database comprised of DBMS resources. The DBMS receives a request to be executed. The request is a DBMS action to be executed using the DBMS resources. The request includes a predicate specifying a maximum cost for executing the request, and a deadline, specifying a deadline by which the request is to be completed in its execution. The DBMS determines a plurality of workloads under which the request is qualified to execute. Each workload of the plurality of workloads includes a respective set of requests that have common characteristics. Each workload of the plurality of workloads includes a respective cost criterion and a respective elapsed time criterion. The DBMS selects a selected workload from among the plurality of workloads. The selected workload has a selected cost criterion and a selected elapsed time criterion. The DBMS begins execution of the request using the selected workload.

Managing cloud pricing and what-if analysis to meet service level goals

A database system receives a query and determines that the query includes an inner join between a parent table and a child table. The database system determines that the following relationships exists between the parent table and the child table: referential integrity ('RI') between a primary key attribute (pk) in the parent table and a foreign key attribute (fk) in the child table and a temporal relationship constraint ('TRC') between a period attribute in the parent table and a TRC-attribute in the child table. The database system determines that the query satisfies non-temporal join elimination conditions and temporal join elimination conditions and that the query contains no other qualification conditions on the parent table's period attribute and eliminates the inner join when planning execution of the query.

Join elimination enhancement for real world temporal applications

A data store system may include at least one storage device to store a plurality of data and at least one processor with access to the storage device. The at least one processor may receive a plurality of features associated with an environment. The at least one processor may further generate a state representation of the environment based on the plurality of features. The at least one processor may further generate a plurality of predicted future states of the environment based on the state representation. The at least one processor may further generate at least one action to be performed by the environment based on the plurality of predicted future states. The at least one processor may provide the at least one action to the environment to be performed. A method and computer-readable medium are also disclosed.

Autonomous workload management in an analytic platform

An Application Programming Interface (API) processes object storage requests in an object storage format that are received from client applications. A mapper maps the object storage formatted requests into database statements and executes the statements within a database management system. Results returned from the statements are mapped by the mapper to object-storage constructs and provided to the API in object storage format. The object storage formatted requests are provided from the API to the client applications to satisfy the original client applications' requests.

Seamless integration between object-based environments and database environments

A database system receives a query to be processed. The database system has resources. A user assigns the query to a tier of resource allocation priorities in a hierarchy of tiers. The tier has been designated as being automatically managed by the database system. The tier has a plurality of levels of priority for resource allocation (LPRAs). The database system decomposes the query into a first step and a set of subsequent steps. The first step has a beginning and each of the set of subsequent steps has a respective beginning. The database system assigns the first step to a first LPRA, wherein executing the query at the first LPRA is projected by the database system to satisfy a service level goal (SLG) within a on_schedule_range of the SLG. The database system determines during execution of the set of subsequent steps that the query is no longer projected to satisfy the SLG within the on_schedule_range of the SLG and, as a result, assigns one of the set of subsequent steps to a second LPRA different from the first LPRA, wherein executing the query at the second LPRA is projected by the database system to return execution of the query to within the on_schedule_range of the SLG.

Automatic resource allocation design for satisfying service level goals of mixed workload queries in a database system

A data-warehousing system allows various areas of an enterprise to view data at varying levels of data freshness. The system acquires data that represents an event in the life of a business enterprise, such as a transaction between the enterprise and one of its customers, and loads this data into a database table. The system then makes the data available for retrieval from the table and stores information indicating when the data was made available for retrieval. In some embodiments, the system also acquires data that is related to and more current than the data representing the event and stores the more current data in the database. The system then stores information indicating when the more current data was stored in the database. Such a data warehouse allows decision-makers in the business to see some information (e.g., customer transaction or account data) up-to-the-moment and other information as it stood at some specific point-in-time, such as at the end of the previous month. The data-warehousing system does this without requiring duplication of data, i.e., without requiring the replication of data in multiple databases or tables. The system allows the enterprise to maintain all of its data in a single database with refresh periods as short as the enterprise wishes. Departments that demand data that changes less frequently can view the data as it stood at some point prior to the last refresh.

Using point-in-time views in a database

A database-management system (DBMS) initiates execution of an incoming database query according to an initial query-execution plan that identifies an expected path for execution. Then, at some point after execution of the query has begun, the DBMS concludes that execution has not proceeded along the expected path and, in response, chooses an alternative query-execution plan for continued execution of the query.

Self-adjusting database-query optimizer

A database system includes an optimizer to generate resource estimates regarding execution of a request in the database system, and a regulator to monitor execution of a request and to adjust a priority level of the request based on the monitored execution and based on the resource estimates provided by the optimizer. The regulator is executable to further feed back statistics regarding execution of the request to the optimizer to improve accuracy of resource estimates provided by the optimizer.

Database system having a regulator to provide feedback statistics to an optimizer

A query is received. It is determined that the query includes an inner join between a parent table and a child table. It is determined that the following relationships exist between the parent table and the child table: referential integrity ('RI') between a primary key attribute (pk) in the parent table and a foreign key attribute (fk) in the child table, where 'attribute' is defined to mean one or more columns, and a temporal relationship constraint (&#x201c;TRC&#x201d;) between a period attribute in the parent table and a TRC-attribute in the child table, the TRC-attribute being a date or time attribute. It is determined that the query does not access any attribute in the parent table other than the pk. It is determined that the query specifies an equality predicate of the form pk=fk. It is determined that the query selects a snapshot from the parent using a predicate of the form parent.[period attribute] contains a point in time (t). It is determined that the query selects from the child those rows whose TRC-attribute is equal to or prior to t. The inner join is eliminated when planning execution of the query. The query is executed to produce a result. The result is saved.

Eliminating inner joins based on a temporal relationship constraint

A database system includes an optimizer to generate resource estimates regarding execution of a request in the database system, and a regulator to monitor execution of a request and to adjust a priority level of the request based on the monitored execution and based on the resource estimates provided by the optimizer.

Database system having a regulator that performs workload regulation based on optimizer estimates

A database system includes a regulator subsystem that is configured to attempt to satisfy service level goals of multiple workloads that are executing in the database system. The regulator subsystem is configured to monitor execution of a particular request belonging to a particular workload and to assign, at plural event intervals, corresponding priority levels to the particular request based on the monitored execution.

Database system having a service level goal responsive regulator

Using point-in-time views to provide varying levels of data freshness

A logical data model (LDM) design methodology that utilizes common or shared subject areas, developed for applications across two or more industries, in the design and construction of data warehouse solutions and logical data models for specific customers. The development and use of shared subject areas provides for more effective new LDM development through re-use of common elements and quicker deployment of horizontal applications on all industries.

Method for developing data warehouse logical data models using shared subject areas

An interactive visual-modeling tool helps a database architect implement a database system. The tool gathers information about data that will form the content of the database, gathers information about one or more applications that will access the database, and gathers information about one or more phases in which the database-implementation project will occur. The tool uses this information to create a model of relationships among the content, the applications, and the project phases and to calculate costs for the implementation project. The tool then presents the model and the calculated costs to a human user through a graphical display.

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Las Vegas, NV, United States of America

Stephen Andrew Brobst