Oracle International Corporation

Kenneth Eng

Roger Bolsius

Praful Hebbar

Raghuram Venkatasubramanian

Alextair Dominico Mascarenhas

Samar Lotia

Harvard Pan

Vijayakumar Ranganathan

Rutuja Joshi

Mahadevan Rajagopalan

Yi Ge

Monisha Balaji

Shreya Sawant

Jorge Zuniga

Gilberto Monroy

Luis Ramirez

David Wong

In accordance with an embodiment, described herein is a system and method for providing query acceleration with a computing environment such as, for example, a business intelligence environment, database, data warehouse, or other type of environment that supports data analytics. A middle layer is provided as a long-term table data storage format; and one more acceleration formats, or acceleration tables, can be periodically regenerated from the middle layer, wherein a determination can be made as to whether an accelerated table exists for a dataset table, and if so, then the accelerated table is used to process the query.

System and method for query acceleration for use with data analytics environments

Described herein is a system and method for providing an integrated function editor, for use with a data analytics environment. The function editor can be utilized to create and register functions available within a cloud infrastructure or cloud environment, for use within a data analytics environment. Such functions available for use within the cloud infrastructure or cloud environment can be displayed for the user, and used, for example, in data analytics workbooks, to create an interface or API that allows connection of the data analytics environment to a cloud infrastructure database.

System and method for integrated function editor for use in data analytics environment

In accordance with an embodiment, described herein is a query execution debugger, for use with a computing environment such as, for example, a business intelligence environment, database, data warehouse, or other type of environment that supports data analytics. A query engine, for example a business intelligence server instance, serves analytics queries or requests from clients, directed to data stored at a database, in accordance with a query execution plan, wherein a logical query can include query language statements received from the clients; while a physical query includes database-specific statements that the query engine sends to the database to retrieve data when processing the logical query. The system can create a query execution debugger file that includes a record metadata portion or section, and a data portion or section, and which can be used to review, simulate, or debug the processing of queries against the database.

Query execution debugger for use with business intelligence and data analytics environments

Systems and methods are described for performing a SQL bypass in a business intelligence (BI) server environment. The BI server initially receives a SQL query and constructs an extensible markup language (XML) representation of the SQL query. The XML representation is sent to an application server that hosts an application developer framework (ADF). The ADF receives the XML representation of the SQL query and constructs a composite view object at runtime, to access the appropriate data. It then generates a database-specific query based on the composite view object and returns it to the BI server. The BI server replans the database-specific query and sends it to a database storing the data.

System and method for providing a composite view object and SQL bypass in a business intelligence server

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Redwood City, CA, United States of America

Kenneth Eng