Bea Systems, Inc.

Salesforce Com, Inc.

Oracle International Corporation

Salesforce, Inc.

Seth John White

Rob Woollen

Dean Bernard Jacobs

Thorick Chow

Matthew Shinn

Adam Messinger

Robert Woollen

Michael Kerby Chen

Alexandre De Castro Alves

Guillaume Le Stum

Benjamin G Shaw

Cédric Beust

Andrew Piper

Rob Woolen

Runtime optimization of grouping operators is described. A system estimates a resource cost for each of multiple grouping operators based on values identified during query runtime, in response to receiving a query request associated with a data stream. The system selects a grouping operator during query runtime, based on a corresponding resource cost, from the multiple grouping operators. The selected grouping operator enables grouping the data stream based on the query request, and outputting a response based on the grouped data stream.

Runtime optimization of grouping operators

Techniques for optimizing result presentation for a database query. A database query is received. The database query is performed with a clause indicating one or more offset values to be used in displaying results from the database query. The one or more offset values indicate a subset within the results from the database query to be presented. An order is imposed on the results from the database query. The subset is presented as determined by the one or more offset values.

Optimizing result presentation of a database operation

Embodiments regard maintaining data consistency between transactional and non-transactional data stores. Embodiments may include receiving a request to archive a set of data stored in a first data store, recording a high water mark in the first data store for the set of data, and archiving the set of data. Archiving the set of data may include copying the set of data into a second data store and inserting a high water mark for the set of data in the first data store and the second data store. Embodiments may further include updating a reference high water mark upon successful completion of operations for the archiving of the data, the reference high water mark representing completion of a last successful archive operation, and, upon receiving a query for requested data contained in the first or second data store, determining whether to allow viewing of the requested data based at least in part on a current value of the reference high water mark.

Maintaining data consistency between transactional and non-transactional data stores

A system selects multiple operators in a query graph by determining whether a corresponding value satisfies a threshold for each operator. The system sorts each selected operator in an ascending order based on a corresponding maximum thread capacity and determines an average number of threads of control based on available threads and the selected operators. The system allocates an initial number of threads to an initial selected operator in the ascending order, the initial number based on a minimum of the average number of threads and corresponding maximum thread capacity. The system determines a revised average number of threads based on remaining number of available threads and remaining number of the selected operators and allocates a next number of threads to a next selected operator in the ascending order, the next number based on a minimum of the revised average number of threads and corresponding maximum thread capacity.

Maximizing operator parallelism

Techniques for providing polymorphic query requests. A request is received that has at least a database query. The database query comprises at least an expression using a polymorphic relationship. The request is processed utilizing the polymorphic relationship. A user-readable result is provided for the query where the result is defined by at least the polymorphic relationship.

Systems, methods and techniques for polymorphic queries

In accordance with embodiments, there are provided mechanisms and methods for facilitating dynamically controlled fetching of data at client computing devices in an on-demand services environment in a multi-tenant environment according to one embodiment. In one embodiment and by way of example, a method includes receiving, at a server computing device, a request from a client computing device. The request includes a query for receiving data from a database coupled to the server computing device in an on-demand database system. The method may further include matching the request against a predetermine threshold value, and where the threshold value includes a first predetermined threshold range based on a first column range or a first row range and a second predetermined threshold range based on a second column range or a second row range. The method may further include generating multiple responses to the request based on one or more formulae and the predetermined threshold value if the request fails to satisfy the predetermined threshold value.

Facilitating dynamically controlled fetching of data at client computing devices in an on-demand services environment

High performance data streaming is provided. An intermediate iterator receives a request to process streaming data in a parent request buffer from a parent iterator. The intermediate iterator sends a request to provide a batch of the streaming data in a request child buffer to a child iterator. The intermediate iterator receives the batch of the streaming data in a child response buffer from the child iterator. The intermediate iterator processes the batch of the streaming data. The intermediate iterator sends the processed batch of the streaming data in a response parent buffer to the parent iterator.

High-performance data streaming

An event server adapted to receive events from an input stream and produce an output event stream. The event server uses a processor using code in an event processing language to process the events. The event server obtaining input events from and/or producing output events to a cache.

Growing community of inventors

San Francisco, CA, United States of America

Seth John White