Oracle International Corporation

Siebel Systems, Inc.

John Leo

William H Waddington

Cetin Ozbutun

Maria Elisabeth Kaval

Yoram Tal

Shivani Gupta

Jasjeet Singh Thind

In one implementation, a method includes obtaining a data entry from a user of a device, and obtaining a first time entry related to a first time zone. The first time entry and the first time zone are selected by a user of the device and the device converts the first time entry to a second time in a second time zone associated with a user of the device. The device then stores the data entry with the second time in the device. The method and device can thus be used to schedule a meeting in a selected local time in selected time zone, which is then converted to a local time in a time zone associated with the device.

Method and device for processing a time-related data entry

Techniques are provided for executing distinct aggregation operations in a manner that is more scalable and efficient than prior techniques. A three-stage technique is provided to parallelize aggregation operations that involve both grouping and multiple distinct-key columns. Such queries are handled by splitting rows into as many pieces as there are distinct aggregates in the query, and processing the row pieces. During the first-stage, a set of slave processes scans the rows of the base tables and performs partial duplicate elimination. During the second-stage, a set of slave processes completes the duplicate elimination and performs partial set function aggregation. During the third-stage, a third set of slave processes completes the set aggregation to produce the results of the distinct aggregation operation. In addition, two-stage parallelization techniques are provided for parallelizing single-distinct aggregations, and for parallelizing distinct aggregation operations that involve multiple distinct-key columns, but do not require grouping.

Parallel distinct aggregates

Growing community of inventors

Palo Alto, CA, United States of America

John Leo