Salesforce Com, Inc.

Salesforce, Inc.

Scott Musser

Peter S Wisnovsky

Carl Watterson Montgomery

Zhijie Guan

Zuye Zheng

Raghav Ravichandran

Aditya Kochhar

Andrew Ouyang

Meghana Ashok

Asra Yousuf

Methods, systems, and devices for generating a query using training observations are described. According to the techniques described herein, a device (e.g., an application server) may receive a set of queries including a set of fields in a tenant-specific dataset associated with the query. The device may generate a set of training observations for the queries based on the set of fields. The device then trains a first machine learning model to determine grouping hierarchies and a second machine learning model to determine aggregation predictions. The device then builds a combined machine learning model based on the determined grouping hierarchies and the aggregation predictions. According to techniques described herein, the device uses the determined grouping hierarchies and the aggregation predictions to rank a set of suggested queries determined in response to an input query and selects a suggested query for display based on the ranking.

Generating a query using training observations

In accordance with embodiments, there are provided mechanisms and methods for facilitating criteria-based cost-efficient routing and deployment of metadata packages in an on-demand services environment according to one embodiment. In one embodiment and by way of example, a method comprises analyzing, by a metadata costing server computing device, characteristics of a metadata package awaiting deployment, where analyzing includes matching the characteristics with predefined criteria associated with deployment of metadata packages. The method may further include routing, by the metadata server, the metadata package for real-time deployment if the characteristics satisfy the criteria, where the real-time deployment allows for bypassing of message queues associated with standard deployment.

Criteria-based cost-efficient routing and deployment of metadata packages in an on-demand environment

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Longmont, CO, United States of America

Scott Musser