Amazon Technologies, Inc.

David John Edwards, Jr

Sumit Kumar Sultania

Jebaraj Moses

Sangeeth Divakaran

Vineeth Chandran Poovathikkal

Brandon William Porter

Peter Varnum Commons

Llewellyn James Mason

Sanjay Govindrao Kulkarni

Charles Porter Schermerhorn

Tegdeep Kondal

Tyson Christopher Trautmann

Elton Victor Pinto

Vishal Mangesh Shanbhag

Scott James McKee

Nisarg Shah

Donald Arthur Parsons

Karanpal Singh Kalsi

Tony Jay Lee

Systems, methods, and computer-readable media are disclosed for an improved database. The systems, methods, and computer-readable media described herein may enhance the response time of databases and improve user experiences. In an example method described herein, a database monitoring system may receive instructions to perform one or more data monitoring operations comprising counting an occurrence of a first value within at least a portion of items stored in a database. The method may include determining a length of a first window of time and fetching, from a first location of a data store of the database, data indicative of a total count of the occurrence of the first value at a time associated with the beginning of the first window of time. In turn, the monitoring system may store data representing the first count in the first memory.

Methods and systems for a fast access database and fast database monitoring

Systems, methods, and computer-readable media are disclosed for an improved database. The systems, methods, and computer-readable media described herein may enhance the response time of databases and improve user experiences. In an example method described herein, a database monitoring system may receive instructions to perform one or more data monitoring operations comprising counting an occurrence of a first value within at least a portion of items stored in a database. The method may include determining a length of a first window of time and fetching, from a first location of a data store of the database, data indicative of a total count of the occurrence of the first value at a time associated with the beginning of the first window of time. In turn, the monitoring system may store data representing the first count in the first memory. The, monitoring system may determine that the first count of the occurrence of the first value changed during the first window of time and store data representing the second count in the first memory. Once the monitoring system determines that the first window of time expired, the monitoring system may provide, to the database, the data representing the second count from the first memory, wherein the database is configured to initiate a write operation for storing the data representing the second count at the first location of the data store of the database.

Techniques for improving efficiency of data processing associated with data queries are described. For example, a computer system may access a first query result of a first time window that result may have been generated based on first transformed data stored in data partitions associated with the first time window. The computer system may access data corresponding to a time unit that falls outside of the first time window and inside a second time window. The first time window and the second time window may have overlapping time units. The computer system may generate a data partition that corresponds to the time unit and that stores second transformed data. The second transformed data may correspond to a data transformation of the data. The computer system may generate a second query result for the second time window based on the second transformed data and the first query result.

Generating query results based on data partitions

This disclosure is directed to, in part, providing customers with an enhanced shopping experience during a visit to a physical store location. The enhanced shopping experience may include providing the customer with customized delivery of product information. The product information may include demonstrations of product use, samples of products, recommendations of related products or areas of interest to a customer, etc. To provide the customized information, the customer may register to be identified while at the physical store location. The physical store location may include sensors that identify a location of the registered customer. A presentation module may then push relevant content to a device located near the customer, possibly in response to a request from the customer and/or a location of the customer.

Enhanced customer shopping experience in physical store locations

Techniques for providing a messaging plan may be provided. A message that conforms to a channel agnostic format may be received. In an example, a messaging plan that includes a channel for delivering the message may be determined based at least in part on a score determined by a machine learning module utilizing metrics of a user. The message may be provided to the user according to the messaging plan. The messaging plan may be updated for subsequent messages based at least in part on updated metrics of the user received in response to the user interacting with the message.

Customer-level cross-channel message planner

Growing community of inventors

Woodinville, WA, United States of America

David John Edwards, Jr