Amazon Technologies, Inc.

Victoria Wong

Desmond Zhou

Ryan Schwartz

Douglas Baldwin Dance

Joerg Perieno Germann

Jie Gao

Yuan Bian

Nicholas Leong

Abhishek Sahay

Boyang Tom Jin

Kyle Malong

Yu Yi

Jean-Christophe Libbrecht

Pascal Schoenhardt

Galen Gong

Bal Jayme Martin Nodora

Rong Wang

Dale Thoma

Hyun Jung Cho

Anand Rathi

Yiu Pong Lam

Methods, systems, and computer-readable media for batch processing with random access for transaction history are disclosed. A batch processing system receives a batch comprising records of events, including a first record of a first event and a second record of a second event. The system assigns the first and second records to a group based (at least in part) on determining that the events are related. The system determines that the group is related to a match set comprising one or more prior events. The system updates one or more values in the match set based (at least in part) on the first and second records. The system stores the updated match set and one or more additional match sets using a storage object. The system retrieves the match set and not the one or more additional match sets from the storage object using an index.

Batch processing with random access for transaction history

Deferred revenue calculations can be necessary in an accrual-basis accounting model where a subscription or other type of sale is conducted that requires deferred revenue recognition. A snapshot state corresponding to the current state of a particular deferral can be generated. Out of order deferred events can also occur. The current state of the deferral can also be published in a downstream system.

Scalable, service-based architecture for efficiently processing accrual-basis, out-of-order events

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Richmond, CA, United States of America

Victoria Wong