Amazon Technologies, Inc.

Ullas Sankhla

Marvin Michael Theimer

Julien Jacques Ellie

Colin Watson

Swapandeep Singh

Brian Dahmen

Paul Anderson

Arjun Raman

Kerry Hart

Yunhan Chen

Yuxin Xie

Fengjia Xiong

Suchi Nandini

Shu Liu

Zachary Mohamed Shalla

Gaurav D Ghare

Léon Thrane

Gautam Shanbhag

Vaibhav Sharma

Shen Pan

Nagesh V Honnalli

Surendra Moolchand Bashani

Sushanth Tiruvaipati

Methods, systems, and computer-readable media for orchestration of computations using a remote repository are disclosed. A representation of one or more inputs to a computation is stored in a repository. The computation is assigned to one or more hosts of a plurality of hosts. A representation of program code executable to perform the computation is stored in the repository. A local copy of the one or more inputs is stored on the one or more hosts. The computation is initiated on the one or more hosts using the program code and the local copy of the one or more inputs. The computation is initiated for a plurality of keys. The computation succeeds for one or more keys after the computation has failed for one or more other keys. A representation of one or more outputs of the computation is stored in the repository.

Orchestration of computations using a remote repository

Methods, systems, and computer-readable media for a client-side filesystem for a remote repository are disclosed. One or more files of a repository are sent from a storage service to a client device. The file(s) are obtained by the client using a credential sent by a repository manager. Local copies of the file(s) are accessible via a local filesystem mounted at the client device. One or more new files associated with the repository are generated at the client device. Using the credential, the one or more new files are obtained at the storage service from the client device. The one or more new files are added to the repository.

Client-side filesystem for a remote repository

Methods, systems, and computer-readable media for parameter variations for computations using a remote repository are disclosed. A first computation is assigned to a first set of one or more hosts. The first computation is associated with first parameters including one or more inputs and program code. A second computation is assigned to a second set of one or more hosts and is associated with a second set of parameters. Execution of the first computation is initiated using the first set of hosts and the first set of parameters. Local copies of the input(s) and program code are obtained from a storage service using a TO credential supplied by a repository manager. Execution of the second computation is initiated using the second set of hosts and the second set of parameters as obtained using a credential supplied by the repository manager.

Parameter variations for computations using a remote repository

To achieve long running batch updates, a transaction aggregator layer and one or more data aggregation queues, such as a command queue, are placed between one or more clients and a database. Writes go to the database aggregator layer and are enqueued in the appropriate data aggregation queue, which may be allocated by transaction. Committing the transaction drains the queue and writes the contents of the queue in one transaction-like update to the database. By using the transaction logic in the transaction aggregator layer, transaction-like behavior may be achieved that allows both updates and transactions to scale with less impact on database servers.

Concurrency control in database transactions

Embodiments of systems and methods are described for reducing latency during invoice generation involving credit distribution. In some implementations, references to invoice line items are sorted by supplemental charge rate and credits are applied to the invoice line items in decreasing supplemental charge rate order. An invoice is generated that includes the invoice line items and associated credits. The process of generating applying the credits is optimized to minimize latency and to provide the greatest financial benefit to the user.

Credit optimization to minimize latency

Growing community of inventors

Seattle, WA, United States of America

Ullas Sankhla