Amazon Technologies, Inc.

Amit Purohit

Akshat Vig

Aravind Ramarathinam

Amit Gupta

Santosh Chandrachood

Ankit Kamboj

Vinayak Thapliyal

Linchi Zhang

Ramkumar Kamalapuram Sugavanam

Min Zhou

Benjamin Donald Wood

Palak Agrawal

Gayatri Ramesh Deo

Lukasz Misiuda

Anoop Gupta

Tanmoy Dutta

Nicholas Gordon

Brian L Welcker

Ravi Math

Sandor Loren Maurice

Alexey Kuznetsov

Lawrence Douglas Webley

Yuhui Yuan

Jagdeep Singh Sidhu

Ramakrishna Dwivedula

Joseph Robert Idziorek

Sachin Honnudike

Sundaresan Krishnamurthy

Serhii Poliakov

Parijatham Santosh Kumar Vodela

James H Mlodgenski

Christopher John Anderson

Inferences may be obtained to handle access requests at a non-relational database system. An access request may be received at a non-relational database system. The non-relational database system may determine that the access request uses a machine learning model to complete the access request. The non-relational database system may cause an inference to be generated using data items for the access request as input to the machine learning model. The access request may be completed using the generated inference.

Obtaining inferences to perform access requests at a non-relational database system

Queries may be made against a non-relational database without impacting the capacities of the non-relational database by enabling performance of queries to a non-relational database via an external query management, backup management, and a non-relational database backup hosted in an external data storage. The query management and backup management of the non-relational database service may split transactional load to the non-relational database and analytical load, and furthermore allow selection of a desired data freshness for queries including various time ranges, such as seconds, minutes, or days.

Analytic query processing using a backup of a database

Techniques for query execution against relational databases using connection pooling are described. According to some embodiments, a query processing service is disclosed that enables users to execute queries against target relational databases implemented by a relational database service. The service receives query requests originated by a client application at a web service endpoint and identifies a connection to a particular target database. In some examples, the query request is a Hyper Text Transfer Protocol (HTTP) message comprising a query to be executed by a target database instance within the provider network. The service transmits the query for execution at the target database via the connection and obtains a query result based on the execution of the query. The service transforms the query result into a format suitable for the client and transmits a query response to the client.

SQL execution over HTTP for relational databases using connection pooling

In response to receiving a parallel processing job from a customer, a system operated by a computing resource service provider allocates and configures a cluster of computer systems capable of executing the job. In an embodiment, each computer system is configured with a first network stack that allows access to resources of the computing resource service provider and a second network stack that allows access to resources of the customer. In an embodiment, the state of the cluster is monitored by the system via the first network stack. In an embodiment, the system deploys a set of tasks on the cluster for fulfilling the processing job. In an embodiment, the tasks have access to the second network stack so that each task can access resources of the customer.

Cluster management

A system operated by a computing resource service provider maintains a pool of computing resources for use in processing job requests submitted by customers. The system allocates computing resources to the pool in anticipation of future resource needs. In various embodiments, future resource needs can be estimated based on scheduled jobs, or historical job information. In an embodiment, the computing resources are virtual computer systems which may be arranged in a cluster. In response to receiving a parallel processing job from a customer, the system reserves computing resources from the pool for performing the job. In an embodiment, the reserved resources are configured with a network namespace that is able to access to a customer's resources.

Resource management

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Issaquah, WA, United States of America

Amit Purohit