公开(公告)号：US12225092B2

公开(公告)日：2025-02-11

申请号：US18310461

申请日：2023-05-01

Applicant: Amazon Technologies, Inc.

Inventor： George Steven McPherson ,  Mehul A. Shah ,  Supratik Chakraborty ,  Prajakta Datta Damle ,  Gopinath Duddi ,  Anurag Windlass Gupta

IPC: H04L67/00 ,  G06F9/4401 ,  G06F9/50 ,  H04L67/01 ,  H04L67/10 ,  H04L69/24

Abstract: Code may be dynamically routed to computing resources for execution. Code may be received for execution on behalf of a client. Execution criteria for the code may be determined and computing resources that satisfy the execution criteria may be identified. The identified computing resources may then be procured for executing the code and then the code may be routed to the procured computing resources for execution. Permissions or authorization to execute the code may be shared to ensure that computing resources executing the code have the same permissions or authorization when executing the code.

公开(公告)号：US11941017B2

公开(公告)日：2024-03-26

申请号：US18048645

申请日：2022-10-21

Applicant: Amazon Technologies, Inc.

Inventor： George Steven McPherson ,  Mehul A. Shah ,  Prajakta Datta Damle ,  Gopinath Duddi ,  Anurag Windlass Gupta

IPC: G06F17/00 ,  G06F9/54 ,  G06F16/25

CPC classification number: G06F16/254 ,  G06F9/542

Abstract: Extract, Transform, Load (ETL) processing may be initiated by detected events. A trigger event may be associated with an ETL process apply one or more transformations to a source data object. The trigger event may be detected for the ETL process and evaluated with respect to one or more execution conditions for the ETL process. If the execution conditions for the ETL process are satisfied, then the ETL process may be executed. At least some of the source data object may be obtained, the one or more transformations of the ETL process may be applied, and one or more transformed data objects may be stored.

公开(公告)号：US11797558B2

公开(公告)日：2023-10-24

申请号：US17491985

申请日：2021-10-01

Applicant: Amazon Technologies, Inc.

Inventor： Mehul A. Shah ,  George Steven McPherson ,  Prajakta Datta Damle ,  Gopinath Duddi ,  Anurag Windlass Gupta ,  Benjamin Albert Sowell ,  Bohou Li

IPC: G06F17/00 ,  G06F16/25 ,  G06F16/28

CPC classification number: G06F16/254 ,  G06F16/282

Abstract: Data transformation workflows may be generated to transform data objects. A source data schema for a data object and a target data format or target data schema for a data object may be identified. A comparison of the source data schema and the target data format or schema may be made to determine what transformations can be performed to transform the data object into the target data format or schema. Code to execute the transformation operations may then be generated. The code may be stored for subsequent modification or execution.

公开(公告)号：US11714573B1

公开(公告)日：2023-08-01

申请号：US17216373

申请日：2021-03-29

Applicant: Amazon Technologies, Inc.

Inventor： Shashank Bhardwaj ,  Roman Gavrilov ,  Brian Scott Ross ,  Mehul A. Shah ,  Benjamin Sowell ,  Anthony A. Virtuoso ,  Linan Zheng

IPC: G06F3/06

CPC classification number: G06F3/0659 ,  G06F3/067 ,  G06F3/0613 ,  G06F3/0614 ,  G06F3/0653

Abstract: Techniques for storage optimization in a distributed object store are described. A storage optimization service of a provider network monitors changes to data objects in a distributed object store that are part of a data lake and are referenced by a table index. The storage optimization service determines whether particular storage optimizations involving the data objects would be beneficial, prioritizes the ordering of these optimizations with a focus on performing impactful optimizations first, while intelligently scheduling the optimizations to avoid overutilization of available resources.

公开(公告)号：US11599514B1

公开(公告)日：2023-03-07

申请号：US17216326

申请日：2021-03-29

Applicant: Amazon Technologies, Inc.

Inventor： Vinay Agrawal ,  Bohou Li ,  Vikas Malik ,  Tushar Poddar ,  Vijayan Prabhakaran ,  Mukesh Punhani ,  Mehul A. Shah ,  Benjamin Sowell ,  Douglas Brian Terry

IPC: G06F16/00 ,  G06F16/21 ,  G06F16/23 ,  G06F16/2458 ,  G06F16/22 ,  G06F16/27 ,  G06F16/248 ,  G06F16/2457

Abstract: Techniques for implementing systems using transactional version sets are described. Transactional version sets or t-sets include a collection of elements, each having a collection of metadata. A t-set is transactional in that a sequence of updates to one or more t-sets are made within an atomic transaction. A t-set is versioned since each committed transaction that updates it produces a new timestamped version that can be accessed via time-travel queries.

公开(公告)号：US11481408B2

公开(公告)日：2022-10-25

申请号：US15385787

申请日：2016-12-20

Applicant: Amazon Technologies, Inc.

Inventor： George Steven McPherson ,  Mehul A. Shah ,  Prajakta Datta Damle ,  Gopinath Duddi ,  Anurag Windlass Gupta

IPC: G06F17/00 ,  G06F16/25 ,  G06F9/54

Abstract: Extract, Transform, Load (ETL) processing may be initiated by detected events. A trigger event may be associated with an ETL process apply one or more transformations to a source data object. The trigger event may be detected for the ETL process and evaluated with respect to one or more execution conditions for the ETL process. If the execution conditions for the ETL process are satisfied, then the ETL process may be executed. At least some of the source data object may be obtained, the one or more transformations of the ETL process may be applied, and one or more transformed data objects may be stored.

公开(公告)号：US20220261413A1

公开(公告)日：2022-08-18

申请号：US17687492

申请日：2022-03-04

Applicant: Amazon Technologies, Inc.

Inventor： Timothy Jones ,  Andrew Borthwick ,  Sergei Dobroshinsky ,  Shehzad Qureshi ,  Stephen Michael Ash ,  Pedrito Uriah Maynard-Zhang ,  Chethan Kommaranahalli Rudramuni ,  Abhishek Sharma ,  Juliana Saussy ,  Adam Lawrence Joseph Heinermann ,  Alaykumar Navinchandra Desai ,  Mehul A. Shah ,  Mehul Y. Shah ,  Anurag Windlass Gupta ,  Prajakta Datta Damle

IPC: G06F16/25 ,  G06F9/54 ,  G06N20/00

Abstract: Specified performance attributes may be used to configure machine learning transformations for ETL jobs. Performance attributes for a machine learning pipeline that applies a model to as part of a transformation for an ETL job may be used to configure a parameter in a stage of the machine learning pipeline. The configured stage may then be used when training the model. The trained machine learning pipeline may then be applied as part of a transformation operation included in an ETL job performed by the ETL system.

公开(公告)号：US10983967B2

公开(公告)日：2021-04-20

申请号：US15478177

申请日：2017-04-03

Applicant: Amazon Technologies, Inc.

Inventor： Dimitris Tsirogiannis ,  Nathan A. Binkert ,  Stavros Harizopoulos ,  Mehul A. Shah ,  Benjamin A. Sowell ,  Bryan D. Kaplan ,  Kevin R. Meyer

IPC: G06F16/21 ,  G06F16/22 ,  G06F16/84 ,  G06F16/23 ,  G06F16/25

Abstract: A data transformation system includes a schema inference module and an export module. The schema inference module is configured to dynamically create a cumulative schema for objects retrieved from a first data source. Each of the retrieved objects includes (i) data and (ii) metadata describing the data. Dynamically creating the cumulative schema includes, for each object of the retrieved objects, (i) inferring a schema from the object and (ii) selectively updating the cumulative schema to describe the object according to the inferred schema. The export module is configured to output the data of the retrieved objects to a data destination system according to the cumulative schema.

公开(公告)号：US20170206256A1

公开(公告)日：2017-07-20

申请号：US15478177

申请日：2017-04-03

Applicant: Amazon Technologies, Inc.

Inventor： Dimitris Tsirogiannis ,  Nathan A. Binkert ,  Stavros Harizopoulos ,  Mehul A. Shah ,  Benjamin A. Sowell ,  Bryan D. Kaplan ,  Kevin R. Meyer

IPC: G06F17/30

CPC classification number: G06F16/211 ,  G06F16/22 ,  G06F16/235 ,  G06F16/254 ,  G06F16/86

Abstract: A data transformation system includes a schema inference module and an export module. The schema inference module is configured to dynamically create a cumulative schema for objects retrieved from a first data source. Each of the retrieved objects includes (i) data and (ii) metadata describing the data. Dynamically creating the cumulative schema includes, for each object of the retrieved objects, (i) inferring a schema from the object and (ii) selectively updating the cumulative schema to describe the object according to the inferred schema. The export module is configured to output the data of the retrieved objects to a data destination system according to the cumulative schema.