Amazon Technologies, Inc.

Shehzad Qureshi

Timothy Jones

Andrew Borthwick

Anurag Windlass Gupta

Mehul A Shah

Prajakta Datta Damle

Mehul Y Shah

Stephen Michael Ash

Juliana Saussy

Abhishek Sharma

Pedrito Uriah Maynard-Zhang

Sergei Dobroshinsky

Chethan Kommaranahalli Rudramuni

Adam Lawrence Joseph Heinermann

Alaykumar Navinchandra Desai

Tianyi Lu

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.

Using specified performance attributes to configure machine learning pipepline stages for an ETL job

Using specified performance attributes to configure machine learning pipeline stages for an ETL job

Block size reduction iterations are performed on a plurality of blocks of records until a block size criterion is met. An iteration comprises identifying, from a first collection of blocks, using one or more pivot operations, a set of combinations of oversized blocks such that at least one record belongs to all blocks of a combination. A new block comprising records that are members of each block of a first combination of the set is included in a second collection of blocks to be examined in a subsequent iteration. On at least one block created in an iteration, analysis operations are performed.

Intersection-based dynamic blocking

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North Bend, WA, United States of America

Shehzad Qureshi