Storage Service Event-Triggered Data Transformation

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Solution Overview

Problem

Current distributed data storage systems require users to manually retrieve, transform, and re-store data, which is time-consuming and resource-intensive, and often necessitate developing customized solutions for different computing resources, making data transformation logistically complicated and costly.

Innovation Solution

A distributed data storage service that performs event-triggered transformations, allowing users to define transformations which are automatically applied when data is made available outside a storage location, using local hardware resources such as FPGAs and RISC processors to reduce network traffic and eliminate the need for user interaction.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Extent of automation

If manual data retrieval, transformation, and re-storage is performed by users, then data transformation can be achieved, but the process becomes time-consuming and resource-intensive

Engineering Contradiction:
Improvedata transformation automationVSAvoidtime for data transformation
Core Design Contradiction:
Extent of automationVSLoss of time

Solution Approach 1:

The storage service automatically performs data transformations without requiring user intervention. The system self-services by detecting when data is accessed and autonomously applying transformations based on stored transformation definitions, eliminating the need for manual data retrieval, transformation, and re-storage operations

Inventive Principle:
Principle #25Self-service

Solution Approach 2:

Transformation definitions are established in advance and stored in the system. When data access events occur, the pre-defined transformations are automatically applied, eliminating the need for users to perform transformation actions at the time of data access

Inventive Principle:
Principle #10Preliminary action

2Adaptability or versatility

If customized transformation solutions are developed for different computing resources, then specific transformation needs can be met, but the process becomes logistically complicated and costly

Engineering Contradiction:
Improvetransformation customizationVSAvoidtransformation system complexity
Core Design Contradiction:
Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The storage service provides a universal transformation framework that can handle multiple transformation types (format conversion, data masking, aggregation, etc.) through a single system. The unified API and event-driven architecture allow the same infrastructure to serve diverse transformation needs without requiring separate customized solutions for each computing resource

Inventive Principle:
Principle #6Universality (Multi-functionality)

Solution Approach 2:

The system achieves customization through configurable transformation parameters and definitions rather than through complex system architecture. Users can define transformations by specifying parameters such as source format, target format, transformation rules, and destination locations, allowing flexible adaptation without increasing system complexity

Inventive Principle:
Principle #35Parameter changes

3Adaptability or versatility

If data is transformed outside the storage service, then transformation flexibility is achieved, but network traffic increases and resource consumption rises

Engineering Contradiction:
Improvetransformation flexibilityVSAvoidnetwork traffic and resource consumption
Core Design Contradiction:
Adaptability or versatilityVSLoss of energy

Solution Approach 1:

The transformation functionality is merged with the storage service infrastructure. Transformation operations are performed within the same system that stores the data, combining storage and processing functions. This eliminates the need to export data externally for transformation and re-import it, thereby reducing network traffic and resource consumption while maintaining transformation flexibility

Inventive Principle:
Principle #5Merging (Combining)

Data Source

PatentUS11860855B1Storage service supporting data transformations
Publication Date: 2024.01.02 AMAZON TECH INC
  • US11860855B1 patent drawing
  • US11860855B1 patent drawing
  • US11860855B1 patent drawing

AI summary

A storage service is configured to receive one or more instructions specifying transformations that are to be applied to data sets stored by the storage service when the data sets are made available outside of particular storage locations within the storage service. In response to triggering events that make the data sets available outside of the particular storage locations, the storage services causes the transformations to be performed on the data sets prior to the data sets being accessible at one or more destination locations outside of the particular storage locations where the data sets are stored. In some embodiments, the transformations are performed on hardware included in the storage service or are performed on external hardware at the direction of the storage service.