Computing Resource Pools for Data Characteristic-Based Allocation

Solution Overview

Problem

Conventional techniques for storing and processing data in database systems do not effectively utilize data characteristics to optimize storage and processing, often treating both indexed and non-indexed data with the same resources despite their differing needs.

Innovation Solution

Designating specific computing groups or pools of resources based on data characteristics, such as indexed or non-indexed data, to optimize storage and processing within the same system, allowing for more efficient handling of data operations.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If conventional techniques treat both indexed and non-indexed data with the same resources, then system simplicity is maintained, but processing efficiency deteriorates

Engineering Contradiction:

Improvedata processing efficiencyVSAvoidresource allocation complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent segments computing resources into distinct pools based on data characteristics. Specifically, it divides resources into those optimized for indexed data and those for non-indexed data, allowing each pool to specialize in handling particular data types efficiently. This segmentation resolves the contradiction by enabling differentiated resource allocation that improves processing efficiency while maintaining manageable complexity through structured organization.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent applies local quality by assigning different resource characteristics to different data types. Computing resources are tailored to match specific data characteristics - for example, certain resource pools are optimized for indexed data operations while others handle non-indexed data. This localized optimization allows each resource pool to excel at its designated function, improving overall processing efficiency without requiring complete system redesign.

Inventive Principle:

Principle #3Local quality

2Speed

If computing resources are designated based on data characteristics, then processing speed is improved, but resource management complexity increases

Engineering Contradiction:

Improvedata processing speedVSAvoidresource management complexity

Core Design Contradiction:

SpeedVSDevice complexity

Solution Approach 1:

The patent segments computing resources into distinct pools based on data characteristics. Specifically, it divides resources into those optimized for indexed data and those for non-indexed data, allowing each pool to specialize in handling particular data types efficiently. This segmentation resolves the contradiction by enabling differentiated resource allocation that improves processing efficiency while maintaining manageable complexity through structured organization.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system implements self-service mechanisms where the resource allocation is automatically managed based on data characteristics. The patent describes designating computing groups or pools of resources based on data characteristics, which enables automatic routing of data operations to appropriate resource pools without manual intervention. This automation reduces the perceived management complexity while maintaining the speed benefits of specialized resource allocation.

Inventive Principle:

Principle #25Self-service

3Productivity

If specialized computing pools are created for different data types, then resource utilization is optimized, but system complexity increases

Engineering Contradiction:

Improveresource utilization efficiencyVSAvoidsystem architecture complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent segments computing resources into distinct pools based on data characteristics. Specifically, it divides resources into those optimized for indexed data and those for non-indexed data, allowing each pool to specialize in handling particular data types efficiently. This segmentation resolves the contradiction by enabling differentiated resource allocation that improves processing efficiency while maintaining manageable complexity through structured organization.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent implements a universal resource pool that can handle both indexed and non-indexed data operations. This multi-functional pool serves as a fallback or complementary resource that can be utilized when specialized pools are not available or when data characteristics do not clearly favor one specialization over another. This universality reduces system complexity by providing a single resource type that can perform multiple functions, while still allowing specialized pools to optimize specific operations.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS10366057B2Designated computing groups or pools of resources for storing and processing data based on its characteristics

Publication Date: 2019.07.30 TERADATA CORP

AI summary

Data or one or more operations can be provided, based on one or more characteristics associated with the data and/or operations, to a designated computing group or pool of computing resources designated for handling the data and/or operations with the particular data characteristic(s). The designated computing group can, for example, be one of multiple computing groups in the same system or device. As such, all of the computing groups can still function together in the same system or device, for example, in parallel. However, each one of the multiple computing groups can, for example, be defined or predefined to include one or more computing resources that are more suitable for storing and/or processing data with one or more data characteristics or handle operations with one or more determined characteristics.