Shared Data Store Registration for Custom Data Conversion

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Solution Overview

Problem

Existing data stores face inefficiencies due to the limitations of generic, well-known compression algorithms that fail to meet the specific compression needs of diverse data types and structures, requiring complex modifications and inflexibility in accommodating changing data types and compression requirements.

Innovation Solution

A system and method for users to easily define, register, and selectively apply custom data conversion algorithms, such as compression and decompression, by composing functions as objects in a database, allowing for adaptable and flexible data handling through a shared library and catalog system.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Quantity of substance

If generic compression algorithms are used, then storage space is conserved and access time is reduced, but compression efficiency and data quality deteriorate for specific data types

Engineering Contradiction:

Improvestorage spaceVSAvoidcompression efficiency

Core Design Contradiction:

Quantity of substanceVSManufacturing precision

Solution Approach 1:

The system allows dynamic selection of compression algorithms based on data type parameters. Different compression schemes (e.g., run-length encoding for repetitive data, dictionary-based for textual data, lossless for numerical data) are applied by changing the algorithm parameters according to the specific data characteristics, thereby optimizing compression efficiency for each data type while maintaining storage conservation.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The data store is segmented into different data types, and appropriate compression algorithms are applied to each segment. This segmentation allows specialized compression techniques to be applied to specific data types (textual, numerical, repetitive patterns) rather than using a single generic algorithm for all data, improving overall compression efficiency while maintaining storage space conservation.

Inventive Principle:

Principle #1Segmentation

2Adaptability or versatility

If custom compression algorithms are incorporated into the database, then compression needs are met, but system complexity and modification difficulty increase

Engineering Contradiction:

Improvecompression adaptabilityVSAvoidsystem complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

An intermediary compression management layer is introduced between the user and the database storage system. This layer handles the complexity of algorithm selection, parameter configuration, and algorithm registration, allowing users to specify compression needs without directly modifying database code. The intermediary manages multiple compression algorithms and their configurations, reducing system complexity while maintaining high adaptability.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The database system is enhanced with a universal compression framework that can accommodate multiple compression algorithms through a standardized interface. This multi-functional approach allows the same database infrastructure to support various compression schemes (generic and custom) without requiring separate systems or complex modifications, thereby reducing overall system complexity while maintaining versatility.

Inventive Principle:

Principle #6Universality (Multi-functionality)

3Adaptability or versatility

If compression algorithms are modified to accommodate new data types, then compression requirements are met, but flexibility and ease of modification decrease

Engineering Contradiction:

Improvedata type accommodationVSAvoidalgorithm modification ease

Core Design Contradiction:

Adaptability or versatilityVSEase of operation

Solution Approach 1:

The compression algorithm selection and configuration is made dynamic rather than static. The system can dynamically register, select, and switch between different compression algorithms based on data type requirements. New compression algorithms can be registered and applied to new data types without modifying existing database code, allowing easy adaptation to changing requirements while maintaining operational simplicity through automated algorithm selection.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system provides self-service capabilities where compression algorithms automatically select and apply themselves based on data type characteristics. When new data types are added, the system can automatically identify appropriate compression schemes from the registered algorithms and apply them without requiring manual intervention or code modification. This self-service approach maintains ease of operation while enhancing adaptability to new data types.

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS9330150B1Registration and utilization of arbitrary data conversion schemes in a shared data store

Publication Date: 2016.05.03 EMC IP HLDG CO LLC

AI summary

Data conversion algorithms such as compression and decompression algorithms or encryption and decryption algorithms are registered in a shared data store for selective use on data by creating implementations of a plurality of functions that as a group characterize the algorithms, converting the implementations to executable code and storing the code in a shared library, and creating and registering data store objects in a data store catalog with a common identifier that enables the algorithm to be selectively called and applied to data.