Metadata-Based Query Translator for Distributed Systems

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Solution Overview

Problem

Current cloud-based applications face high maintenance costs and performance issues due to the need for multiple code versions and inefficient handling of complex queries, especially when information needs change over time, and existing frameworks like CRUD services struggle with flexibility and optimization.

Innovation Solution

A metadata-based general request translator system that allows for data retrieval using a general request language, translating requests into storage-specific queries and optimizing data structures based on usage patterns, enabling self-optimization and reducing the need for manual code development and maintenance.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If multiple code versions are maintained for backward compatibility, then compatibility with different information needs is improved, but maintenance cost increases

Engineering Contradiction:

Improvebackward compatibilityVSAvoidmaintenance cost

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent implements a universal query translation layer that can handle multiple query types and data formats through a single endpoint. The system uses a metadata-driven approach where a general query language is translated into storage-specific queries, eliminating the need for multiple specialized code versions while maintaining compatibility with different information needs

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The patent introduces an intermediary query translation service that sits between the client and the data store. This mediator translates high-level general queries into storage-specific queries, allowing the system to maintain a single code version while supporting multiple data access patterns and backward compatibility requirements

Inventive Principle:

Principle #24Intermediary (Mediator)

2Ease of manufacture

If CRUD services are used for automatic endpoint generation, then development effort is reduced, but query performance deteriorates

Engineering Contradiction:

Improvedevelopment effortVSAvoidquery performance

Core Design Contradiction:

Ease of manufactureVSProductivity

Solution Approach 1:

The patent uses metadata parameters to dynamically configure query translation behavior. By storing usage patterns and performance metrics as metadata, the system can automatically adjust translation strategies to optimize query performance while maintaining the automated generation benefits of CRUD services

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The system implements self-optimization by automatically analyzing usage patterns and adjusting query translation strategies without manual intervention. The metadata-driven approach allows the system to learn from actual query performance and automatically optimize translation rules, combining automated generation with performance optimization

Inventive Principle:

Principle #25Self-service

3Adaptability or versatility

If generic data stores are used for flexibility, then adaptability to changing information needs is improved, but performance and cost worsen

Engineering Contradiction:

ImproveflexibilityVSAvoidperformance

Core Design Contradiction:

Adaptability or versatilityVSProductivity

Solution Approach 1:

The patent segments the query processing system into distinct layers: a flexible general query language layer for adaptability, and storage-specific query execution layers for performance. The metadata-driven translation layer connects these segments, allowing each layer to optimize for its specific purpose while working together as a unified system

Inventive Principle:

Principle #1Segmentation

4Productivity

If manually configured storage is used for performance, then query performance is improved, but development and deployment cost increases

Engineering Contradiction:

Improvequery performanceVSAvoiddevelopment cost

Core Design Contradiction:

ProductivityVSEase of manufacture

Solution Approach 1:

The system automatically analyzes usage patterns and optimizes query translation strategies without manual configuration. By implementing self-optimization through metadata-driven adaptation, the system achieves performance comparable to manual configuration while eliminating the associated development and maintenance costs

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS11372855B2Metadata-based general request translator for distributed computer systems

Publication Date: 2022.06.28 RISK MANAGEMENT SOLUTIONS INC

AI summary

In an embodiment, a method comprises storing metadata that maps a domain model to data stored in a plurality of data stores, each data store being associated with a particular query language, the domain model describing the data and relationships between the data. The method comprises receiving a request for data stored in a first data store of, the request being in a request query language based on the domain model. The method comprises generating an abstract syntax tree indicating a field selection, an entity path, and a condition based on the request; generating a structure model comprising one or more aggregation levels for one or more entities; and generating annotations comprising query language aliases for portions of the request and correlating the portions of the request with the metadata. The method comprises generating queries in a first query language associated with the first data store based on the annotations; and sending the queries to the first data store.