Distributed Machine Language Query Management for Low-Latency Database Analysis

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Solution Overview

Problem

Existing database analytic tools are inefficient, costly, and require substantial configuration and training, making it difficult for businesses to access and analyze large volumes of data effectively.

Innovation Solution

A low-latency database analysis system with distributed machine-language query management, which includes a distributed in-memory database, an in-memory database instance, and a machine-language-query management instance, automatically generates and caches machine language queries to improve data access efficiency and responsiveness.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If traditional database analytic tools are used, then data can be accessed and analyzed, but the system becomes inefficient, costly, and requires substantial configuration and training

Engineering Contradiction:

Improvedata access efficiencyVSAvoidconfiguration and training requirements

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The system enables self-service through automatic query translation from natural language to machine language queries. The query translation module automatically converts user queries without requiring manual configuration or specialized training, allowing users to access data efficiently through intuitive interfaces rather than complex system setup

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces manual mechanical query construction with automated machine translation. Instead of requiring users to manually configure queries using complex database languages, the system substitutes this mechanical process with automated natural language to machine language translation, eliminating the need for substantial configuration and training

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Speed

If machine language queries are generated and cached in memory, then query execution speed increases, but memory resources are consumed

Engineering Contradiction:

Improvequery execution speedVSAvoidmemory resource utilization

Core Design Contradiction:

SpeedVSUse of energy by moving object

Solution Approach 1:

The system performs preliminary action by pre-compiling and caching frequently accessed machine language queries in memory before they are actually executed. This allows rapid query retrieval and execution without requiring real-time translation, significantly improving query execution speed for repeated operations

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent implements copying by creating cached versions of machine language queries in memory. Instead of repeatedly translating and executing the same queries, the system copies the compiled query plans into memory for rapid retrieval, reducing the computational overhead of repeated query execution while managing memory resources through selective caching

Inventive Principle:

Principle #26Copying

3Loss of time

If distributed machine language query management is implemented, then system responsiveness improves, but system complexity increases

Engineering Contradiction:

Improvesystem responsivenessVSAvoiddistributed system architecture

Core Design Contradiction:

Loss of timeVSDevice complexity

Solution Approach 1:

The system applies segmentation by dividing the query management functionality into separate distributed modules. The query translation module, execution module, and caching mechanisms are segmented across different system components, allowing independent optimization and improved responsiveness through parallel processing while managing complexity through modular architecture

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces an intermediary query translation module that mediates between natural language queries and machine language execution. This intermediary layer translates and optimizes queries before they reach the execution engine, enabling faster response times by pre-processing and optimizing queries in a centralized manner while maintaining distributed system flexibility

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS11429607B2Machine language query management for low-latency database analysis system

Publication Date: 2022.08.30 THOUGHTSPOT INC

AI summary

Data-query execution with distributed machine-language query management in a low-latency database analysis system may include obtaining, at a distributed in-memory database, a data-query expressing a request for data in a defined structured query language associated with the distributed in-memory database, automatically generating a high-level language query representing at least a portion of the data-query, obtaining a machine language query corresponding to the high-level language query, executing the machine language query to obtain results data, and outputting the results data. Obtaining the machine language query may include determining whether the machine language query is cached, and in response to a determination that the machine language query is unavailable, sending a request for the machine language query to a distributed machine-language-query management instance.