Constituent Data Indexing With Contraindicated Sampling

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Solution Overview

Problem

Existing database analytic tools are inefficient, costly, and require substantial configuration and training, limiting accessibility and utility of large volumes of data stored in complex data storage systems.

Innovation Solution

A data access and analysis system that indexes constituent data by obtaining and updating a constituent-data index, determining contraindications for sampling and updating, and traversing the index to automatically generate data queries, reducing resource utilization and improving accessibility.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If traditional database analytic tools are used to analyze large volumes of data, then data analysis capability is provided, but resource utilization increases and accessibility decreases

Engineering Contradiction:

Improvedata analysis capabilityVSAvoidresource utilization

Core Design Contradiction:

ProductivityVSUse of energy by moving object

Solution Approach 1:

The system performs preliminary actions by pre-computing and storing index structures (e.g., column-value indexes, row-context indexes) that capture statistical properties, data distributions, and relationships before actual analysis queries are executed. This allows the system to quickly resolve user requests without performing full data scans, thereby reducing resource utilization during analysis operations.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system introduces an intermediary layer consisting of index structures and resolution components that mediate between user data requests and the underlying data source. This intermediary layer translates high-level user requests into optimized data queries by traversing pre-built indexes, reducing the computational burden on the data source and improving overall system efficiency.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Productivity

If traditional database analytic tools are used, then data analysis is performed, but configuration and training requirements increase complexity

Engineering Contradiction:

Improvedata analysis capabilityVSAvoidconfiguration and training requirements

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The system implements self-service by automatically resolving user requests through traversal of pre-built indexes without requiring manual configuration or expert intervention. The resolution component autonomously interprets user requests, navigates the index structures, and generates appropriate data queries, making the system accessible to users without specialized training in database analytics.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The index structures serve multiple functions simultaneously: they enable fast data retrieval, provide statistical summaries, support various query types, and facilitate automatic request resolution. This multi-functionality reduces the need for separate configuration mechanisms and simplifies the user interface, as a single index-based infrastructure handles diverse analytical needs.

Inventive Principle:

Principle #6Universality (Multi-functionality)

3Ease of operation

If complete data indexing is performed for all columns, then data accessibility is improved, but resource utilization increases

Engineering Contradiction:

Improvedata accessibilityVSAvoidresource utilization

Core Design Contradiction:

Ease of operationVSUse of energy by moving object

Solution Approach 1:

The system applies local quality by creating different types of indexes for different columns based on their specific characteristics and access patterns. High-cardinality columns may receive different treatment than low-cardinality columns, and the system selectively builds indexes only for columns that will benefit from them, avoiding the resource overhead of indexing every column uniformly.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The system employs partial indexing by creating index structures for only the most frequently accessed or most beneficial columns rather than indexing the entire dataset. The resolution component intelligently determines which index to traverse based on the specific request, achieving good accessibility for common queries while minimizing the resources required for index maintenance.

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS12450216B2Indexing constituent data

Publication Date: 2025.10.21 THOUGHTSPOT INC

AI summary

Updating a constituent-data index includes determining whether sampling is currently contraindicated for the column, in response to determining that sampling is currently contraindicated for the column, omitting sampling the column, in response to determining that sampling is currently other than contraindicated for the column, sampling the column, determining whether updating the constituent-data index is currently contraindicated for the column, in response to determining that updating the constituent-data index is currently contraindicated for the column, omitting updating the constituent-data index with respect to the column, and in response to determining that updating is currently other than contraindicated for the column, updating the constituent-data index with respect to the column.