Federated Query Syntax for Multi-Table Data Interoperability
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Solution Overview
Problem
Conventional data storage and querying technologies face challenges in handling large, complex datasets due to inherent barriers and incompatibilities among disparate datasets, leading to inefficient data interoperability and cumbersome query formation processes.
Innovation Solution
A collaborative dataset consolidation system that uses a dataset ingestion controller to transform tabular data into graph data arrangements, enabling enhanced query language syntax for multi-table queries through a dataset query engine, which optimizes query formation by allowing simultaneous access to multiple datasets without the need for extensive UNION clauses or data preprocessing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional data storage and querying technologies are used to handle large, complex datasets, then data interoperability is achieved through standard methods, but the process becomes inefficient and cumbersome due to inherent barriers and incompatibilities among disparate datasets
Solution Approach 1:
The patent introduces a federated query system that acts as an intermediary layer between disparate data sources and the user. This system translates high-level federated queries into source-specific queries, eliminating the need for users to manually navigate data silos and incompatibilities. The intermediary handles the complexity of data interoperability transparently, improving efficiency without exposing the underlying complexity to end users.
Solution Approach 2:
The patent segments the query processing system into distinct components: a federated query parser, a query translation engine, and source-specific query executors. This segmentation allows each component to specialize in handling specific aspects of data interoperability, making the overall system more efficient at managing complex, disparate datasets while presenting a simplified interface to users.
2Ease of operation
If extensive UNION clauses or data preprocessing is used to access multiple datasets, then complete data access is achieved, but query formation becomes cumbersome and computational resource usage increases
Solution Approach 1:
The patent performs preliminary actions by pre-compiling and caching query execution plans for federated queries. The system analyzes the federated query structure in advance, determines the optimal execution strategy, and caches the translation mappings between federated query syntax and source-specific query syntax. This preliminary processing reduces the computational resources needed during actual query execution and simplifies the user experience by providing consistent, optimized performance.
Solution Approach 2:
The patent creates and uses query templates that can be reused across multiple data access operations. Once a federated query structure is defined and optimized, it can be copied and applied to access different datasets with the same structural patterns, significantly reducing the effort required for query formation and minimizing redundant computational work.
3Productivity
If conventional query languages require identification of each data file and separate querying before joining results, then precise data control is achieved, but the query process becomes multi-step and inefficient
Solution Approach 1:
The patent merges multiple source-specific query operations into a single federated query statement. The federated query syntax allows users to specify multiple data sources and their relationships in one unified query, which the system then translates and executes as coordinated operations. This merging eliminates the need for users to manually construct multi-step processes involving separate queries and manual result joining, significantly improving productivity and reducing the time lost to query formation.
Solution Approach 2:
The patent creates a universal federated query language that can access multiple different data sources and formats through a single standardized syntax. This universal interface performs multiple functions: it identifies data files, formulates appropriate queries for each source, coordinates execution, and automatically joins results - all through one query statement rather than requiring separate operations for each function.
Data Source
AI summary
Various embodiments relate generally to data science and data analysis, computer software and systems, and wired and wireless network communications to interface among repositories of disparate datasets and computing machine-based entities configured to access datasets, and, more specifically, to a computing and data storage platform configured to provide one or more computerized tools that facilitate development and management of data projects, including implementation of extended computerized query language syntax to analyze, for example, multiple tabular data arrangements in data-driven collaborative projects. For example, a method may include generating data to present a query editor in a data project interface, receiving data representing a first query command to select one or more subsets of data, identifying in the data representing a second query command a subset of datasets from which to extract the data, and applying a query based on a first query command and a second query command.