Query Rewriting for Nested Data in Distributed Systems
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing data management and storage solutions often lead to fragmented data storage across different locations and formats, making it difficult to analyze and process distributed data effectively, as they lack the ability to handle nested data operations efficiently.
Innovation Solution
Implementing a format-independent data processing service that combines nested data operations by utilizing query engines capable of handling nested data, allowing for distributed query processing across various data formats and locations without the need for data reformatting or migration, through techniques like query rewriting and subquery processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is stored across different locations and formats to meet current storage needs, then data accessibility and storage flexibility are improved, but the ability to analyze and process distributed data collectively deteriorates
Solution Approach 1:
The patent introduces a query rewriting component as an intermediary between the query engine and distributed data sources. This intermediary translates queries into formats suitable for different data locations and structures, enabling the query engine to process distributed data without direct modifications. The rewriting component mediates between the uniform query interface and the heterogeneous data storage, resolving the contradiction between storage flexibility and processing ease.
Solution Approach 2:
The patent segments the query processing system into distinct components: a query engine, a query rewriting component, and data sources. The query rewriting component is further segmented into sub-components that handle different aspects of query transformation. This segmentation allows each component to specialize in specific tasks, with the rewriting component bridging the gap between flexible data storage and unified query processing.
2Productivity
If query engines are upgraded to support nested data operations, then nested data processing capability is improved, but system complexity and upgrade requirements increase
Solution Approach 1:
The query rewriting component serves as an intermediary that provides nested data processing capability without requiring upgrades to the core query engine. It translates queries involving nested data into forms that the existing query engine can handle, thereby improving nested data processing capability while avoiding system complexity and upgrade requirements.
Solution Approach 2:
The patent implements query rewriting that creates virtual copies or representations of nested data structures in a flattened format. Instead of modifying the query engine to handle nested data directly, the system creates rewritten versions of queries that operate on transformed data representations, achieving enhanced capability without increasing core system complexity.
3Quantity of substance
If data is distributed across different storage systems, then storage capacity and accessibility are improved, but data format compatibility and unified processing deteriorate
Solution Approach 1:
The query rewriting component provides universal functionality that works across multiple data formats and storage systems. It implements a unified query rewriting mechanism that can handle various data formats (JSON, XML, relational, etc.) and storage locations, making the system adaptable to diverse data sources while maintaining consistent processing capabilities.
Solution Approach 2:
The patent dynamically changes query parameters and data representation formats based on the target data source. The query rewriting component transforms queries into appropriate formats for different storage systems and data structures, enabling unified processing across heterogeneous environments without sacrificing storage capacity or format compatibility.
Data Source
AI summary
A query that references nested data may have sub-expressions included in a subquery for nested data to perform the query. A first query engine may rewrite the query to include one or more sub-expressions that reference the nested data into a subquery for the nested data as part of generating a plan to perform the query. A second query engine may then be caused to perform the subquery for the nested data. A result of the query may be inclusive of the performance of the subquery at the second query engine.