Query Rewriting for Hierarchical Data Storage Constraints
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Solution Overview
Problem
Relational database systems face inefficiencies when optimizing queries on hierarchically stored data, as existing technologies cannot directly leverage relational optimizations due to the heterogeneous nature of hierarchical storage.
Innovation Solution
Constraints are enforced on how data within a directory is stored in a database, allowing queries to be rewritten to target specific subsets of data, thereby restricting the search space and enabling efficient execution using traditional optimization techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If hierarchical storage mechanisms are used to organize data in files and folders, then data organization and accessibility are improved, but query optimization capabilities are lost because queries cannot leverage relational storage optimizations
Solution Approach 1:
The patent segments the database into multiple partitions, each partition containing a portion of the hierarchical data. This segmentation allows the system to apply different storage and optimization strategies to different segments, enabling query optimization on specific partitions while maintaining hierarchical organization overall.
Solution Approach 2:
The patent introduces an intermediary layer that translates hierarchical queries into relational query forms. This intermediary mechanism enables the system to maintain hierarchical data organization while allowing relational optimization techniques to be applied during query execution, effectively bridging the gap between hierarchical storage and relational optimization.
2Adaptability or versatility
If data is stored in a heterogeneous hierarchical format, then flexibility and adaptability are improved, but the ability to apply traditional relational optimization techniques deteriorates
Solution Approach 1:
The patent changes the parameter of data representation by organizing hierarchical data into partitioned relational structures. This parameter change allows the system to maintain the flexibility of hierarchical storage while transforming the data into a form that can leverage traditional relational optimization techniques, effectively resolving the contradiction between adaptability and optimization applicability.
3Adaptability or versatility
If queries are executed across multiple files and folders mapped to different relational tables, then comprehensive data search capability is improved, but query execution efficiency deteriorates due to inability to use relational optimizations
Solution Approach 1:
The patent segments the data storage into multiple partitions that can be independently optimized and queried. This segmentation allows comprehensive data search across all partitions while enabling efficient query execution on individual partitions using relational optimizations, thereby reducing overall query execution time despite maintaining broad search capability.
Solution Approach 2:
The patent applies partial action by optimizing specific partitions individually rather than requiring optimization across all data. This approach allows the system to achieve significant performance improvements on frequently queried partitions while maintaining the ability to search across the entire distributed data set, effectively balancing comprehensive search capability with execution efficiency.
Data Source
AI summary
Constraints that restrict how corresponding identifiable groups of files are stored in a database, are enforced on corresponding file data. In response to a query on any data from an identifiable group of files, the effect of the constraint on how the corresponding data is stored is determined. The original query is rewritten, based on the effect of the constraint, so that the rewritten query is directed to a particular subset of the data stored in the database. Consequently, the search space is restricted to an identifiable subset of the database and execution of the rewritten query is more efficient than execution of the original query.