Database Query Optimization Using Reference Matrix
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Solution Overview
Problem
Conventional database search systems process all columns during queries, including null columns, leading to hardware inefficiency due to unnecessary processing, which consumes resources and reduces utilization.
Innovation Solution
A system that generates optimized queries by using a reference matrix to identify and exclude null columns, constructed through machine learning, allowing only relevant columns to be searched, thereby reducing the number of columns processed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If complete queries of large databases are performed processing all columns including null columns, then comprehensive search results are obtained, but hardware efficiency deteriorates due to unnecessary processing
Solution Approach 1:
The patent extracts and removes null columns from the database query processing pipeline. By identifying columns that contain only null values and excluding them from search operations, the system eliminates unnecessary processing while preserving all relevant data columns, thus resolving the contradiction between comprehensive results and hardware efficiency
Solution Approach 2:
The patent applies partial action by processing only the necessary subset of columns rather than all columns. The system dynamically determines which columns contain valid data and processes only those columns during search operations, avoiding the excessive processing of null columns while maintaining complete search functionality
2Loss of information
If all columns are processed during search operations, then complete data is retrieved, but processing power is wasted on null columns
Solution Approach 1:
The system extracts and identifies null columns through metadata analysis and removes them from the processing set. By separating null columns from data columns, the system retrieves complete information from relevant columns while eliminating energy-wasting operations on null columns
Solution Approach 2:
The patent performs preliminary analysis of column data characteristics before executing search operations. By pre-identifying which columns contain valid data through metadata inspection, the system prepares an optimized query plan that avoids wasting processing power on null columns while ensuring complete data retrieval from valid columns
3Reliability
If null columns are included in search operations, then comprehensive coverage is achieved, but execution time increases
Solution Approach 1:
The system extracts null columns from the query execution plan by analyzing column metadata before search operations. This removal of null columns reduces the number of columns that need to be scanned and processed, directly decreasing execution time while maintaining comprehensive coverage of all data columns
Solution Approach 2:
The patent performs preliminary identification of null columns through metadata inspection prior to executing search operations. This advance preparation creates an optimized query plan that excludes null columns, thereby reducing execution time without compromising the comprehensiveness of search results
4Measurement precision
If complete queries process all columns, then accurate results are produced, but memory usage increases
Solution Approach 1:
The system extracts and identifies null columns through metadata analysis and excludes them from query processing. This reduction in the number of processed columns decreases the amount of data that needs to be loaded into memory, thereby reducing memory usage while preserving result accuracy from all valid data columns
Data Source
AI summary
Various systems, methods, and computer program products are provided for optimizing database querying. The method includes receiving a search request to perform a search operation associated with a database. The search request includes one or more search values. The method also includes identifying one or more search columns of the database based on at least one of the one or more search values. The identification of the one or more search columns includes comparing the at least one of the one or more search values with a reference matrix. The reference matrix relates to contents of the database. The method further includes updating the search request based on the one or more search columns identified. The method still further includes causing a transmission of the updated search request for performance of the search operation.