Database Partitioning for Electrical Data Management
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Solution Overview
Problem
Database response times slow due to increasing amounts of irrelevant historical data, leading to sluggish performance and the need for complex data mining tools, which are expensive and complex, and archiving data decreases performance as databases grow in size.
Innovation Solution
Partitioning electrical data in a database by creating tables associated with distinct groups and dates, storing data based on group and acquisition date, and archiving data according to retention rules, allowing for efficient retrieval and removal of aged data to improve response times and scalability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all historical data is retained in the database, then data completeness is improved, but database response time deteriorates
Solution Approach 1:
The patent segments the database into multiple tables partitioned by date ranges (e.g., current month, previous months, archived historical data). This segmentation allows the system to retrieve only relevant data subsets based on query requirements, avoiding full database scans and improving response time while maintaining data completeness across all partitions.
Solution Approach 2:
The patent extracts older historical data from the active database tables and stores it in separate archived tables or external storage systems. This extraction removes irrelevant or less frequently accessed data from the main query path, reducing the search space for common queries while preserving access to historical data when needed.
2Quantity of substance
If data is archived by retrieving, saving to external file, and removing from database table, then storage efficiency is improved, but database performance deteriorates
Solution Approach 1:
The patent performs preliminary actions by pre-partitioning data into appropriately sized tables based on date ranges before archiving is needed. This proactive organization eliminates the need for time-consuming data retrieval and reorganization operations during archiving, as the data is already structured for efficient storage and retrieval.
Solution Approach 2:
The patent creates copy tables that mirror the structure of active data tables but store archived historical data. These copy tables allow the system to maintain the same query interface and data structure while physically separating archived data, enabling efficient storage without impacting the performance of active database operations.
3Adaptability or versatility
If sophisticated data mining tools are used to extract patterns from large amounts of data, then data analysis capability is improved, but system complexity increases
Solution Approach 1:
The patent extracts and removes the complexity of sophisticated data mining tools by implementing a simpler partitioning-based data organization system. Instead of using complex OLAP tools or advanced data mining software, the system achieves efficient data analysis by organizing data into date-partitioned tables that enable straightforward querying and pattern recognition with standard database operations.
Data Source
AI summary
A method of partitioning and archiving electrical data received from a power monitoring system in a database including a plurality of tables organized by at least group and date. Data in the database is queried by first searching an electrical data catalog to determine whether the data exists in the database before searching the database. The data is targeted by group and by date, yielding faster response times and enhanced database scalability. An electrical data retention table includes a set of rules governing, for each group, the maximum age of the data that can be stored in the table in the database. A data table associated with a particular group whose age exceeds the maximum age provided in the set of rules is removed from the database and from the electrical data catalog. If desired, the entire data table can be imported back into the database.