Utility Meter Data Query Optimization
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Solution Overview
Problem
Current meter data management systems face inefficiencies in accessing and processing large volumes of data from utility data stores, leading to prolonged query times due to the need for numerous queries for small amounts of data, particularly in environments with millions of readings.
Innovation Solution
Implementing a calculation engine that retrieves configuration data and readings in batches, building processing trees to enable efficient querying of utility data stores, and estimating boundary readings by analyzing register readings, thereby reducing the number of queries required.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If the meter data management service queries the data store for each piece of data as needed, then the system can obtain readings and information, but the number of queries increases significantly and processing time lengthens
Solution Approach 1:
The patent performs preliminary actions by identifying all required service point channels and their associated formulas before querying the data store. The system builds a complete query plan that determines all necessary readings and information in advance, then executes a single comprehensive query to retrieve all required data at once, eliminating the need for multiple sequential queries.
2Ease of operation
If the system retrieves data in multiple separate queries, then it can obtain specific readings when needed, but the overall processing efficiency decreases
Solution Approach 1:
The patent merges multiple separate data retrieval operations into a single unified query. By combining all required service point channel identifiers and formula information into one query statement, the system retrieves all necessary readings and configuration data in a single operation, dramatically improving processing efficiency while maintaining the ability to retrieve specific data points.
3Reliability
If the meter data management service performs utility processing for multiple service point channels sequentially, then it can validate and report readings, but the processing time increases with the number of channels
Solution Approach 1:
The system performs preliminary identification of all service point channels requiring validation and reporting before executing queries. By pre-determining the complete set of channels and their associated formulas, the system can process all channels in parallel or batch mode after the initial query, maintaining validation accuracy while significantly increasing processing throughput compared to sequential handling.
Data Source
AI summary
Information in a data store may be efficiently accessed to perform boundary reading processing. In one example, register readings of one or more register channels that are linked to one or more interval channels may be retrieved from the data store to determine whether or not a boundary reading of a time span is missing. If a boundary reading is missing, but a proximate register reading exists, the boundary reading may be estimated from the proximate register reading and at least one interval reading.