Batch Query Calculation Engine for Utility Meter Data
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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 small queries for information and readings.
Innovation Solution
Implementing a calculation engine that retrieves configuration data and readings in batches, building processing trees to enable single queries for multiple service point channels, and estimating boundary readings by analyzing register and interval readings, thereby reducing the number of queries required.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the meter data management service queries the data store for information and readings as each piece of data is needed, then the service can obtain the required data, but the number of queries to the data store increases significantly, lengthening the time needed to obtain readings and perform utility processing
Solution Approach 1:
The patent applies preliminary action by performing utility processing operations (validation, reporting, etc.) in advance before the actual readings are needed. The system queries the data store for batches of readings and performs processing operations on these readings beforehand, storing the processed results. When readings are subsequently needed, the pre-processed data is already available, eliminating the need for time-consuming queries and processing at the moment of need.
2Reliability
If the meter data management service performs utility processing for multiple service point channels, then comprehensive data validation and reporting are achieved, but the number of individual queries to the data store increases, reducing overall processing speed
Solution Approach 1:
The patent applies merging by combining multiple service point channel queries into single batch queries to the data store. Instead of querying each service point channel individually for validation and reporting operations, the system consolidates these requests and retrieves data for multiple channels in one query operation. This dramatically reduces the total number of queries while maintaining comprehensive validation and reporting across all channels.
3Measurement precision
If the system retrieves readings and configuration data in individual small batches, then data accuracy is maintained, but the total number of queries to the data store increases, extending processing time
Solution Approach 1:
The system performs preliminary actions by retrieving and processing configuration data and readings in advance for multiple service point channels. By querying the data store for batches of configuration data and readings before they are needed for validation or reporting, the system prepares the data beforehand. This preliminary retrieval and processing eliminates the need for subsequent individual queries, maintaining data accuracy while significantly reducing total retrieval time.
Data Source
AI summary
Information in a data store may be efficiently accessed by querying the data store for batches of information. In one example, configuration data associated with service point channels of processing trees may be retrieved from the data store with a single query to the data store. Readings for the processing trees may also be retrieved from the data store with a single query to the data store.