Database Storage Structure for Timestamped Data Retrieval
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Solution Overview
Problem
Conventional database systems, particularly relational databases, face challenges in efficiently analyzing historical data due to limited built-in support for querying and resource-intensive vendor-specific queries, making it difficult to manage and analyze vast amounts of timestamped data from networked devices like printers and MFDs.
Innovation Solution
A database management system with a first data storage structure for unordered timestamped counter data entries and a second data storage structure that maps address data, timestamps, and device identifiers, allowing for quick identification of non-null counter data entries within specified time periods, reducing computational costs by eliminating the need for extensive searches.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional relational database systems are used to store and analyze timestamped data from multiple devices, then data can be stored in a structured manner, but querying and analyzing historical data requires significant computational resources and vendor-specific complex queries that reduce system performance
Solution Approach 1:
The patent divides the database into two separate storage structures: a first data storage structure for storing timestamped counter data entries in an unordered manner, and a second data storage structure for storing mapping information (address data, timestamps, device identifiers). This segmentation allows efficient querying by separating the raw data storage from the index/mapping storage, enabling quick location of relevant data without scanning entire datasets.
Solution Approach 2:
The second data storage structure acts as an intermediary between the query system and the first data storage structure. It contains mapping information that directly links timestamps and device identifiers to storage addresses, serving as a lookup table that eliminates the need for complex vendor-specific queries and reduces computational overhead for data retrieval.
2Adaptability or versatility
If data is stored in an unordered manner in the first data storage structure, then storage flexibility is improved, but retrieving specific time period data requires extensive searching through all entries
Solution Approach 1:
The system performs preliminary action by pre-computing and storing mapping information in the second data storage structure. When data is inserted into the first storage structure, the corresponding mapping (storage address, timestamp, device identifier) is simultaneously created in the second structure. This preliminary organization enables O(1) or O(log n) retrieval time instead of requiring a full scan of unordered data.
3Adaptability or versatility
If vendor-specific complex queries are used to analyze historical data, then analytical capabilities are enhanced, but computational resources are significantly consumed reducing overall system performance
Solution Approach 1:
The patent creates a simplified copy or view of the data through the second data storage structure that contains only the essential mapping information (address data, timestamps, device identifiers). This copied structure provides analytical capabilities for querying by time period and device without requiring complex vendor-specific queries on the full dataset, significantly reducing computational resource consumption while maintaining analytical versatility.
Data Source
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AI summary
A database management system comprises a first data storage structure, a second data storage structure, and data access means. The first data storage structure is for storing timestamped counter data entries for each of a plurality of devices in an unordered manner and such that each counter data entry is assigned a uniquely identifiable storage address. The second data storage structure is for storing and mapping between: address data that identifies the storage addresses of counter data entries, excluding those counter data entries which are null or empty, timestamps corresponding to the counter data entries, and device identifiers that identify the devices to which the counter data entries correspond. The data access means is for, in response to receiving a request for data in respect of a specified time period and at least one of the plurality of devices, using the second data storage structure to identify, for the or each specified device, the storage addresses of the temporally first and last counter data entries that fall within the specified time period and that are not null or empty.