Prioritized Data Structure for Fast Field Access
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Solution Overview
Problem
Existing data handling methods, such as ArrayLists and HashMaps, are inefficient when processing large volumes of data structures, particularly for read operations that do not utilize all data fields, leading to high processing times and increased complexity and cost when attempting to address these inefficiencies.
Innovation Solution
A new data structure is created with a sequential index and array of values, including a subset of prioritized entries that are the most commonly accessed, allowing for direct access to these fields without hash lookups or iterations, while maintaining interoperability and using standard Java Collection formats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If HashMap is used for data storage, then constant access time for reading individual entries is achieved, but processing speed is slower than ArrayList for small size Collection
Solution Approach 1:
The data structure is segmented into two parts: a prioritized subset of commonly accessed fields stored in an optimized format for fast reading, and the remaining fields stored in standard format. This segmentation allows different access patterns for different portions of the data, resolving the contradiction between fast access and processing speed.
Solution Approach 2:
Different parts of the data structure are given different qualities: the prioritized subset fields are stored with direct index access for optimal read performance, while other fields use standard storage. This local optimization resolves the contradiction by making the commonly accessed portion fast without sacrificing overall processing capability.
2Productivity
If ArrayList is used for data storage, then faster processing for small size Collection is achieved, but access time increases due to iteration requirements
Solution Approach 1:
The system performs preliminary action by pre-identifying and prioritizing the subset of fields that are most commonly accessed in read operations. This preliminary classification allows the data structure to be optimized in advance for the specific access patterns of the application, resolving the contradiction between processing speed and access time.
3Adaptability or versatility
If standard Java data structures are used, then interoperability across different processing systems is maintained, but processing efficiency decreases for large volumes of data
Solution Approach 1:
The data structure is made dynamic by allowing configuration of the prioritized subset based on specific application requirements. The system can adapt its optimization strategy dynamically according to the access patterns and requirements of different processing systems, maintaining interoperability while improving processing efficiency for large data volumes.
Data Source
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AI summary
A method of processing a target data structure having a plurality of data fields and corresponding indices is described. The method comprises: receiving a pre-determined set of field names, wherein the set of field names comprises a prioritised subset of data fields of the target data structure including at least one prioritised field name and a corresponding index identifier; establishing, for each prioritised field name in the set of predetermined field names, an access key for directly accessing a data field of the target data structure using the index identifier to determine the corresponding index where the data field corresponds to the prioritised field name; and processing the target data structure to generate an output, wherein the processing step comprises reading a data value of a data fields of the target data structure directly using the access key when the data field to be read corresponds to a prioritised field name.