Logical Access for Expanded View Datasets
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Solution Overview
Problem
Current data processing systems are inefficient in generating datasets for complex computations, as they often materialize all related data, leading to computational and storage costs, and result in stale data due to pre-generation before actual use.
Innovation Solution
The system enables users to preview attributes of an expanded view dataset, allowing selection of specific fields for downstream processing, generating a dataset that includes only the necessary fields, thereby optimizing speed and memory usage by providing logical access without materializing the entire dataset.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If all fields of an expanded view dataset are materialized for downstream processing, then data availability and completeness are improved, but computational cost and memory usage increase significantly
Solution Approach 1:
The system extracts only the specific fields required by downstream processing tasks from the expanded view dataset, rather than materializing all fields. The field selection mechanism identifies and retrieves only necessary columns, eliminating unnecessary data extraction and processing overhead.
Solution Approach 2:
The expanded view dataset is segmented into individual fields that can be selectively accessed. The system divides the complete dataset structure into discrete, independently accessible fields, allowing downstream processes to request only the specific segments they need rather than processing the entire dataset.
2Ease of operation
If the entire expanded view dataset is generated before use, then data accessibility is improved, but storage cost and data staleness worsen
Solution Approach 1:
The system performs preliminary definition of the expanded view dataset structure and field metadata, but delays actual data materialization until needed. The dataset definition, relationships, and field descriptions are prepared in advance, enabling quick on-demand generation of specific fields without pre-generating all data.
Solution Approach 2:
Instead of storing and transferring complete dataset copies, the system uses lightweight field definitions and metadata that describe the expanded view structure. These definitions enable rapid reconstruction of specific fields from source data without copying entire datasets.
3Manufacturing precision
If all fields are included in the dataset for comprehensive analysis, then analytical completeness is improved, but processing speed decreases
Solution Approach 1:
The system dynamically adjusts the dataset content based on downstream processing requirements. Field selection is not fixed but adapts to the specific needs of each processing task, allowing the dataset to be optimized in real-time for both completeness and processing speed by including only relevant fields.
Data Source
AI summary
A method implemented by a data processing system for: enabling a user to preview attributes of fields of an expanded view of a base dataset and to specify one or more of the fields to use in downstream data processing and generating a dataset that includes the one or more of the fields from the preview specified to be used in the downstream data processing, with the generated dataset having increased efficiency with respect to speed and data memory, relative to an efficiency of generating a dataset including all the fields of the expanded view when only the specified one or more of the fields are used in the downstream data processing.