Dynamic Map Data Structure for Flexible Columnar Data Retrieval
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Solution Overview
Problem
Conventional systems face limitations in retrieving and displaying data from fixed column databases, as they require data to be organized according to predefined indexed and storage rules, making it difficult to access and present user-determined columnar data that is not defined by existing column headers.
Innovation Solution
The system generates a map data structure based on user selections, allowing for the retrieval and display of additional columns of data alongside existing data, without adhering to the database's defined organizational structure, using a query mechanism that constructs key-value pairs to dynamically fetch and render data in a user interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data is stored in a fixed columnar database with predefined indexed structure, then data storage efficiency and retrieval speed are improved, but flexibility to access user-determined columns not defined by existing headers deteriorates
Solution Approach 1:
The system dynamically generates a map data structure based on user selections rather than using a fixed predefined structure. When a user selects specific columns for analysis, the system creates a dynamic map that adapts to the user's needs, allowing flexible access to any combination of columns without being constrained by pre-defined indexes or storage rules.
Solution Approach 2:
The patent introduces a map data structure as an intermediary layer between the fixed columnar database and the user interface. This map acts as a mediator that translates user selections into appropriate data retrieval operations, enabling users to access arbitrary column combinations without directly querying the underlying fixed structure database.
2Loss of time
If data is organized according to predefined indexed rules, then database query efficiency is improved, but ability to present user-determined columnar data deteriorates
Solution Approach 1:
The system performs preliminary actions by generating a map data structure that anticipates user needs. Instead of requiring users to formulate complex queries against predefined indexes, the system proactively creates a flexible map structure that can accommodate any user-determined column combination, thereby eliminating query formulation time while maintaining efficient data access.
Solution Approach 2:
The system changes the structural parameters of data organization by transitioning from fixed predefined indexes to a dynamic map data structure. This parameter change allows the system to maintain efficient data access while simultaneously supporting user-determined column selections, as the map structure can be reconfigured based on user preferences without reorganizing the underlying database.
3Reliability
If standard query techniques are used to access columnar data, then database consistency is maintained, but user accessibility and ease of operation deteriorates
Solution Approach 1:
The map data structure serves as an intermediary that shields users from complex database query techniques. Users simply select desired columns through an intuitive interface, and the map structure handles the translation to appropriate database operations, maintaining database consistency while greatly simplifying user interaction and improving accessibility.
Solution Approach 2:
The system provides self-service by automatically generating the map data structure and handling data retrieval based on user selections. Users do not need to learn or apply standard query techniques; the system autonomously manages the complexity of database interactions while maintaining data consistency, making the system easy to operate for users regardless of their technical knowledge.
Data Source
AI summary
In one general aspect, a method and system are described for generating a map data structure constructed in a tabular form. The map data structure may include a plurality of keys indicated in column headers and a plurality of lists of values indicated in rows. Each list of values may be mapped to a respective key in the plurality of key. The map data structure may be iteratively parsed for each key to generate a plurality of additional columns and additional data. The additional columns and the additional data may be rendered in an updated tabular representation as an extension of the first tabular representation in the user interface.