Tagged Column-Oriented Data Structures for Faster Project Filtering
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Solution Overview
Problem
Existing project management software applications lack efficient data filtering and aggregation capabilities, making it difficult to quickly retrieve relevant project information in real time.
Innovation Solution
A system and method for generating tagged column-oriented data structures, where columns contain cells of a single data type, including at least one tag type column, allowing for rapid data location and filtering based on tags.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional row-oriented data structures are used in project management software, then data storage is simple and straightforward, but data filtering and aggregation capabilities are inefficient and slow
Solution Approach 1:
The patent segments data into column-oriented structures where each column represents a specific data attribute (e.g., project name, task name, status) and contains only values of that attribute type. This segmentation enables efficient filtering and aggregation operations on specific columns without processing entire rows, directly improving data filtering efficiency while maintaining structured organization.
Solution Approach 2:
The patent transitions from traditional row-oriented data storage to column-oriented data storage, effectively changing the dimensional organization of data. This dimensionality change allows for more efficient data retrieval and aggregation operations by enabling direct access to specific columns and their values, significantly improving productivity in data filtering and aggregation tasks.
2Loss of time
If comprehensive project data is stored in traditional data structures, then all project information is available, but retrieving relevant data quickly becomes difficult and time-consuming
Solution Approach 1:
The patent extracts specific columns containing relevant data attributes (such as project name, task name, status, cost) from the comprehensive data set and organizes them into separate column structures. This extraction enables rapid retrieval of specific data types without processing or scanning through all project data, significantly reducing data retrieval time while maintaining access to the full data volume when needed.
Solution Approach 2:
The patent assigns specific data types and validation rules to each column, creating local quality constraints that ensure only valid data is stored in each column. This local quality approach not only improves data integrity but also enables optimized storage and retrieval operations for each column type, reducing the time required to access and process relevant data while maintaining comprehensive data storage capacity.
Data Source
AI summary
A system and method for generating tagged column-oriented data structures, including: generating a column-oriented data structure that comprises a plurality of columns, wherein each column comprises a plurality of cells that are associated with a single data type, wherein at least one of the plurality of columns is a tag type column; and inserting at least one tag into a first cell of the tag type column, where the first cell further associated with a first row of cells.