Hierarchical Dataset Serialization for Database Storage Efficiency
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Solution Overview
Problem
Existing database systems face challenges in efficiently storing and retrieving datasets with hierarchical structures, as they often require complex data formats and large volumes, which existing technologies struggle to handle effectively.
Innovation Solution
A data processing system that serializes hierarchical datasets into data strings, generates a globally unique identifier as an access key, and stores these strings in a database table, allowing for efficient storage and retrieval by using a serializer and deserializer to convert between hierarchical and flat data formats, while accommodating dynamic changes to data structures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If hierarchical datasets are stored directly in database tables, then the data structure complexity is maintained, but the storage efficiency and retrieval performance deteriorate
Solution Approach 1:
The patent segments the storage process into two distinct parts: (1) serialization of hierarchical data into flat format, and (2) storage of the serialized data in database tables. This segmentation allows the system to maintain storage efficiency while managing data structure complexity through the serialization intermediary.
Solution Approach 2:
The patent introduces serialization as an intermediary process between the hierarchical data structure and the database table storage. The serializer converts complex hierarchical data into a flat format suitable for database storage, while the deserializer reconstructs the hierarchical structure during retrieval, thus resolving the contradiction between maintaining data structure and improving storage efficiency.
2Adaptability or versatility
If complex hierarchical data formats are used, then the data modeling capability is improved, but the system's ability to handle and process the data deteriorates
Solution Approach 1:
The patent implements dynamic data handling through runtime serialization and deserialization processes. The system can adapt to different hierarchical data formats and structures by dynamically serializing them into a standardized flat format for efficient processing and storage, then deserializing back to the original structure when needed, thus maintaining both adaptability and processing efficiency.
3Quantity of substance
If large volumes of hierarchical data are stored, then the data capacity is increased, but the retrieval time and processing overhead increase
Solution Approach 1:
The patent applies preliminary action by pre-serializing hierarchical data into a compact flat format before storage. This preprocessing step reduces the storage footprint and optimizes the data layout for faster retrieval operations, allowing large volumes of data to be stored with minimized retrieval time and processing overhead.
Data Source
AI summary
Systems and methods are provided for storing a dataset having a hierarchical data structure in a database. In one implementation, a data processing system includes a data dictionary for storing data that describes predefined hierarchical data structures, wherein each data structure includes a plurality of data fields that have a unique field name and at least one field attribute. The data processing system also includes a volatile storage that stores a dataset having a unique dataset name. The dataset is an instance of one of the predetermined hierarchical data structures. A serializer is provided that converts the dataset into a data string. An access key is generated for the data string. Moreover, the data processing system includes a non-volatile storage that stores a database table and database export means for storing the string in the database table using the access key that is assigned to the dataset name.