User-Defined Data Loading Logic for Database Ingestion
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Solution Overview
Problem
Existing data loading methods lack flexibility and efficiency in managing data from diverse sources and formats, requiring users to define logic for each data load and lacking optimization for bottlenecks, which complicates the process and reduces efficiency.
Innovation Solution
A method that allows users to define user-defined logic for data loading, including location identification, filtering, and parsing, with the option for late binding and dynamic policy management, enabling customization and optimization of data loading processes through a unified interface and data loading manager.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing data loading methods are used, then data can be loaded from standard sources, but flexibility and efficiency are reduced due to inability to customize loading logic
Solution Approach 1:
The system enables users to define their own loading logic through a user-friendly interface, allowing self-service customization of data loading processes. Users can specify location identification, filtering criteria, and parsing operations without requiring extensive knowledge of distribution computation systems, thereby achieving flexibility while managing complexity through guided self-configuration.
Solution Approach 2:
The patent introduces an intermediary layer between users and the complex data loading infrastructure. This intermediary provides a simplified interface that translates user-defined logic into executable loading operations, shielding users from underlying system complexity while enabling customized data loading from diverse sources and formats.
2Adaptability or versatility
If users define custom loading logic, then flexibility improves, but the ease of operation decreases due to requirement for extensive knowledge
Solution Approach 1:
The system provides self-service capabilities by allowing users to define loading logic through an intuitive interface without requiring extensive technical knowledge. Users can configure location identification, filtering, and parsing operations directly, making the system both customizable and easy to operate through guided self-configuration.
Solution Approach 2:
The patent enables parameter changes through a user-friendly interface that allows users to modify loading parameters such as location identification, filtering criteria, and parsing operations. This approach maintains ease of operation by presenting parameters in an accessible format while enabling full customization capability through parameter modification.
3Productivity
If data loading is optimized for efficiency, then productivity improves, but device complexity increases due to bottleneck optimization requirements
Solution Approach 1:
The system incorporates feedback mechanisms that automatically optimize data loading based on detected bottlenecks and performance characteristics. By monitoring loading processes and adjusting parameters accordingly, the system achieves improved productivity while managing complexity through automated feedback-driven optimization rather than manual configuration.
Solution Approach 2:
The patent applies preliminary action by pre-configuring optimization parameters and pre-processing data based on detected characteristics before the main loading operation. This allows the system to identify and prepare optimization strategies in advance, improving loading efficiency while reducing the complexity of real-time decision-making during the actual data loading process.
Data Source
AI summary
As part of managing the loading of data from a source onto a database, according to an example, an interface through which a user is to define logic related to the loading of the data onto the database is provided. The user-defined logic pertains to at least one of a user-defined location identification of the source, a user-defined filter to be applied on the data, and a user-defined parsing operation to be performed on the data to convert the data into an appropriate format for the database. In addition, the user-defined logic is received and the user-defined logic is implemented to load the data onto the database.