Unified Data Pipeline Configuration via Source Connectors
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Solution Overview
Problem
Conventional data pipeline systems face inflexibility and inefficiency due to rigid frameworks that require extensive modification for different data sources, leading to complex and user-intensive configuration processes, limiting adaptability and ease of use across various data sources.
Innovation Solution
A data transformation system that utilizes source and target connectors to map unified request formats to native code commands, enabling dynamic execution of data pipeline job configurations across diverse data sources without requiring low-level implementation code, thus facilitating adaptable and user-friendly data pipeline management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional data pipeline frameworks use data source specific languages or APIs for configuration, then the system can communicate with and utilize particular data sources, but the system requires extensive modification when interacting with different data sources or when data sources change recognized languages or APIs
Solution Approach 1:
The patent introduces an intermediary layer (the data pipeline execution system) that translates between a unified request format and data source specific native code commands. This mediator allows the configuration to remain simple and unified while still enabling communication with diverse data sources through automatic translation to their specific languages or APIs.
Solution Approach 2:
The patent implements a universal request format that can be used with multiple different data sources without modification. This universal interface allows a single configuration to work across various data sources, eliminating the need for data source specific configuration languages or APIs while maintaining broad compatibility.
2Ease of operation
If conventional systems require coding of low-level implementations for each data source, then the system can connect to and execute commands on specific data sources, but the system requires highly technical users and lacks ease of use for wider audiences
Solution Approach 1:
The execution system acts as an intermediary that handles the complexity of low-level implementation details automatically. Users interact with a simple unified request format while the system translates these requests into data source specific native code commands, eliminating the need for users to code low-level implementations for each data source.
Solution Approach 2:
The system performs automatic translation and adaptation without requiring user intervention. The execution system self-services by converting unified requests into appropriate native commands for different data sources, removing the burden from users to manually adapt configurations for each data source.
3Productivity
If conventional systems create data pipeline job configurations with individually customized instructions for different data sources, then the system can be precise in its interaction with each data source, but the system requires time intensive modification or creation of configurations and extensive user interaction
Solution Approach 1:
The patent implements a universal request format that serves multiple data sources with a single configuration. This eliminates the need to create individually customized configurations for each data source, allowing one configuration to work across various data sources without time-intensive modification while maintaining precise interaction through automatic translation.
Solution Approach 2:
The execution system serves as an intermediary that automatically handles the translation from unified requests to data source specific commands. This eliminates the manual time-intensive process of creating customized configurations for each data source, as the system automatically generates the appropriate native code commands based on the unified request format.
Data Source
AI summary
The disclosure describes embodiments of systems, methods, and non-transitory computer readable storage media that dynamically execute data source agnostic data pipeline job configurations that can interact with a variety of data sources while utilizing a unified request format. In particular, the disclosed systems can facilitate a data pipeline framework that utilizes source connectors for data sources, target connectors for data sources, and data transformations in data pipeline job configurations to build various data pipelines. For instance, the disclosed systems can utilize a data pipeline job configuration that includes requests for a data source in a given language with various other data pipeline functionalities via data source connectors specified within the data pipeline job configuration. For example, the disclosed systems can utilize a data source connector to map data source requests to native code commands for the data source to read or write data in relation to the data source.