Stream Processing Pipeline Configuration via Dynamic Files
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Solution Overview
Problem
Traditional stream processing pipelines are inflexible and difficult to configure based on data properties and user requirements, leading to performance issues and data transmission bottlenecks in distributed-computing systems.
Innovation Solution
A customizable configuration file is used to generate stream processing pipelines with customizable pipeline stages, allowing for flexible configuration based on tenant systems and data properties, and includes designated buffer stages for each data service to eliminate bottlenecks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional stream processing pipelines are used, then data collection and processing can be performed, but the pipelines are inflexible and difficult to configure based on data properties and user requirements
Solution Approach 1:
The patent implements dynamic configuration of stream processing pipelines by allowing the configuration to be modified at runtime without requiring pipeline restart. The system loads configuration parameters from external sources (such as configuration files or databases) and applies them to the running pipeline, enabling flexible adaptation to different data properties and user requirements while maintaining pipeline operation.
Solution Approach 2:
The patent enables parameter changes in the stream processing pipeline by allowing configuration parameters to be adjusted dynamically. Different parameters such as buffer sizes, processing thresholds, and data source configurations can be modified based on data properties and user requirements, providing adaptability without requiring complete pipeline reconfiguration or restart.
2Productivity
If traditional buffering techniques are used in stream processing pipelines, then data can be buffered for processing, but data transmission bottlenecks occur
Solution Approach 1:
The patent segments the buffering function into multiple distributed buffer components located at different nodes in the stream processing pipeline. Instead of a single centralized buffer that creates bottlenecks, the system uses multiple buffer instances that can operate in parallel, distributing the buffering load and eliminating transmission bottlenecks while maintaining high data processing throughput.
3Adaptability or versatility
If stream processing pipelines are configured for different tenant systems and data properties, then customization and performance improvement are achieved, but configuration and management become more complex
Solution Approach 1:
The patent implements a universal configuration framework that can serve multiple tenant systems and different data properties through a common set of configurable parameters. The system uses standardized configuration templates and parameter sets that can be applied across different tenants, reducing the complexity of configuration and management while still allowing tenant-specific customization through parameter adjustment rather than structural modification.
Data Source
AI summary
Techniques for generating a stream processing pipeline are provided. In one embodiment, a method includes receiving a configuration file from a data service. The configuration file represents a pipeline configuration of the stream processing pipeline, and the pipeline configuration includes representations of a plurality of different types of pipeline stages configured based on a respective customization of an entity. The method further includes generating a plurality of pipeline stages in accordance with the pipeline configuration of the stream processing pipeline; collecting, at one or more pipeline stages of a first-type in the stream processing pipeline, data items from one or more data sources; processing the collected data items at one or more pipeline stages of a second-type in the stream processing pipeline; and transmitting, at one or more pipeline stages of a third-type in the stream processing pipeline, the processed data items to the data service.