Open Executor for Data Stream Processing
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Solution Overview
Problem
Existing stream analytics platforms face challenges in efficiently managing and processing continuous, real-time data streams due to fragile code and error-prone manual management of operator execution patterns, leading to suboptimal performance and incorrect results.
Innovation Solution
The introduction of an open-executor in a stream analytics platform that standardizes operational patterns and supports automatic execution of stream operators, allowing for customizable application logic and elastic parallelization of stateful operators, enabling efficient handling of granular dataflow analytics through chunk-wise and group-wise processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual management of operator execution patterns is used, then flexibility in implementing application logic is maintained, but code fragility and error-proness increase
Solution Approach 1:
The patent introduces an open-executor as an intermediary component that mediates between the stream operators and the execution environment. This open-executor provides standardized interfaces and execution patterns, allowing application logic to be implemented through configuration rather than manual coding, thereby reducing code fragility while maintaining flexibility.
Solution Approach 2:
The patent transforms execution patterns from hardcoded parameters to configurable parameters within the open-executor framework. By allowing execution patterns to be specified as parameters rather than embedded in code, the system achieves both reliability through standardization and adaptability through configurable parameters.
2Reliability
If standardized execution patterns are implemented, then code reliability and consistency improve, but system complexity increases
Solution Approach 1:
The open-executor is designed as a universal component that handles multiple execution patterns and operator types through a single standardized interface. This multi-functionality reduces system complexity by eliminating the need for multiple specialized execution handlers while maintaining execution consistency across different operator types.
Solution Approach 2:
The patent segments the execution system into distinct layers: the open-executor framework providing standardized execution patterns, and the stream operators implementing specific application logic. This segmentation allows complexity to be isolated to the framework layer while keeping operator implementation simple and focused.
3Productivity
If elastic parallelization is applied to stateful operators, then processing throughput increases, but management complexity of dataflow increases
Solution Approach 1:
The open-executor implements self-service mechanisms for managing parallel execution of stateful operators. The framework automatically handles dataflow management, state distribution, and coordination across multiple parallel instances, eliminating the need for manual management while enabling elastic parallelization to increase throughput.
4Measurement precision
If chunk-wise and group-wise processing is implemented, then dataflow analytics precision improves, but processing time increases
Solution Approach 1:
The patent implements periodic action through chunk-wise processing, where data is processed in regular chunks or batches rather than continuously. This periodic processing allows for precise group-wise analytics while managing processing time by breaking down continuous dataflow into manageable periodic segments that can be processed efficiently.
Data Source
AI summary
Customizing functions performed by data flow operators when processing data streams. An open-executor(s) is provided as part of the data stream analytics platform, wherein such open-executor allows for both of: 1) customizing user plug-ins for the operators, to accommodate changes in user requirements; and 2) predefining templates that are based on specific meta-properties of various operators and that are common therebetween.