Dataflow Controller Segmentation for Stream Processing Reliability
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Large-scale cloud and Internet service providers face challenges in managing high variability and uncertainties in event streams, leading to resource underutilization and instability in stream processing systems due to inevitable failures and hardware heterogeneity.
Innovation Solution
Implementing a dataflow controller technology where dedicated controllers manage individual dataflow execution graphs, with a higher-level controller overseeing multiple dataflow controllers, and using a pool of pre-instantiated controllers to rapidly replace failed ones, ensuring robustness and resilience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single shared controller manages multiple dataflow execution graphs, then device complexity is reduced, but reliability deteriorates because a single controller failure can impact multiple execution graphs
Solution Approach 1:
The controller is segmented into multiple dedicated controllers, where each controller is assigned to manage a specific dataflow execution graph. This segmentation isolates failure domains so that a controller failure impacts only its assigned execution graph rather than multiple graphs, thereby improving reliability while maintaining manageable complexity through clear assignment boundaries.
2Reliability
If dedicated controllers are assigned to each dataflow execution graph, then reliability is improved by isolating failure impact, but device complexity increases due to multiple controllers
Solution Approach 1:
Each dedicated controller is designed with universal functionality to manage any dataflow execution graph assigned to it. The controllers implement standardized interfaces and control logic that can handle diverse execution graphs, allowing the system to scale by adding identical multi-functional controller units rather than requiring specialized controllers for each graph, thus managing complexity through uniformity.
3Reliability
If resources are provisioned with safety factors to handle variability, then reliability is improved, but resource utilization deteriorates due to idle resources
Solution Approach 1:
The system dynamically assigns and reassigns dedicated controllers to different dataflow execution graphs based on runtime conditions, workload characteristics, and controller availability. This dynamic allocation allows the system to adapt to temporal and spatial variability in event streams, maintaining reliable performance through appropriate safety factors while optimizing resource utilization by matching controller resources to actual demand rather than static over-provisioning.
Data Source
AI summary
A dataflow controller technology. A dataflow execution graph (such as a directed acyclic graph) receives or is to receive one or more data streams for processing. The control of the dataflow execution graph is performed by a set of one or more dataflow controllers that are dedicated to that dataflow execution graph. Each dataflow execution graph is instantiated and assigned to the dataflow execution graph such that the assignment results in the dataflow controller executing dataflow control functions for that dataflow execution graph. By dedicating controller(s) to only one dataflow execution graph, the risk of failure of the controller is bound to a single dataflow execution graph.