Task Node Restart via Periodic Checkpointing
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Solution Overview
Problem
The management and orchestration of large, dynamically fluctuating streams of data pose challenges due to workload imbalances, leading to performance issues and resource wastage, with existing solutions requiring resource restarts and extensive searches for previous states during restarts, resulting in significant delays.
Innovation Solution
Implementing a data ingestion service that periodically checkpoints data source progress points into a common data structure, allowing for faster restarts and dynamic task configuration without restarting task nodes, enabling efficient resumption of data processing and configuration changes without downtime.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If resources are restarted during repartitioning, then workload distribution is improved, but system delay increases significantly
Solution Approach 1:
The system performs preliminary checkpointing of resource states at regular intervals before repartitioning occurs. When repartitioning is needed, resources can restart and recover their state from the most recent checkpoint rather than searching through entire logs, dramatically reducing restart delay while still enabling workload redistribution.
Solution Approach 2:
The patent extracts the resource state information from the main data stream logs and stores it separately in checkpoint data structures. This allows resources to quickly recover state without searching through lengthy operational logs, reducing restart time while maintaining the ability to redistribute workloads.
2Measurement precision
If resources search through lengthy logs to determine previous state during restart, then state recovery accuracy is improved, but restart delay increases
Solution Approach 1:
The system pre-captures and stores resource state information at checkpoint intervals throughout operation. When a resource needs to restart, it can immediately retrieve its state from the nearest preceding checkpoint without searching through entire logs, ensuring accurate state recovery while minimizing restart delay.
Solution Approach 2:
The patent creates copies of resource state information at regular checkpoints and stores them in dedicated checkpoint data structures. During restart, resources retrieve state from these copied checkpoint data rather than searching original logs, maintaining recovery accuracy while dramatically reducing the time needed to locate state information.
3Adaptability or versatility
If all resources are restarted whenever any repartitioning occurs, then workload balance is improved, but system availability decreases
Solution Approach 1:
The system segments the resource restart process by allowing individual resources to restart independently based on their specific repartitioning needs rather than forcing a system-wide restart. Resources that don't need repartitioning can continue operating, maintaining system availability while still achieving workload balance through targeted resource restarts.
Solution Approach 2:
By pre-checkpointing resource states, the system enables selective resource restarts during repartitioning events. Resources can recover quickly from checkpoints without requiring other resources to restart, maintaining overall system availability while still achieving the desired workload redistribution.
Data Source
AI summary
Various embodiments of systems and methods for faster restart of task nodes using periodic checkpointing for data sources are described. A task node obtains data from data sources in order to perform one or more tasks. The task node checkpoints data source progress points for each of its data sources, whether active or inactive, into a common checkpoint data structure at least once every time interval. Multiple task nodes checkpoint their data source progress points into the same common checkpoint data structure. After restart, the task node determines where to resume obtaining data from its data sources by determining a limited portion of the common checkpoint data structure based on the time interval, analyzing only the limited portion of the common checkpoint data structure, retrieving the data source progress points for each of its data sources, and resuming obtaining data from the data sources to perform tasks.