Real-Time and Non-Real-Time Read Channels for Stream Isolation
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Solution Overview
Problem
The management and orchestration of large, dynamically fluctuating streams of data in distributed systems is challenging due to workload imbalances, resource underutilization, and the need for diverse processing speeds, which can lead to performance issues and disruptions.
Innovation Solution
Implementing a data stream management service (SMS) with isolated read channels (IRCs) that provide logical isolation and customizable read scalability, using techniques like proactive migration and partition storage reconfiguration to meet the diverse needs of different applications, and employing persistent network connections for data transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If more resources are added to handle large streams of data, then system capacity increases, but workload imbalances and resource underutilization occur
Solution Approach 1:
The patent segments the data stream into multiple partitions that can be independently processed by different computing resources. This segmentation allows workloads to be distributed across multiple nodes, preventing any single resource from becoming a bottleneck while maintaining overall system capacity. Each partition can be assigned to specific processing units, enabling balanced resource utilization.
Solution Approach 2:
The patent implements dynamic resource allocation and load balancing mechanisms that automatically adjust workload distribution based on real-time system conditions. Computing resources can be dynamically assigned to different partitions as needed, allowing the system to adapt to fluctuating data streams and maintain optimal resource utilization without manual intervention.
2Speed
If resources are allocated for fast processing, then near instantaneous analysis is achieved, but other applications with lower speed requirements suffer from resource underutilization
Solution Approach 1:
The patent applies different quality levels of processing to different data partitions based on application requirements. Some partitions can be processed with high-speed resources for time-critical applications, while other partitions use standard-speed resources for less time-sensitive applications. This local differentiation optimizes both speed for critical operations and overall resource utilization across the system.
Solution Approach 2:
The patent allows processing parameters such as computation depth, aggregation frequency, and resource allocation to be changed per partition or per application. This enables fast processing where needed while using slower, more resource-efficient processing elsewhere, thereby improving overall resource utilization without sacrificing critical performance requirements.
3Quantity of substance
If distributed systems grow in size, then more data can be processed, but connectivity failures and hardware failures occur more frequently
Solution Approach 1:
The patent implements preliminary failure detection and recovery mechanisms that proactively monitor system health and prepare recovery actions before failures disrupt operations. Checksum verification, data replication, and automated failover protocols are established in advance, allowing the system to maintain reliability as it scales by quickly detecting and recovering from failures without data loss or extended disruptions.
Data Source
AI summary
In response to a first programmatic request, metadata indicating that a first isolated read channel of a real-time category has been associated with a first target stream is stored at a stream management service. In response to another request, metadata indicating that a second isolated read channel of a non-real-time category has been associated with a second target stream is stored. In response to a read request indicating the first channel or the second channel, one or more data records of the corresponding target streams are provided.