Tiered Streaming Storage Prefetch for Lower Batch-Read Latency
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Solution Overview
Problem
Conventional streaming storage systems lack a tiered storage layout that efficiently manages data distribution across different storage tiers, leading to increased latency during batch reads from long-term storage services, especially when dealing with varying read behaviors.
Innovation Solution
Implementing asynchronous, parallel prefetch reads from long-term storage while a reader performs batch reads, using heuristics to determine when to initiate prefetch based on client read patterns, particularly for sequential access behaviors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If data is stored in long-term storage service for cost effectiveness, then storage cost is reduced, but read latency increases substantially
Solution Approach 1:
The system performs preliminary actions by executing asynchronous prefetch reads from long-term storage before the actual read requests are needed. The prefetch mechanism proactively retrieves data from long-term storage and caches it in memory, so that when readers need the data, it is already available in fast memory, eliminating the latency of synchronous reads while maintaining cost-effective long-term storage.
2Reliability
If synchronous reads are performed from long-term storage, then data accuracy is ensured, but throughput decreases due to waiting for replies
Solution Approach 1:
The system introduces an intermediary caching layer between long-term storage and readers. The prefetch mechanism acts as a mediator that asynchronously retrieves data from long-term storage and stores it in memory cache. Readers then read from this intermediary cache rather than directly from long-term storage, ensuring data accuracy while eliminating the throughput bottleneck caused by synchronous waits.
3Loss of energy
If tiered storage layout is implemented, then cost effectiveness and parallelism are improved, but reading efficiency from long-term storage deteriorates
Solution Approach 1:
The prefetch mechanism performs preliminary actions by proactively reading data from long-term storage into memory cache before actual read operations occur. This preliminary prefetching eliminates the inefficiency of on-demand synchronous reads from tiered storage, maintaining the cost effectiveness and parallelism benefits of tiered architecture while dramatically improving reading efficiency.
4Productivity
If prefetch reads are performed for all read patterns, then throughput is improved, but resource waste increases for random read behaviors
Solution Approach 1:
The system applies dynamic adaptation by monitoring read patterns and adjusting prefetch behavior accordingly. For sequential read patterns, aggressive prefetching is enabled to maximize throughput. For random read patterns, prefetching is reduced or disabled to avoid resource waste. This dynamic adjustment optimizes the balance between throughput improvement and resource consumption based on actual workload characteristics.
Data Source
AI summary
Disclosed systems and methods employ a data prefetch mechanism for tiered streaming storage systems. Disclosed features improve performance and efficiency of batch reads, i.e., read operations that require data imported from a long-term storage service. In at least some embodiments, disclosed systems and methods execute asynchronous, parallel prefetch reads from long-term storage while a reader is performing batch reads. The prefetched data may correspond to the next data required by the reader and, if so, the reader can perform the next read operation without incurring the latency associated with a synchronous read from long term storage. Disclosed systems and methods thereby beneficially improve throughput for streaming batch readers.