Erasure-Coded Shard Retrieval for Read Tail Latency Reduction
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Solution Overview
Problem
Data storage systems using erasure coding face challenges in reducing read tail latency, which occurs when retrieving the last erasure coded shard, leading to increased overall read times and potential service level agreement (SLA) violations.
Innovation Solution
Implementing a shard calibration process that selects a subset of erasure coded shards or adjusts the number of shards to retrieve based on collective latency indicators and latency limits, allowing for earlier data reconstruction and reducing read tail latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all erasure coded shards are retrieved to ensure data reconstruction, then data reliability is maintained, but read tail latency increases
Solution Approach 1:
The patent applies partial action by retrieving only a subset of erasure coded shards (k shards out of n total shards) rather than all shards. This allows data reconstruction to proceed with sufficient redundancy while avoiding the latency penalty of waiting for all shards, thus resolving the contradiction between reliability and read tail latency
Solution Approach 2:
The system performs preliminary calibration to determine optimal shard subset sizes and compositions before actual data retrieval operations. This pre-computed knowledge enables faster read operations by avoiding real-time decisions about which shards to retrieve, reducing read tail latency while maintaining reliability
2Ease of operation
If a fixed number of erasure coded shards is retrieved, then system operation is simplified, but latency limits may be violated
Solution Approach 1:
The patent implements dynamic shard retrieval by adjusting the number of shards to retrieve based on calibrated latency characteristics and current system conditions. Rather than using a fixed number, the system adaptively determines optimal shard counts to meet latency limits while maintaining operational simplicity through automated calibration
Solution Approach 2:
The system employs feedback mechanisms through calibration processes that measure actual read latencies and use this information to adjust future shard retrieval strategies. This closed-loop approach ensures latency limits are met while maintaining ease of operation through automated adjustment rather than manual tuning
Data Source
AI summary
A collective latency indicator is determined that is associated with a latency in retrieving multiple erasure coded shards generated from an erasure coding on initial data. The collective latency indicator is compared to a latency limit, and a number of erasure coded shards to retrieve is adjusted based on the comparison of the collective latency indicator to the latency limit.