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feat(job): implement Redis Set storage for SyncPeersJob to avoid big key issues #4654 #4668
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When the number of peers becomes excessively large, wouldn't this approach actually place a greater strain on redis?
With 100,000 Peers, this implies that the
redis.sAdd()method must be invoked 100,000 times. Although this eliminates the issue of a single Key holding an excessively large volume of data, it introduces a new problem: executingredis.sAdd()100,000 times incurs significant overhead—potentially resulting in a situation even worse than the original one.Regardless of how
redis.SAdd()is invoked, it alters only the write method, not the resulting data structure. Whether you write 100,000 entries in a single operation or perform 100,000 separate writes of one entry each, the outcome remains the same: a single Set containing 100,000 members.In a separate PR(#4654), the implementation utilizes sharding to limit the number of Peers associated with any single Key. This method resolves the issue of excessive data storage under a single Key without incurring the overhead of repeated
redis.sAdd()calls. I believe this implementation approach is superior; what are your thoughts?To summarize, I think the correct approach is to attempt to shard the data using different keys, rather than writing data to the same key in small, frequent increments.