Cache replicated entries & don't block main task w/ replication #88
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With this change, we are also caching entries which come from the leader replication protocol. As entries come in, we append them to the log and then cache the entry. When it is safe to apply entries to the state machine, we will take them directly from the in-memory cache instead of going to disk. Moreover, and most importantly, we are not longer blocking the AppendEntries RPC handler with the logic of the state machine replication workflow. There is a small amount of async task juggling to ensure that we don't run into situations where we would have two writers attempting to write to the state machine at the same time. This is easily avoided in our algorithm. closes #12 closes #76
thedodd
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@MarinPostma & @sunli829 I was wondering if you two would be interested in reviewing this PR. Pretty happy with how simple this turned out to be. There were some complexities to think through to ensure that we don't have any Raft "safety" violations as we transition from follower to leader, as cluster leadership changes, and to ensure the cache can be trusted. Fortunately, all quite simple at the end of the day. |
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Hello @thedodd ! That was fast! I didn't know about |
The log index provided to the log compaction interface was a bit misleading. When performing log compaction, the compaction can only cover the breadth of the log up to the last applied log (obvs) and under write load, this value may change quickly. As such, the expectations of the log compaction interface have been refined and clarified. Now, the only expectation is that the storage implementation will export/checkpoint/snapshot its state machine, and then use the value of that export's last applied log as the metadata indicating the breadth of the log covered by the snapshot.
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closes #12
closes #76
closes #87