In this commit, we begin to queue any active syncers until the initial
historical sync has completed. We do this to ensure we can properly
handle any new channel updates at tip. This is required for fresh nodes
that are syncing the channel graph for the first time. If we begin
accepting updates at tip while the initial historical sync is still
ongoing, then we risk not processing certain updates since we've yet to
learn of the channels themselves.
In this commit, we add logic to handle a peer with whom we're performing
an initial historical sync disconnecting. This is required to ensure we
get as much of the graph as possible when starting a fresh node. It will
also serve useful to ensure we do not get stalled once we prevent active
GossipSyncers from starting until the initial historical sync has
completed.
Now that the roundRobinHandler is no longer present, this commit aims to
clean up and simplify some of the logic surrounding initializing/tearing
down new/stale GossipSyncers from the SyncManager. Along the way, we
also synchronize these calls with the syncerHandler, which will serve
useful in future work that allows us to recovery from initial historical
sync disconnections.
Since ActiveSync GossipSyncers no longer synchronize our state with the
remote peers, none of the logic surrounding the round-robin is required
within the SyncManager.
Assuming a graph size of 50,000 channels, an interval of 20 minutes
would cause nodes to consume about 600MB per month in bandwidth doing
these routine historical sync spot checks. In this commit, we increase
to one hour, which consumes about 300MB per month.
This commit reduces the number of channels a syncer will request from
the remote node in a single QueryShortChanIDs message. The current size
is derived from the chunkSize, which is meant to signal the maximum
number of short chan ids that can fit in a single ReplyChannelRange
message. For EncodingSortedPlain, this number is 8000, and we use the
same number to dictate the size of the batch from the remote peer.
We modify this by introducing a separately configurable batchSize, so
that both can be tuned independently. The value is chosen to reduce the
amount of buffering the remote party will perform, only requiring them
queue 500 responses, as opposed to 8000. In turn, this reduces larges
spikes in allocation on the remote node at the expense of a few extra
round trips for the control messages. However, will be negligible since
the control messages are much smaller than the messages being returned.
In this commit, we address a bug where we'd attempt to replace the
stale active syncer when it transitioned to a passive syncer. This
replacement logic is only intended to happen when the active syncer
disconnects, as rotateActiveSyncerCandidate chooses and queues its own
replacement.
In this commit, we introduce a new subsystem for the gossiper: the
SyncManager. This subsystem is a major overhaul on the way the daemon
performs the graph query sync state machine with peers.
Along with this subsystem, we also introduce the concept of an active
syncer. An active syncer is simply a GossipSyncer currently operating
under an ActiveSync sync type. Before this commit, all GossipSyncer's
would act as active syncers, which means that we were receiving new
graph updates from all of them. This isn't necessary, as it greatly
increases bandwidth usage as the network grows. The SyncManager changes
this by requiring a specific number of active syncers. Once we reach
this specified number, any future peers will have a GossipSyncer with a
PassiveSync sync type.
It is responsible for three main things:
1. Choosing different peers randomly to receive graph updates from to
ensure we don't only receive them from the same set of peers.
2. Choosing different peers to force a historical sync with to ensure we
have as much of the public network as possible. The first syncer
registered with the manager will also attempt a historical sync.
3. Managing an in-order queue of active syncers where the next cannot be
started until the current one has completed its state machine to ensure
they don't overlap and request the same set of channels, which
significantly reduces bandwidth usage and addresses a number of issues.
