When we schedule a failover, broadcast a PONG to the slaves.
The other slaves that plan to get elected will do the same too, this way
it is likely that every slave will have a good picture of its own rank.
Note that this is N*N messages where N is the number of slaves for the
failing master, however usually even large clusters have many master
nodes but a limited number of replicas per node, so this is harmless.
When we schedule a failover, broadcast a PONG to the slaves.
The other slaves that plan to get elected will do the same too, this way
it is likely that every slave will have a good picture of its own rank.
Note that this is N*N messages where N is the number of slaves for the
failing master, however usually even large clusters have many master
nodes but a limited number of replicas per node, so this is harmless.
Note that when we compute the initial delay, there are probably still
more up to date information to receive from slaves with new offsets, so
the delay is recomputed when new data is available.
Note that when we compute the initial delay, there are probably still
more up to date information to receive from slaves with new offsets, so
the delay is recomputed when new data is available.
Return the number of slaves for the same master having a better
replication offset of the current slave, that is, the slave "rank" used
to pick a delay before the request for election.
Return the number of slaves for the same master having a better
replication offset of the current slave, that is, the slave "rank" used
to pick a delay before the request for election.
Accessing to the 'myself' node, the node representing the currently
running instance, is handy without the need to type
server.cluster->myself every time.
Accessing to the 'myself' node, the node representing the currently
running instance, is handy without the need to type
server.cluster->myself every time.
The two fields are used in order to remember the latest known
replication offset and the time we received it from other slave nodes.
This will be used by slaves in order to start the election procedure
with a delay that is proportional to the rank of the slave among the
other slaves for this master, when sorted for replication offset.
Usually this allows the slave with the most updated offset to win the
election and replace the failing master in the cluster.
The two fields are used in order to remember the latest known
replication offset and the time we received it from other slave nodes.
This will be used by slaves in order to start the election procedure
with a delay that is proportional to the rank of the slave among the
other slaves for this master, when sorted for replication offset.
Usually this allows the slave with the most updated offset to win the
election and replace the failing master in the cluster.
Incremental flushing in rio.c is only used to avoid huge kernel buffers
synched to slow disks creating big latency spikes, so this fix has no
durability implications, however it is certainly more correct to make
sure that the FILE buffers are flushed to the kernel before calling
fsync on the file descriptor.
Thanks to Li Shao Kai for reporting this issue in the Redis mailing
list.
Incremental flushing in rio.c is only used to avoid huge kernel buffers
synched to slow disks creating big latency spikes, so this fix has no
durability implications, however it is certainly more correct to make
sure that the FILE buffers are flushed to the kernel before calling
fsync on the file descriptor.
Thanks to Li Shao Kai for reporting this issue in the Redis mailing
list.
One of the simple heuristics used by Redis Cluster in order to avoid
losing data in the typical failure modes created by the asynchronous
replication with the slaves (a master is unable, when accepting a
write, to immediately tell if it should be really accepted or refused
because of a configuration change), is to wait some time before to
rejoin the cluster after being partitioned away from the majority of
instances.
A similar condition happens when a master is restarted. It does not know
if it was already failed over, nor if all the clients have already an
updated configuration about the cluster map, so it is possible that
clients will try to write to stale masters that were restarted.
In a similar way this commit changes masters behavior so they wait
2000 milliseconds before accepting writes after a reboot. There is
nothing special about 2 seconds if not to be a value supposedly larger
a few orders of magnitude compared to the cluster bus communication
latencies.
One of the simple heuristics used by Redis Cluster in order to avoid
losing data in the typical failure modes created by the asynchronous
replication with the slaves (a master is unable, when accepting a
write, to immediately tell if it should be really accepted or refused
because of a configuration change), is to wait some time before to
rejoin the cluster after being partitioned away from the majority of
instances.
A similar condition happens when a master is restarted. It does not know
if it was already failed over, nor if all the clients have already an
updated configuration about the cluster map, so it is possible that
clients will try to write to stale masters that were restarted.
In a similar way this commit changes masters behavior so they wait
2000 milliseconds before accepting writes after a reboot. There is
nothing special about 2 seconds if not to be a value supposedly larger
a few orders of magnitude compared to the cluster bus communication
latencies.
