sendApp accesses the storage several times. Perviously, we
assume that the storage will not be modified during the read
opeartions. The assumption is not true since the storage can
be compacted between the read operations. If a compaction
causes a read entries error, we should not painc. Instead, we
can simply retry the sendApp logic until succeed.
ForceGosched() performs bad when GOMAXPROCS>1. When GOMAXPROCS=1, it
could promise that other goroutines run long enough
because it always yield the processor to other goroutines. But it cannot
yield processor to goroutine running on other processors. So when
GOMAXPROCS>1, the yield may finish when goroutine on the other
processor just runs for little time.
Here is a test to confirm the case:
```
package main
import (
"fmt"
"runtime"
"testing"
)
func ForceGosched() {
// possibility enough to sched up to 10 go routines.
for i := 0; i < 10000; i++ {
runtime.Gosched()
}
}
var d int
func loop(c chan struct{}) {
for {
select {
case <-c:
for i := 0; i < 1000; i++ {
fmt.Sprintf("come to time %d", i)
}
d++
}
}
}
func TestLoop(t *testing.T) {
c := make(chan struct{}, 1)
go loop(c)
c <- struct{}{}
ForceGosched()
if d != 1 {
t.Fatal("d is not incremented")
}
}
```
`go test -v -race` runs well, but `GOMAXPROCS=2 go test -v -race` fails.
Change the functionality to waiting for schedule to happen.
The commit > unstable might not true for follower. The leader only need
to ensure the entry is stored on the majority of nodes to commit an
entry. So the minority of the cluster might receive commit > unstable
append request. This is normal.
raft node should set initial prev hard state to empty.
Or it will not send the first hard coded state to application
until the state changes again.
This commit fixs the issue. It introduce a small overhead, that
the same tate might send to application twice when restarting.
But this is fine.
etcd now compact raft storage asynchronously, and append entry to raft
storage may happen at the same time. Add the lock to fix the bug that
the entries saved in storage may be organized in a wrong way.
Each progress has a inflighs sliding window. When the progress
is in replicate state, inflights will control the sending speed
of the leader.
The leader can have at most maxInflight number of inflight
messages for each replicate progress. Receving a appResp moves
forward the sliding window. Heartbeat response free one
slot if the window is full.
limit the max size of entries sent per message.
Lower the cost at probing state as we limit the size per message;
lower the penalty when aggressively decrease to a too low next.
