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Fabian Reinartz 2017-07-12 13:49:23 +02:00
parent dba7586671
commit 6861b3d03d
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storage/remote/queue_manager.go
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// Copyright 2013 The Prometheus Authors
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
package remote
import (
"math"
"sync"
"time"
"golang.org/x/time/rate"
"github.com/prometheus/client_golang/prometheus"
"github.com/prometheus/common/log"
"github.com/prometheus/common/model"
"github.com/prometheus/prometheus/config"
"github.com/prometheus/prometheus/relabel"
)
// String constants for instrumentation.
const (
namespace = "prometheus"
subsystem = "remote_storage"
queue = "queue"
// We track samples in/out and how long pushes take using an Exponentially
// Weighted Moving Average.
ewmaWeight = 0.2
shardUpdateDuration = 10 * time.Second
// Allow 30% too many shards before scaling down.
shardToleranceFraction = 0.3
// Limit to 1 log event every 10s
logRateLimit = 0.1
logBurst = 10
)
var (
succeededSamplesTotal = prometheus.NewCounterVec(
prometheus.CounterOpts{
Namespace: namespace,
Subsystem: subsystem,
Name: "succeeded_samples_total",
Help: "Total number of samples successfully sent to remote storage.",
},
[]string{queue},
)
failedSamplesTotal = prometheus.NewCounterVec(
prometheus.CounterOpts{
Namespace: namespace,
Subsystem: subsystem,
Name: "failed_samples_total",
Help: "Total number of samples which failed on send to remote storage.",
},
[]string{queue},
)
droppedSamplesTotal = prometheus.NewCounterVec(
prometheus.CounterOpts{
Namespace: namespace,
Subsystem: subsystem,
Name: "dropped_samples_total",
Help: "Total number of samples which were dropped due to the queue being full.",
},
[]string{queue},
)
sentBatchDuration = prometheus.NewHistogramVec(
prometheus.HistogramOpts{
Namespace: namespace,
Subsystem: subsystem,
Name: "sent_batch_duration_seconds",
Help: "Duration of sample batch send calls to the remote storage.",
Buckets: prometheus.DefBuckets,
},
[]string{queue},
)
queueLength = prometheus.NewGaugeVec(
prometheus.GaugeOpts{
Namespace: namespace,
Subsystem: subsystem,
Name: "queue_length",
Help: "The number of processed samples queued to be sent to the remote storage.",
},
[]string{queue},
)
queueCapacity = prometheus.NewGaugeVec(
prometheus.GaugeOpts{
Namespace: namespace,
Subsystem: subsystem,
Name: "queue_capacity",
Help: "The capacity of the queue of samples to be sent to the remote storage.",
},
[]string{queue},
)
numShards = prometheus.NewGaugeVec(
prometheus.GaugeOpts{
Namespace: namespace,
Subsystem: subsystem,
Name: "shards",
Help: "The number of shards used for parallel sending to the remote storage.",
},
[]string{queue},
)
)
func init() {
prometheus.MustRegister(succeededSamplesTotal)
prometheus.MustRegister(failedSamplesTotal)
prometheus.MustRegister(droppedSamplesTotal)
prometheus.MustRegister(sentBatchDuration)
prometheus.MustRegister(queueLength)
prometheus.MustRegister(queueCapacity)
prometheus.MustRegister(numShards)
}
// QueueManagerConfig is the configuration for the queue used to write to remote
// storage.
type QueueManagerConfig struct {
// Number of samples to buffer per shard before we start dropping them.
QueueCapacity int
// Max number of shards, i.e. amount of concurrency.
MaxShards int
// Maximum number of samples per send.
MaxSamplesPerSend int
// Maximum time sample will wait in buffer.
BatchSendDeadline time.Duration
// Max number of times to retry a batch on recoverable errors.
MaxRetries int
// On recoverable errors, backoff exponentially.
MinBackoff time.Duration
MaxBackoff time.Duration
}
// defaultQueueManagerConfig is the default remote queue configuration.
var defaultQueueManagerConfig = QueueManagerConfig{
// With a maximum of 1000 shards, assuming an average of 100ms remote write
// time and 100 samples per batch, we will be able to push 1M samples/s.
MaxShards: 1000,
MaxSamplesPerSend: 100,
// By default, buffer 1000 batches, which at 100ms per batch is 1:40mins. At
// 1000 shards, this will buffer 100M samples total.
QueueCapacity: 100 * 1000,
BatchSendDeadline: 5 * time.Second,
// Max number of times to retry a batch on recoverable errors.
MaxRetries: 10,
MinBackoff: 30 * time.Millisecond,
MaxBackoff: 100 * time.Millisecond,
}
// StorageClient defines an interface for sending a batch of samples to an
// external timeseries database.
type StorageClient interface {
// Store stores the given samples in the remote storage.
Store(model.Samples) error
// Name identifies the remote storage implementation.
Name() string
}
// QueueManager manages a queue of samples to be sent to the Storage
// indicated by the provided StorageClient.
type QueueManager struct {
cfg QueueManagerConfig
externalLabels model.LabelSet
relabelConfigs []*config.RelabelConfig
client StorageClient
queueName string
logLimiter *rate.Limiter
shardsMtx sync.Mutex
shards *shards
numShards int
reshardChan chan int
quit chan struct{}
wg sync.WaitGroup
samplesIn, samplesOut, samplesOutDuration *ewmaRate
integralAccumulator float64
}
// NewQueueManager builds a new QueueManager.
func NewQueueManager(cfg QueueManagerConfig, externalLabels model.LabelSet, relabelConfigs []*config.RelabelConfig, client StorageClient) *QueueManager {
t := &QueueManager{
cfg: cfg,
externalLabels: externalLabels,
relabelConfigs: relabelConfigs,
client: client,
queueName: client.Name(),
logLimiter: rate.NewLimiter(logRateLimit, logBurst),
numShards: 1,
reshardChan: make(chan int),
quit: make(chan struct{}),
samplesIn: newEWMARate(ewmaWeight, shardUpdateDuration),
samplesOut: newEWMARate(ewmaWeight, shardUpdateDuration),
samplesOutDuration: newEWMARate(ewmaWeight, shardUpdateDuration),
}
t.shards = t.newShards(t.numShards)
numShards.WithLabelValues(t.queueName).Set(float64(t.numShards))
queueCapacity.WithLabelValues(t.queueName).Set(float64(t.cfg.QueueCapacity))
return t
}
// Append queues a sample to be sent to the remote storage. It drops the
// sample on the floor if the queue is full.
// Always returns nil.
func (t *QueueManager) Append(s *model.Sample) error {
var snew model.Sample
snew = *s
snew.Metric = s.Metric.Clone()
for ln, lv := range t.externalLabels {
if _, ok := s.Metric[ln]; !ok {
snew.Metric[ln] = lv
}
}
snew.Metric = model.Metric(
relabel.Process(model.LabelSet(snew.Metric), t.relabelConfigs...))
if snew.Metric == nil {
return nil
}
t.shardsMtx.Lock()
enqueued := t.shards.enqueue(&snew)
t.shardsMtx.Unlock()
if enqueued {
queueLength.WithLabelValues(t.queueName).Inc()
} else {
droppedSamplesTotal.WithLabelValues(t.queueName).Inc()
if t.logLimiter.Allow() {
log.Warn("Remote storage queue full, discarding sample. Multiple subsequent messages of this kind may be suppressed.")
}
}
return nil
}
// NeedsThrottling implements storage.SampleAppender. It will always return
// false as a remote storage drops samples on the floor if backlogging instead
// of asking for throttling.
func (*QueueManager) NeedsThrottling() bool {
return false
}
// Start the queue manager sending samples to the remote storage.
// Does not block.
func (t *QueueManager) Start() {
t.wg.Add(2)
go t.updateShardsLoop()
go t.reshardLoop()
t.shardsMtx.Lock()
defer t.shardsMtx.Unlock()
t.shards.start()
}
// Stop stops sending samples to the remote storage and waits for pending
// sends to complete.
func (t *QueueManager) Stop() {
log.Infof("Stopping remote storage...")
close(t.quit)
t.wg.Wait()
t.shardsMtx.Lock()
defer t.shardsMtx.Unlock()
t.shards.stop()
log.Info("Remote storage stopped.")
}
func (t *QueueManager) updateShardsLoop() {
defer t.wg.Done()
ticker := time.Tick(shardUpdateDuration)
for {
select {
case <-ticker:
t.calculateDesiredShards()
case <-t.quit:
return
}
}
}
func (t *QueueManager) calculateDesiredShards() {
t.samplesIn.tick()
t.samplesOut.tick()
t.samplesOutDuration.tick()
// We use the number of incoming samples as a prediction of how much work we
// will need to do next iteration. We add to this any pending samples
// (received - sent) so we can catch up with any backlog. We use the average
// outgoing batch latency to work out how many shards we need.
var (
samplesIn = t.samplesIn.rate()
samplesOut = t.samplesOut.rate()
samplesPending = samplesIn - samplesOut
samplesOutDuration = t.samplesOutDuration.rate()
)
// We use an integral accumulator, like in a PID, to help dampen oscillation.
t.integralAccumulator = t.integralAccumulator + (samplesPending * 0.1)
if samplesOut <= 0 {
return
}
var (
timePerSample = samplesOutDuration / samplesOut
desiredShards = (timePerSample * (samplesIn + samplesPending + t.integralAccumulator)) / float64(time.Second)
)
log.Debugf("QueueManager.calculateDesiredShards samplesIn=%f, samplesOut=%f, samplesPending=%f, desiredShards=%f",
samplesIn, samplesOut, samplesPending, desiredShards)
// Changes in the number of shards must be greater than shardToleranceFraction.
var (
lowerBound = float64(t.numShards) * (1. - shardToleranceFraction)
upperBound = float64(t.numShards) * (1. + shardToleranceFraction)
)
log.Debugf("QueueManager.updateShardsLoop %f <= %f <= %f", lowerBound, desiredShards, upperBound)
if lowerBound <= desiredShards && desiredShards <= upperBound {
return
}
numShards := int(math.Ceil(desiredShards))
if numShards > t.cfg.MaxShards {
numShards = t.cfg.MaxShards
}
if numShards == t.numShards {
return
}
// Resharding can take some time, and we want this loop
// to stay close to shardUpdateDuration.
select {
case t.reshardChan <- numShards:
log.Infof("Remote storage resharding from %d to %d shards.", t.numShards, numShards)
t.numShards = numShards
default:
log.Infof("Currently resharding, skipping.")
}
}
func (t *QueueManager) reshardLoop() {
defer t.wg.Done()
for {
select {
case numShards := <-t.reshardChan:
t.reshard(numShards)
case <-t.quit:
return
}
}
}
func (t *QueueManager) reshard(n int) {
numShards.WithLabelValues(t.queueName).Set(float64(n))
t.shardsMtx.Lock()
newShards := t.newShards(n)
oldShards := t.shards
t.shards = newShards
t.shardsMtx.Unlock()
oldShards.stop()
// We start the newShards after we have stopped (the therefore completely
// flushed) the oldShards, to guarantee we only every deliver samples in
// order.
newShards.start()
}
type shards struct {
qm *QueueManager
queues []chan *model.Sample
done chan struct{}
wg sync.WaitGroup
}
func (t *QueueManager) newShards(numShards int) *shards {
queues := make([]chan *model.Sample, numShards)
for i := 0; i < numShards; i++ {
queues[i] = make(chan *model.Sample, t.cfg.QueueCapacity)
}
s := &shards{
qm: t,
queues: queues,
done: make(chan struct{}),
}
s.wg.Add(numShards)
return s
}
func (s *shards) len() int {
return len(s.queues)
}
func (s *shards) start() {
for i := 0; i < len(s.queues); i++ {
go s.runShard(i)
}
}
func (s *shards) stop() {
for _, shard := range s.queues {
close(shard)
}
s.wg.Wait()
}
func (s *shards) enqueue(sample *model.Sample) bool {
s.qm.samplesIn.incr(1)
fp := sample.Metric.FastFingerprint()
shard := uint64(fp) % uint64(len(s.queues))
select {
case s.queues[shard] <- sample:
return true
default:
return false
}
}
func (s *shards) runShard(i int) {
defer s.wg.Done()
queue := s.queues[i]
// Send batches of at most MaxSamplesPerSend samples to the remote storage.
// If we have fewer samples than that, flush them out after a deadline
// anyways.
pendingSamples := model.Samples{}
for {
select {
case sample, ok := <-queue:
if !ok {
if len(pendingSamples) > 0 {
log.Debugf("Flushing %d samples to remote storage...", len(pendingSamples))
s.sendSamples(pendingSamples)
log.Debugf("Done flushing.")
}
return
}
queueLength.WithLabelValues(s.qm.queueName).Dec()
pendingSamples = append(pendingSamples, sample)
for len(pendingSamples) >= s.qm.cfg.MaxSamplesPerSend {
s.sendSamples(pendingSamples[:s.qm.cfg.MaxSamplesPerSend])
pendingSamples = pendingSamples[s.qm.cfg.MaxSamplesPerSend:]
}
case <-time.After(s.qm.cfg.BatchSendDeadline):
if len(pendingSamples) > 0 {
s.sendSamples(pendingSamples)
pendingSamples = pendingSamples[:0]
}
}
}
}
func (s *shards) sendSamples(samples model.Samples) {
begin := time.Now()
s.sendSamplesWithBackoff(samples)
// These counters are used to calculate the dynamic sharding, and as such
// should be maintained irrespective of success or failure.
s.qm.samplesOut.incr(int64(len(samples)))
s.qm.samplesOutDuration.incr(int64(time.Since(begin)))
}
// sendSamples to the remote storage with backoff for recoverable errors.
func (s *shards) sendSamplesWithBackoff(samples model.Samples) {
backoff := s.qm.cfg.MinBackoff
for retries := s.qm.cfg.MaxRetries; retries > 0; retries-- {
begin := time.Now()
err := s.qm.client.Store(samples)
sentBatchDuration.WithLabelValues(s.qm.queueName).Observe(time.Since(begin).Seconds())
if err == nil {
succeededSamplesTotal.WithLabelValues(s.qm.queueName).Add(float64(len(samples)))
return
}
log.Warnf("Error sending %d samples to remote storage: %s", len(samples), err)
if _, ok := err.(recoverableError); !ok {
break
}
time.Sleep(backoff)
backoff = backoff * 2
if backoff > s.qm.cfg.MaxBackoff {
backoff = s.qm.cfg.MaxBackoff
}
}
failedSamplesTotal.WithLabelValues(s.qm.queueName).Add(float64(len(samples)))
}