prometheus/storage/remote/queue_manager.go
Chris Marchbanks dfad1da296
Remove duplicate metrics in QueueManager
Right now any new metrics added for remote write need to be added to
both the QueueManager struct, and the queueManagerMetrics struct.
Instead, use the queueManagerMetrics struct directly from QueueManager.

The newQueueManagerMetrics constructor will now create the metrics for a
specific queue with name and endpoint pre-populated, and a new copy of
the struct will be created specifically for each queue.

This also fixes a bug where prometheus_remote_storage_sent_bytes_total
is not being unregistered after a queue is changed.

Signed-off-by: Chris Marchbanks <csmarchbanks@gmail.com>
2020-05-05 14:13:59 -06:00

913 lines
27 KiB
Go

// 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 (
"context"
"math"
"strconv"
"sync"
"sync/atomic"
"time"
"github.com/go-kit/kit/log"
"github.com/go-kit/kit/log/level"
"github.com/gogo/protobuf/proto"
"github.com/golang/snappy"
"github.com/prometheus/client_golang/prometheus"
"github.com/prometheus/prometheus/config"
"github.com/prometheus/prometheus/pkg/labels"
"github.com/prometheus/prometheus/pkg/relabel"
"github.com/prometheus/prometheus/prompb"
"github.com/prometheus/prometheus/tsdb/record"
"github.com/prometheus/prometheus/tsdb/wal"
)
const (
// 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
)
type queueManagerMetrics struct {
reg prometheus.Registerer
succeededSamplesTotal prometheus.Counter
failedSamplesTotal prometheus.Counter
retriedSamplesTotal prometheus.Counter
droppedSamplesTotal prometheus.Counter
enqueueRetriesTotal prometheus.Counter
sentBatchDuration prometheus.Histogram
highestSentTimestamp *maxGauge
pendingSamples prometheus.Gauge
shardCapacity prometheus.Gauge
numShards prometheus.Gauge
maxNumShards prometheus.Gauge
minNumShards prometheus.Gauge
desiredNumShards prometheus.Gauge
bytesSent prometheus.Counter
}
func newQueueManagerMetrics(r prometheus.Registerer, rn, e string) *queueManagerMetrics {
m := &queueManagerMetrics{
reg: r,
}
constLabels := prometheus.Labels{
remoteName: rn,
endpoint: e,
}
m.succeededSamplesTotal = prometheus.NewCounter(prometheus.CounterOpts{
Namespace: namespace,
Subsystem: subsystem,
Name: "succeeded_samples_total",
Help: "Total number of samples successfully sent to remote storage.",
ConstLabels: constLabels,
})
m.failedSamplesTotal = prometheus.NewCounter(prometheus.CounterOpts{
Namespace: namespace,
Subsystem: subsystem,
Name: "failed_samples_total",
Help: "Total number of samples which failed on send to remote storage, non-recoverable errors.",
ConstLabels: constLabels,
})
m.retriedSamplesTotal = prometheus.NewCounter(prometheus.CounterOpts{
Namespace: namespace,
Subsystem: subsystem,
Name: "retried_samples_total",
Help: "Total number of samples which failed on send to remote storage but were retried because the send error was recoverable.",
ConstLabels: constLabels,
})
m.droppedSamplesTotal = prometheus.NewCounter(prometheus.CounterOpts{
Namespace: namespace,
Subsystem: subsystem,
Name: "dropped_samples_total",
Help: "Total number of samples which were dropped after being read from the WAL before being sent via remote write.",
ConstLabels: constLabels,
})
m.enqueueRetriesTotal = prometheus.NewCounter(prometheus.CounterOpts{
Namespace: namespace,
Subsystem: subsystem,
Name: "enqueue_retries_total",
Help: "Total number of times enqueue has failed because a shards queue was full.",
ConstLabels: constLabels,
})
m.sentBatchDuration = prometheus.NewHistogram(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,
ConstLabels: constLabels,
})
m.highestSentTimestamp = &maxGauge{
Gauge: prometheus.NewGauge(prometheus.GaugeOpts{
Namespace: namespace,
Subsystem: subsystem,
Name: "queue_highest_sent_timestamp_seconds",
Help: "Timestamp from a WAL sample, the highest timestamp successfully sent by this queue, in seconds since epoch.",
ConstLabels: constLabels,
}),
}
m.pendingSamples = prometheus.NewGauge(prometheus.GaugeOpts{
Namespace: namespace,
Subsystem: subsystem,
Name: "pending_samples",
Help: "The number of samples pending in the queues shards to be sent to the remote storage.",
ConstLabels: constLabels,
})
m.shardCapacity = prometheus.NewGauge(prometheus.GaugeOpts{
Namespace: namespace,
Subsystem: subsystem,
Name: "shard_capacity",
Help: "The capacity of each shard of the queue used for parallel sending to the remote storage.",
ConstLabels: constLabels,
})
m.numShards = prometheus.NewGauge(prometheus.GaugeOpts{
Namespace: namespace,
Subsystem: subsystem,
Name: "shards",
Help: "The number of shards used for parallel sending to the remote storage.",
ConstLabels: constLabels,
})
m.maxNumShards = prometheus.NewGauge(prometheus.GaugeOpts{
Namespace: namespace,
Subsystem: subsystem,
Name: "shards_max",
Help: "The maximum number of shards that the queue is allowed to run.",
ConstLabels: constLabels,
})
m.minNumShards = prometheus.NewGauge(prometheus.GaugeOpts{
Namespace: namespace,
Subsystem: subsystem,
Name: "shards_min",
Help: "The minimum number of shards that the queue is allowed to run.",
ConstLabels: constLabels,
})
m.desiredNumShards = prometheus.NewGauge(prometheus.GaugeOpts{
Namespace: namespace,
Subsystem: subsystem,
Name: "shards_desired",
Help: "The number of shards that the queues shard calculation wants to run based on the rate of samples in vs. samples out.",
ConstLabels: constLabels,
})
m.bytesSent = prometheus.NewCounter(prometheus.CounterOpts{
Namespace: namespace,
Subsystem: subsystem,
Name: "sent_bytes_total",
Help: "The total number of bytes sent by the queue.",
ConstLabels: constLabels,
})
if r != nil {
r.MustRegister(
m.succeededSamplesTotal,
m.failedSamplesTotal,
m.retriedSamplesTotal,
m.droppedSamplesTotal,
m.enqueueRetriesTotal,
m.sentBatchDuration,
m.highestSentTimestamp,
m.pendingSamples,
m.shardCapacity,
m.numShards,
m.maxNumShards,
m.minNumShards,
m.desiredNumShards,
m.bytesSent,
)
}
return m
}
func (m *queueManagerMetrics) unregister() {
if m.reg != nil {
m.reg.Unregister(m.succeededSamplesTotal)
m.reg.Unregister(m.failedSamplesTotal)
m.reg.Unregister(m.retriedSamplesTotal)
m.reg.Unregister(m.droppedSamplesTotal)
m.reg.Unregister(m.enqueueRetriesTotal)
m.reg.Unregister(m.sentBatchDuration)
m.reg.Unregister(m.highestSentTimestamp)
m.reg.Unregister(m.pendingSamples)
m.reg.Unregister(m.shardCapacity)
m.reg.Unregister(m.numShards)
m.reg.Unregister(m.maxNumShards)
m.reg.Unregister(m.minNumShards)
m.reg.Unregister(m.desiredNumShards)
m.reg.Unregister(m.bytesSent)
}
}
// 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(context.Context, []byte) error
// Name uniquely identifies the remote storage.
Name() string
// Endpoint is the remote read or write endpoint for the storage client.
Endpoint() string
}
// QueueManager manages a queue of samples to be sent to the Storage
// indicated by the provided StorageClient. Implements writeTo interface
// used by WAL Watcher.
type QueueManager struct {
// https://golang.org/pkg/sync/atomic/#pkg-note-BUG
lastSendTimestamp int64
logger log.Logger
flushDeadline time.Duration
cfg config.QueueConfig
externalLabels labels.Labels
relabelConfigs []*relabel.Config
watcher *wal.Watcher
clientMtx sync.RWMutex
storeClient StorageClient
seriesMtx sync.Mutex
seriesLabels map[uint64]labels.Labels
seriesSegmentIndexes map[uint64]int
droppedSeries map[uint64]struct{}
shards *shards
numShards int
reshardChan chan int
quit chan struct{}
wg sync.WaitGroup
samplesIn, samplesDropped, samplesOut, samplesOutDuration *ewmaRate
metrics *queueManagerMetrics
}
// NewQueueManager builds a new QueueManager.
func NewQueueManager(
metrics *queueManagerMetrics,
watcherMetrics *wal.WatcherMetrics,
readerMetrics *wal.LiveReaderMetrics,
logger log.Logger,
walDir string,
samplesIn *ewmaRate,
cfg config.QueueConfig,
externalLabels labels.Labels,
relabelConfigs []*relabel.Config,
client StorageClient,
flushDeadline time.Duration,
) *QueueManager {
if logger == nil {
logger = log.NewNopLogger()
}
logger = log.With(logger, remoteName, client.Name(), endpoint, client.Endpoint())
t := &QueueManager{
logger: logger,
flushDeadline: flushDeadline,
cfg: cfg,
externalLabels: externalLabels,
relabelConfigs: relabelConfigs,
storeClient: client,
seriesLabels: make(map[uint64]labels.Labels),
seriesSegmentIndexes: make(map[uint64]int),
droppedSeries: make(map[uint64]struct{}),
numShards: cfg.MinShards,
reshardChan: make(chan int),
quit: make(chan struct{}),
samplesIn: samplesIn,
samplesDropped: newEWMARate(ewmaWeight, shardUpdateDuration),
samplesOut: newEWMARate(ewmaWeight, shardUpdateDuration),
samplesOutDuration: newEWMARate(ewmaWeight, shardUpdateDuration),
metrics: metrics,
}
t.watcher = wal.NewWatcher(watcherMetrics, readerMetrics, logger, client.Name(), t, walDir)
t.shards = t.newShards()
return t
}
// Append queues a sample to be sent to the remote storage. Blocks until all samples are
// enqueued on their shards or a shutdown signal is received.
func (t *QueueManager) Append(samples []record.RefSample) bool {
outer:
for _, s := range samples {
t.seriesMtx.Lock()
lbls, ok := t.seriesLabels[s.Ref]
if !ok {
t.metrics.droppedSamplesTotal.Inc()
t.samplesDropped.incr(1)
if _, ok := t.droppedSeries[s.Ref]; !ok {
level.Info(t.logger).Log("msg", "Dropped sample for series that was not explicitly dropped via relabelling", "ref", s.Ref)
}
t.seriesMtx.Unlock()
continue
}
t.seriesMtx.Unlock()
// This will only loop if the queues are being resharded.
backoff := t.cfg.MinBackoff
for {
select {
case <-t.quit:
return false
default:
}
if t.shards.enqueue(s.Ref, sample{
labels: lbls,
t: s.T,
v: s.V,
}) {
continue outer
}
t.metrics.enqueueRetriesTotal.Inc()
time.Sleep(time.Duration(backoff))
backoff = backoff * 2
if backoff > t.cfg.MaxBackoff {
backoff = t.cfg.MaxBackoff
}
}
}
return true
}
// Start the queue manager sending samples to the remote storage.
// Does not block.
func (t *QueueManager) Start() {
// Initialise some metrics.
t.metrics.shardCapacity.Set(float64(t.cfg.Capacity))
t.metrics.pendingSamples.Set(0)
t.metrics.maxNumShards.Set(float64(t.cfg.MaxShards))
t.metrics.minNumShards.Set(float64(t.cfg.MinShards))
t.metrics.desiredNumShards.Set(float64(t.cfg.MinShards))
t.shards.start(t.numShards)
t.watcher.Start()
t.wg.Add(2)
go t.updateShardsLoop()
go t.reshardLoop()
}
// Stop stops sending samples to the remote storage and waits for pending
// sends to complete.
func (t *QueueManager) Stop() {
level.Info(t.logger).Log("msg", "Stopping remote storage...")
defer level.Info(t.logger).Log("msg", "Remote storage stopped.")
close(t.quit)
t.wg.Wait()
// Wait for all QueueManager routines to end before stopping shards and WAL watcher. This
// is to ensure we don't end up executing a reshard and shards.stop() at the same time, which
// causes a closed channel panic.
t.shards.stop()
t.watcher.Stop()
// On shutdown, release the strings in the labels from the intern pool.
t.seriesMtx.Lock()
for _, labels := range t.seriesLabels {
releaseLabels(labels)
}
t.seriesMtx.Unlock()
t.metrics.unregister()
}
// StoreSeries keeps track of which series we know about for lookups when sending samples to remote.
func (t *QueueManager) StoreSeries(series []record.RefSeries, index int) {
t.seriesMtx.Lock()
defer t.seriesMtx.Unlock()
for _, s := range series {
ls := processExternalLabels(s.Labels, t.externalLabels)
lbls := relabel.Process(ls, t.relabelConfigs...)
if len(lbls) == 0 {
t.droppedSeries[s.Ref] = struct{}{}
continue
}
t.seriesSegmentIndexes[s.Ref] = index
internLabels(lbls)
// We should not ever be replacing a series labels in the map, but just
// in case we do we need to ensure we do not leak the replaced interned
// strings.
if orig, ok := t.seriesLabels[s.Ref]; ok {
releaseLabels(orig)
}
t.seriesLabels[s.Ref] = lbls
}
}
// SeriesReset is used when reading a checkpoint. WAL Watcher should have
// stored series records with the checkpoints index number, so we can now
// delete any ref ID's lower than that # from the two maps.
func (t *QueueManager) SeriesReset(index int) {
t.seriesMtx.Lock()
defer t.seriesMtx.Unlock()
// Check for series that are in segments older than the checkpoint
// that were not also present in the checkpoint.
for k, v := range t.seriesSegmentIndexes {
if v < index {
delete(t.seriesSegmentIndexes, k)
releaseLabels(t.seriesLabels[k])
delete(t.seriesLabels, k)
delete(t.droppedSeries, k)
}
}
}
// SetClient updates the client used by a queue. Used when only client specific
// fields are updated to avoid restarting the queue.
func (t *QueueManager) SetClient(c StorageClient) {
t.clientMtx.Lock()
t.storeClient = c
t.clientMtx.Unlock()
}
func (t *QueueManager) client() StorageClient {
t.clientMtx.RLock()
defer t.clientMtx.RUnlock()
return t.storeClient
}
func internLabels(lbls labels.Labels) {
for i, l := range lbls {
lbls[i].Name = interner.intern(l.Name)
lbls[i].Value = interner.intern(l.Value)
}
}
func releaseLabels(ls labels.Labels) {
for _, l := range ls {
interner.release(l.Name)
interner.release(l.Value)
}
}
// processExternalLabels merges externalLabels into ls. If ls contains
// a label in externalLabels, the value in ls wins.
func processExternalLabels(ls labels.Labels, externalLabels labels.Labels) labels.Labels {
i, j, result := 0, 0, make(labels.Labels, 0, len(ls)+len(externalLabels))
for i < len(ls) && j < len(externalLabels) {
if ls[i].Name < externalLabels[j].Name {
result = append(result, labels.Label{
Name: ls[i].Name,
Value: ls[i].Value,
})
i++
} else if ls[i].Name > externalLabels[j].Name {
result = append(result, externalLabels[j])
j++
} else {
result = append(result, labels.Label{
Name: ls[i].Name,
Value: ls[i].Value,
})
i++
j++
}
}
for ; i < len(ls); i++ {
result = append(result, labels.Label{
Name: ls[i].Name,
Value: ls[i].Value,
})
}
result = append(result, externalLabels[j:]...)
return result
}
func (t *QueueManager) updateShardsLoop() {
defer t.wg.Done()
ticker := time.NewTicker(shardUpdateDuration)
defer ticker.Stop()
for {
select {
case <-ticker.C:
desiredShards := t.calculateDesiredShards()
if !t.shouldReshard(desiredShards) {
continue
}
// Resharding can take some time, and we want this loop
// to stay close to shardUpdateDuration.
select {
case t.reshardChan <- desiredShards:
level.Info(t.logger).Log("msg", "Remote storage resharding", "from", t.numShards, "to", desiredShards)
t.numShards = desiredShards
default:
level.Info(t.logger).Log("msg", "Currently resharding, skipping.")
}
case <-t.quit:
return
}
}
}
// shouldReshard returns if resharding should occur
func (t *QueueManager) shouldReshard(desiredShards int) bool {
if desiredShards == t.numShards {
return false
}
// We shouldn't reshard if Prometheus hasn't been able to send to the
// remote endpoint successfully within some period of time.
minSendTimestamp := time.Now().Add(-2 * time.Duration(t.cfg.BatchSendDeadline)).Unix()
lsts := atomic.LoadInt64(&t.lastSendTimestamp)
if lsts < minSendTimestamp {
level.Warn(t.logger).Log("msg", "Skipping resharding, last successful send was beyond threshold", "lastSendTimestamp", lsts, "minSendTimestamp", minSendTimestamp)
return false
}
return true
}
// calculateDesiredShards returns the number of desired shards, which will be
// the current QueueManager.numShards if resharding should not occur for reasons
// outlined in this functions implementation. It is up to the caller to reshard, or not,
// based on the return value.
func (t *QueueManager) calculateDesiredShards() int {
t.samplesOut.tick()
t.samplesDropped.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 - send) so we can catch up with any backlog. We use the average
// outgoing batch latency to work out how many shards we need.
var (
samplesInRate = t.samplesIn.rate()
samplesOutRate = t.samplesOut.rate()
samplesKeptRatio = samplesOutRate / (t.samplesDropped.rate() + samplesOutRate)
samplesOutDuration = t.samplesOutDuration.rate() / float64(time.Second)
samplesPendingRate = samplesInRate*samplesKeptRatio - samplesOutRate
highestSent = t.metrics.highestSentTimestamp.Get()
highestRecv = highestTimestamp.Get()
delay = highestRecv - highestSent
samplesPending = delay * samplesInRate * samplesKeptRatio
)
if samplesOutRate <= 0 {
return t.numShards
}
// When behind we will try to catch up on a proporation of samples per tick.
// This works similarly to an integral accumulator in that pending samples
// is the result of the error integral.
const integralGain = 0.1 / float64(shardUpdateDuration/time.Second)
var (
timePerSample = samplesOutDuration / samplesOutRate
desiredShards = timePerSample * (samplesInRate*samplesKeptRatio + integralGain*samplesPending)
)
t.metrics.desiredNumShards.Set(desiredShards)
level.Debug(t.logger).Log("msg", "QueueManager.calculateDesiredShards",
"samplesInRate", samplesInRate,
"samplesOutRate", samplesOutRate,
"samplesKeptRatio", samplesKeptRatio,
"samplesPendingRate", samplesPendingRate,
"samplesPending", samplesPending,
"samplesOutDuration", samplesOutDuration,
"timePerSample", timePerSample,
"desiredShards", desiredShards,
"highestSent", highestSent,
"highestRecv", highestRecv,
)
// Changes in the number of shards must be greater than shardToleranceFraction.
var (
lowerBound = float64(t.numShards) * (1. - shardToleranceFraction)
upperBound = float64(t.numShards) * (1. + shardToleranceFraction)
)
level.Debug(t.logger).Log("msg", "QueueManager.updateShardsLoop",
"lowerBound", lowerBound, "desiredShards", desiredShards, "upperBound", upperBound)
if lowerBound <= desiredShards && desiredShards <= upperBound {
return t.numShards
}
numShards := int(math.Ceil(desiredShards))
// Do not downshard if we are more than ten seconds back.
if numShards < t.numShards && delay > 10.0 {
level.Debug(t.logger).Log("msg", "Not downsharding due to being too far behind")
return t.numShards
}
if numShards > t.cfg.MaxShards {
numShards = t.cfg.MaxShards
} else if numShards < t.cfg.MinShards {
numShards = t.cfg.MinShards
}
return numShards
}
func (t *QueueManager) reshardLoop() {
defer t.wg.Done()
for {
select {
case numShards := <-t.reshardChan:
// We start the newShards after we have stopped (the therefore completely
// flushed) the oldShards, to guarantee we only every deliver samples in
// order.
t.shards.stop()
t.shards.start(numShards)
case <-t.quit:
return
}
}
}
func (t *QueueManager) newShards() *shards {
s := &shards{
qm: t,
done: make(chan struct{}),
}
return s
}
type sample struct {
labels labels.Labels
t int64
v float64
}
type shards struct {
mtx sync.RWMutex // With the WAL, this is never actually contended.
qm *QueueManager
queues []chan sample
// Emulate a wait group with a channel and an atomic int, as you
// cannot select on a wait group.
done chan struct{}
running int32
// Soft shutdown context will prevent new enqueues and deadlocks.
softShutdown chan struct{}
// Hard shutdown context is used to terminate outgoing HTTP connections
// after giving them a chance to terminate.
hardShutdown context.CancelFunc
}
// start the shards; must be called before any call to enqueue.
func (s *shards) start(n int) {
s.mtx.Lock()
defer s.mtx.Unlock()
newQueues := make([]chan sample, n)
for i := 0; i < n; i++ {
newQueues[i] = make(chan sample, s.qm.cfg.Capacity)
}
s.queues = newQueues
var hardShutdownCtx context.Context
hardShutdownCtx, s.hardShutdown = context.WithCancel(context.Background())
s.softShutdown = make(chan struct{})
s.running = int32(n)
s.done = make(chan struct{})
for i := 0; i < n; i++ {
go s.runShard(hardShutdownCtx, i, newQueues[i])
}
s.qm.metrics.numShards.Set(float64(n))
}
// stop the shards; subsequent call to enqueue will return false.
func (s *shards) stop() {
// Attempt a clean shutdown, but only wait flushDeadline for all the shards
// to cleanly exit. As we're doing RPCs, enqueue can block indefinitely.
// We must be able so call stop concurrently, hence we can only take the
// RLock here.
s.mtx.RLock()
close(s.softShutdown)
s.mtx.RUnlock()
// Enqueue should now be unblocked, so we can take the write lock. This
// also ensures we don't race with writes to the queues, and get a panic:
// send on closed channel.
s.mtx.Lock()
defer s.mtx.Unlock()
for _, queue := range s.queues {
close(queue)
}
select {
case <-s.done:
return
case <-time.After(s.qm.flushDeadline):
level.Error(s.qm.logger).Log("msg", "Failed to flush all samples on shutdown")
}
// Force an unclean shutdown.
s.hardShutdown()
<-s.done
}
// enqueue a sample. If we are currently in the process of shutting down or resharding,
// will return false; in this case, you should back off and retry.
func (s *shards) enqueue(ref uint64, sample sample) bool {
s.mtx.RLock()
defer s.mtx.RUnlock()
select {
case <-s.softShutdown:
return false
default:
}
shard := uint64(ref) % uint64(len(s.queues))
select {
case <-s.softShutdown:
return false
case s.queues[shard] <- sample:
return true
}
}
func (s *shards) runShard(ctx context.Context, shardID int, queue chan sample) {
defer func() {
if atomic.AddInt32(&s.running, -1) == 0 {
close(s.done)
}
}()
shardNum := strconv.Itoa(shardID)
// 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.
var (
max = s.qm.cfg.MaxSamplesPerSend
nPending = 0
pendingSamples = allocateTimeSeries(max)
buf []byte
)
timer := time.NewTimer(time.Duration(s.qm.cfg.BatchSendDeadline))
stop := func() {
if !timer.Stop() {
select {
case <-timer.C:
default:
}
}
}
defer stop()
for {
select {
case <-ctx.Done():
return
case sample, ok := <-queue:
if !ok {
if nPending > 0 {
level.Debug(s.qm.logger).Log("msg", "Flushing samples to remote storage...", "count", nPending)
s.sendSamples(ctx, pendingSamples[:nPending], &buf)
s.qm.metrics.pendingSamples.Sub(float64(nPending))
level.Debug(s.qm.logger).Log("msg", "Done flushing.")
}
return
}
// Number of pending samples is limited by the fact that sendSamples (via sendSamplesWithBackoff)
// retries endlessly, so once we reach max samples, if we can never send to the endpoint we'll
// stop reading from the queue. This makes it safe to reference pendingSamples by index.
pendingSamples[nPending].Labels = labelsToLabelsProto(sample.labels, pendingSamples[nPending].Labels)
pendingSamples[nPending].Samples[0].Timestamp = sample.t
pendingSamples[nPending].Samples[0].Value = sample.v
nPending++
s.qm.metrics.pendingSamples.Inc()
if nPending >= max {
s.sendSamples(ctx, pendingSamples, &buf)
nPending = 0
s.qm.metrics.pendingSamples.Sub(float64(max))
stop()
timer.Reset(time.Duration(s.qm.cfg.BatchSendDeadline))
}
case <-timer.C:
if nPending > 0 {
level.Debug(s.qm.logger).Log("msg", "runShard timer ticked, sending samples", "samples", nPending, "shard", shardNum)
s.sendSamples(ctx, pendingSamples[:nPending], &buf)
s.qm.metrics.pendingSamples.Sub(float64(nPending))
nPending = 0
}
timer.Reset(time.Duration(s.qm.cfg.BatchSendDeadline))
}
}
}
func (s *shards) sendSamples(ctx context.Context, samples []prompb.TimeSeries, buf *[]byte) {
begin := time.Now()
err := s.sendSamplesWithBackoff(ctx, samples, buf)
if err != nil {
level.Error(s.qm.logger).Log("msg", "non-recoverable error", "count", len(samples), "err", err)
s.qm.metrics.failedSamplesTotal.Add(float64(len(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)))
atomic.StoreInt64(&s.qm.lastSendTimestamp, time.Now().Unix())
}
// sendSamples to the remote storage with backoff for recoverable errors.
func (s *shards) sendSamplesWithBackoff(ctx context.Context, samples []prompb.TimeSeries, buf *[]byte) error {
backoff := s.qm.cfg.MinBackoff
req, highest, err := buildWriteRequest(samples, *buf)
*buf = req
if err != nil {
// Failing to build the write request is non-recoverable, since it will
// only error if marshaling the proto to bytes fails.
return err
}
for {
select {
case <-ctx.Done():
return ctx.Err()
default:
}
begin := time.Now()
err := s.qm.client().Store(ctx, req)
s.qm.metrics.sentBatchDuration.Observe(time.Since(begin).Seconds())
if err == nil {
s.qm.metrics.succeededSamplesTotal.Add(float64(len(samples)))
s.qm.metrics.bytesSent.Add(float64(len(req)))
s.qm.metrics.highestSentTimestamp.Set(float64(highest / 1000))
return nil
}
if _, ok := err.(recoverableError); !ok {
return err
}
s.qm.metrics.retriedSamplesTotal.Add(float64(len(samples)))
level.Warn(s.qm.logger).Log("msg", "Failed to send batch, retrying", "err", err)
time.Sleep(time.Duration(backoff))
backoff = backoff * 2
if backoff > s.qm.cfg.MaxBackoff {
backoff = s.qm.cfg.MaxBackoff
}
}
}
func buildWriteRequest(samples []prompb.TimeSeries, buf []byte) ([]byte, int64, error) {
var highest int64
for _, ts := range samples {
// At the moment we only ever append a TimeSeries with a single sample in it.
if ts.Samples[0].Timestamp > highest {
highest = ts.Samples[0].Timestamp
}
}
req := &prompb.WriteRequest{
Timeseries: samples,
}
data, err := proto.Marshal(req)
if err != nil {
return nil, highest, err
}
// snappy uses len() to see if it needs to allocate a new slice. Make the
// buffer as long as possible.
if buf != nil {
buf = buf[0:cap(buf)]
}
compressed := snappy.Encode(buf, data)
return compressed, highest, nil
}
func allocateTimeSeries(capacity int) []prompb.TimeSeries {
timeseries := make([]prompb.TimeSeries, capacity)
// We only ever send one sample per timeseries, so preallocate with length one.
for i := range timeseries {
timeseries[i].Samples = []prompb.Sample{{}}
}
return timeseries
}