prometheus/storage/remote/queue_manager.go
Callum Styan 3639d51eb6 Remote Storage: string interner should not panic in release (#5487)
* Don't panic if we try to release a string that is not in the interner.

* Move seriesMtx locking in QueueManager's StoreSeries function.

This stops us from calling release for strings that aren't interned if
there's a race between reading a checkpoint and storing new series
labels, which could happen during checkpointing or reloading config.

Signed-off-by: Callum Styan <callumstyan@gmail.com>
2019-04-24 10:46:31 +01:00

797 lines
23 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/client_golang/prometheus/promauto"
"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/tsdb"
tsdbLabels "github.com/prometheus/tsdb/labels"
)
// 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
)
var (
succeededSamplesTotal = promauto.NewCounterVec(
prometheus.CounterOpts{
Namespace: namespace,
Subsystem: subsystem,
Name: "succeeded_samples_total",
Help: "Total number of samples successfully sent to remote storage.",
},
[]string{queue},
)
failedSamplesTotal = promauto.NewCounterVec(
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.",
},
[]string{queue},
)
retriedSamplesTotal = promauto.NewCounterVec(
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.",
},
[]string{queue},
)
droppedSamplesTotal = promauto.NewCounterVec(
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.",
},
[]string{queue},
)
enqueueRetriesTotal = promauto.NewCounterVec(
prometheus.CounterOpts{
Namespace: namespace,
Subsystem: subsystem,
Name: "enqueue_retries_total",
Help: "Total number of times enqueue has failed because a shards queue was full.",
},
[]string{queue},
)
sentBatchDuration = promauto.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},
)
queueHighestSentTimestamp = promauto.NewGaugeVec(
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.",
},
[]string{queue},
)
queuePendingSamples = promauto.NewGaugeVec(
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.",
},
[]string{queue},
)
shardCapacity = promauto.NewGaugeVec(
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.",
},
[]string{queue},
)
numShards = promauto.NewGaugeVec(
prometheus.GaugeOpts{
Namespace: namespace,
Subsystem: subsystem,
Name: "shards",
Help: "The number of shards used for parallel sending to the remote storage.",
},
[]string{queue},
)
)
// 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 identifies the remote storage implementation.
Name() 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 {
logger log.Logger
flushDeadline time.Duration
cfg config.QueueConfig
externalLabels labels.Labels
relabelConfigs []*relabel.Config
client StorageClient
watcher *WALWatcher
seriesMtx sync.Mutex
seriesLabels map[uint64][]prompb.Label
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
integralAccumulator float64
highestSentTimestampMetric *maxGauge
pendingSamplesMetric prometheus.Gauge
enqueueRetriesMetric prometheus.Counter
droppedSamplesTotal prometheus.Counter
numShardsMetric prometheus.Gauge
failedSamplesTotal prometheus.Counter
sentBatchDuration prometheus.Observer
succeededSamplesTotal prometheus.Counter
retriedSamplesTotal prometheus.Counter
shardCapacity prometheus.Gauge
}
// NewQueueManager builds a new QueueManager.
func NewQueueManager(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()
}
name := client.Name()
logger = log.With(logger, "queue", name)
t := &QueueManager{
logger: logger,
flushDeadline: flushDeadline,
cfg: cfg,
externalLabels: externalLabels,
relabelConfigs: relabelConfigs,
client: client,
seriesLabels: make(map[uint64][]prompb.Label),
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),
}
t.watcher = NewWALWatcher(logger, 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(s []tsdb.RefSample) bool {
type enqueuable struct {
ts prompb.TimeSeries
ref uint64
}
tempSamples := make([]enqueuable, 0, len(s))
t.seriesMtx.Lock()
for _, sample := range s {
// If we have no labels for the series, due to relabelling or otherwise, don't send the sample.
if _, ok := t.seriesLabels[sample.Ref]; !ok {
t.droppedSamplesTotal.Inc()
t.samplesDropped.incr(1)
if _, ok := t.droppedSeries[sample.Ref]; !ok {
level.Info(t.logger).Log("msg", "dropped sample for series that was not explicitly dropped via relabelling", "ref", sample.Ref)
}
continue
}
tempSamples = append(tempSamples, enqueuable{
ts: prompb.TimeSeries{
Labels: t.seriesLabels[sample.Ref],
Samples: []prompb.Sample{
prompb.Sample{
Value: float64(sample.V),
Timestamp: sample.T,
},
},
},
ref: sample.Ref,
})
}
t.seriesMtx.Unlock()
outer:
for _, sample := range tempSamples {
// 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(sample.ref, sample.ts) {
continue outer
}
t.enqueueRetriesMetric.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() {
// Setup the QueueManagers metrics. We do this here rather than in the
// constructor because of the ordering of creating Queue Managers's, stopping them,
// and then starting new ones in storage/remote/storage.go ApplyConfig.
name := t.client.Name()
t.highestSentTimestampMetric = &maxGauge{
Gauge: queueHighestSentTimestamp.WithLabelValues(name),
}
t.pendingSamplesMetric = queuePendingSamples.WithLabelValues(name)
t.enqueueRetriesMetric = enqueueRetriesTotal.WithLabelValues(name)
t.droppedSamplesTotal = droppedSamplesTotal.WithLabelValues(name)
t.numShardsMetric = numShards.WithLabelValues(name)
t.failedSamplesTotal = failedSamplesTotal.WithLabelValues(name)
t.sentBatchDuration = sentBatchDuration.WithLabelValues(name)
t.succeededSamplesTotal = succeededSamplesTotal.WithLabelValues(name)
t.retriedSamplesTotal = retriedSamplesTotal.WithLabelValues(name)
t.shardCapacity = shardCapacity.WithLabelValues(name)
// Initialise some metrics.
t.shardCapacity.Set(float64(t.cfg.Capacity))
t.pendingSamplesMetric.Set(0)
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()
defer t.seriesMtx.Unlock()
for _, labels := range t.seriesLabels {
release(labels)
}
// Delete metrics so we don't have alerts for queues that are gone.
name := t.client.Name()
queueHighestSentTimestamp.DeleteLabelValues(name)
queuePendingSamples.DeleteLabelValues(name)
enqueueRetriesTotal.DeleteLabelValues(name)
droppedSamplesTotal.DeleteLabelValues(name)
numShards.DeleteLabelValues(name)
failedSamplesTotal.DeleteLabelValues(name)
sentBatchDuration.DeleteLabelValues(name)
succeededSamplesTotal.DeleteLabelValues(name)
retriedSamplesTotal.DeleteLabelValues(name)
shardCapacity.DeleteLabelValues(name)
}
// StoreSeries keeps track of which series we know about for lookups when sending samples to remote.
func (t *QueueManager) StoreSeries(series []tsdb.RefSeries, index int) {
// Lock before any calls to labelsToLabels proto, as that's where string interning is done.
t.seriesMtx.Lock()
defer t.seriesMtx.Unlock()
temp := make(map[uint64][]prompb.Label, len(series))
for _, s := range series {
ls := processExternalLabels(s.Labels, t.externalLabels)
rl := relabel.Process(ls, t.relabelConfigs...)
if len(rl) == 0 {
t.droppedSeries[s.Ref] = struct{}{}
continue
}
temp[s.Ref] = labelsToLabelsProto(rl)
}
for ref, labels := range temp {
t.seriesSegmentIndexes[ref] = index
// 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[ref]; ok {
release(orig)
}
t.seriesLabels[ref] = labels
}
}
// 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)
release(t.seriesLabels[k])
delete(t.seriesLabels, k)
}
}
}
func release(ls []prompb.Label) {
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 tsdbLabels.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:
t.calculateDesiredShards()
case <-t.quit:
return
}
}
}
func (t *QueueManager) calculateDesiredShards() {
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 (
samplesIn = t.samplesIn.rate()
samplesOut = t.samplesOut.rate()
samplesKeptRatio = samplesOut / (t.samplesDropped.rate() + samplesOut)
samplesOutDuration = t.samplesOutDuration.rate()
highestSent = t.highestSentTimestampMetric.Get()
highestRecv = highestTimestamp.Get()
samplesPending = (highestRecv - highestSent) * samplesIn * samplesKeptRatio
)
// 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 * samplesPending) / float64(time.Second)
)
level.Debug(t.logger).Log("msg", "QueueManager.caclulateDesiredShards",
"samplesIn", samplesIn,
"samplesOut", samplesOut,
"samplesKeptRatio", samplesKeptRatio,
"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
}
numShards := int(math.Ceil(desiredShards))
if numShards > t.cfg.MaxShards {
numShards = t.cfg.MaxShards
} else if numShards < t.cfg.MinShards {
numShards = t.cfg.MinShards
}
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:
level.Info(t.logger).Log("msg", "Remote storage resharding", "from", t.numShards, "to", numShards)
t.numShards = numShards
default:
level.Info(t.logger).Log("msg", "Currently resharding, skipping.")
}
}
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 shards struct {
mtx sync.RWMutex // With the WAL, this is never actually contended.
qm *QueueManager
queues []chan prompb.TimeSeries
// 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 prompb.TimeSeries, n)
for i := 0; i < n; i++ {
newQueues[i] = make(chan prompb.TimeSeries, 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.numShardsMetric.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 prompb.TimeSeries) 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, i int, queue chan prompb.TimeSeries) {
defer func() {
if atomic.AddInt32(&s.running, -1) == 0 {
close(s.done)
}
}()
shardNum := strconv.Itoa(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 := []prompb.TimeSeries{}
max := s.qm.cfg.MaxSamplesPerSend
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 len(pendingSamples) > 0 {
level.Debug(s.qm.logger).Log("msg", "Flushing samples to remote storage...", "count", len(pendingSamples))
s.sendSamples(ctx, pendingSamples)
s.qm.pendingSamplesMetric.Sub(float64(len(pendingSamples)))
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 > 100 samples, if we can never send to the endpoint we'll
// stop reading from the queue (which has a size of 10).
pendingSamples = append(pendingSamples, sample)
s.qm.pendingSamplesMetric.Inc()
if len(pendingSamples) >= max {
s.sendSamples(ctx, pendingSamples[:max])
pendingSamples = pendingSamples[max:]
s.qm.pendingSamplesMetric.Sub(float64(max))
stop()
timer.Reset(time.Duration(s.qm.cfg.BatchSendDeadline))
}
case <-timer.C:
if len(pendingSamples) > 0 {
level.Debug(s.qm.logger).Log("msg", "runShard timer ticked, sending samples", "samples", len(pendingSamples), "shard", shardNum)
n := len(pendingSamples)
s.sendSamples(ctx, pendingSamples)
pendingSamples = pendingSamples[:0]
s.qm.pendingSamplesMetric.Sub(float64(n))
}
timer.Reset(time.Duration(s.qm.cfg.BatchSendDeadline))
}
}
}
func (s *shards) sendSamples(ctx context.Context, samples []prompb.TimeSeries) {
begin := time.Now()
err := s.sendSamplesWithBackoff(ctx, samples)
if err != nil {
level.Error(s.qm.logger).Log("msg", "non-recoverable error", "count", len(samples), "err", err)
s.qm.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)))
}
// sendSamples to the remote storage with backoff for recoverable errors.
func (s *shards) sendSamplesWithBackoff(ctx context.Context, samples []prompb.TimeSeries) error {
backoff := s.qm.cfg.MinBackoff
req, highest, err := buildWriteRequest(samples)
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.sentBatchDuration.Observe(time.Since(begin).Seconds())
if err == nil {
s.qm.succeededSamplesTotal.Add(float64(len(samples)))
s.qm.highestSentTimestampMetric.Set(float64(highest / 1000))
return nil
}
if _, ok := err.(recoverableError); !ok {
return err
}
s.qm.retriedSamplesTotal.Add(float64(len(samples)))
level.Debug(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) ([]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
}
compressed := snappy.Encode(nil, data)
return compressed, highest, nil
}