777 lines
22 KiB
Go
777 lines
22 KiB
Go
// Copyright 2013 The Prometheus Authors
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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package remote
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import (
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"context"
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"math"
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"strconv"
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"sync"
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"sync/atomic"
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"time"
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"github.com/go-kit/kit/log"
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"github.com/go-kit/kit/log/level"
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"github.com/gogo/protobuf/proto"
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"github.com/golang/snappy"
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"github.com/prometheus/client_golang/prometheus"
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"github.com/prometheus/client_golang/prometheus/promauto"
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"github.com/prometheus/prometheus/config"
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"github.com/prometheus/prometheus/pkg/labels"
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"github.com/prometheus/prometheus/pkg/relabel"
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"github.com/prometheus/prometheus/prompb"
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"github.com/prometheus/tsdb"
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tsdbLabels "github.com/prometheus/tsdb/labels"
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)
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// String constants for instrumentation.
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const (
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namespace = "prometheus"
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subsystem = "remote_storage"
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queue = "queue"
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// We track samples in/out and how long pushes take using an Exponentially
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// Weighted Moving Average.
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ewmaWeight = 0.2
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shardUpdateDuration = 10 * time.Second
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// Allow 30% too many shards before scaling down.
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shardToleranceFraction = 0.3
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)
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var (
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succeededSamplesTotal = promauto.NewCounterVec(
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prometheus.CounterOpts{
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Namespace: namespace,
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Subsystem: subsystem,
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Name: "succeeded_samples_total",
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Help: "Total number of samples successfully sent to remote storage.",
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},
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[]string{queue},
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)
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failedSamplesTotal = promauto.NewCounterVec(
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prometheus.CounterOpts{
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Namespace: namespace,
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Subsystem: subsystem,
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Name: "failed_samples_total",
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Help: "Total number of samples which failed on send to remote storage, non-recoverable errors.",
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},
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[]string{queue},
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)
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retriedSamplesTotal = promauto.NewCounterVec(
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prometheus.CounterOpts{
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Namespace: namespace,
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Subsystem: subsystem,
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Name: "retried_samples_total",
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Help: "Total number of samples which failed on send to remote storage but were retried because the send error was recoverable.",
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},
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[]string{queue},
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)
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droppedSamplesTotal = promauto.NewCounterVec(
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prometheus.CounterOpts{
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Namespace: namespace,
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Subsystem: subsystem,
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Name: "dropped_samples_total",
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Help: "Total number of samples which were dropped after being read from the WAL before being sent via remote write.",
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},
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[]string{queue},
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)
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enqueueRetriesTotal = promauto.NewCounterVec(
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prometheus.CounterOpts{
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Namespace: namespace,
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Subsystem: subsystem,
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Name: "enqueue_retries_total",
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Help: "Total number of times enqueue has failed because a shards queue was full.",
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},
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[]string{queue},
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)
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sentBatchDuration = promauto.NewHistogramVec(
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prometheus.HistogramOpts{
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Namespace: namespace,
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Subsystem: subsystem,
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Name: "sent_batch_duration_seconds",
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Help: "Duration of sample batch send calls to the remote storage.",
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Buckets: prometheus.DefBuckets,
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},
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[]string{queue},
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)
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queueHighestSentTimestamp = promauto.NewGaugeVec(
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prometheus.GaugeOpts{
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Namespace: namespace,
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Subsystem: subsystem,
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Name: "queue_highest_sent_timestamp_seconds",
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Help: "Timestamp from a WAL sample, the highest timestamp successfully sent by this queue, in seconds since epoch.",
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},
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[]string{queue},
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)
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queuePendingSamples = promauto.NewGaugeVec(
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prometheus.GaugeOpts{
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Namespace: namespace,
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Subsystem: subsystem,
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Name: "pending_samples",
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Help: "The number of samples pending in the queues shards to be sent to the remote storage.",
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},
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[]string{queue},
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)
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shardCapacity = promauto.NewGaugeVec(
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prometheus.GaugeOpts{
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Namespace: namespace,
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Subsystem: subsystem,
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Name: "shard_capacity",
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Help: "The capacity of each shard of the queue used for parallel sending to the remote storage.",
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},
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[]string{queue},
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)
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numShards = promauto.NewGaugeVec(
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prometheus.GaugeOpts{
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Namespace: namespace,
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Subsystem: subsystem,
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Name: "shards",
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Help: "The number of shards used for parallel sending to the remote storage.",
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},
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[]string{queue},
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)
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)
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// StorageClient defines an interface for sending a batch of samples to an
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// external timeseries database.
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type StorageClient interface {
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// Store stores the given samples in the remote storage.
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Store(context.Context, []byte) error
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// Name identifies the remote storage implementation.
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Name() string
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}
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// QueueManager manages a queue of samples to be sent to the Storage
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// indicated by the provided StorageClient. Implements writeTo interface
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// used by WAL Watcher.
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type QueueManager struct {
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logger log.Logger
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flushDeadline time.Duration
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cfg config.QueueConfig
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externalLabels labels.Labels
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relabelConfigs []*relabel.Config
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client StorageClient
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watcher *WALWatcher
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seriesMtx sync.Mutex
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seriesLabels map[uint64][]prompb.Label
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seriesSegmentIndexes map[uint64]int
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droppedSeries map[uint64]struct{}
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shards *shards
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numShards int
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reshardChan chan int
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quit chan struct{}
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wg sync.WaitGroup
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samplesIn, samplesDropped, samplesOut, samplesOutDuration *ewmaRate
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integralAccumulator float64
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highestSentTimestampMetric *maxGauge
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pendingSamplesMetric prometheus.Gauge
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enqueueRetriesMetric prometheus.Counter
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droppedSamplesTotal prometheus.Counter
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numShardsMetric prometheus.Gauge
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failedSamplesTotal prometheus.Counter
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sentBatchDuration prometheus.Observer
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succeededSamplesTotal prometheus.Counter
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retriedSamplesTotal prometheus.Counter
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}
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// NewQueueManager builds a new QueueManager.
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func NewQueueManager(logger log.Logger, walDir string, samplesIn *ewmaRate, cfg config.QueueConfig, externalLabels labels.Labels, relabelConfigs []*relabel.Config, client StorageClient, flushDeadline time.Duration) *QueueManager {
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if logger == nil {
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logger = log.NewNopLogger()
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}
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name := client.Name()
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logger = log.With(logger, "queue", name)
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t := &QueueManager{
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logger: logger,
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flushDeadline: flushDeadline,
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cfg: cfg,
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externalLabels: externalLabels,
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relabelConfigs: relabelConfigs,
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client: client,
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seriesLabels: make(map[uint64][]prompb.Label),
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seriesSegmentIndexes: make(map[uint64]int),
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droppedSeries: make(map[uint64]struct{}),
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numShards: cfg.MinShards,
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reshardChan: make(chan int),
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quit: make(chan struct{}),
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samplesIn: samplesIn,
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samplesDropped: newEWMARate(ewmaWeight, shardUpdateDuration),
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samplesOut: newEWMARate(ewmaWeight, shardUpdateDuration),
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samplesOutDuration: newEWMARate(ewmaWeight, shardUpdateDuration),
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highestSentTimestampMetric: &maxGauge{
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Gauge: queueHighestSentTimestamp.WithLabelValues(name),
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},
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pendingSamplesMetric: queuePendingSamples.WithLabelValues(name),
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enqueueRetriesMetric: enqueueRetriesTotal.WithLabelValues(name),
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droppedSamplesTotal: droppedSamplesTotal.WithLabelValues(name),
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numShardsMetric: numShards.WithLabelValues(name),
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failedSamplesTotal: failedSamplesTotal.WithLabelValues(name),
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sentBatchDuration: sentBatchDuration.WithLabelValues(name),
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succeededSamplesTotal: succeededSamplesTotal.WithLabelValues(name),
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retriedSamplesTotal: retriedSamplesTotal.WithLabelValues(name),
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}
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t.watcher = NewWALWatcher(logger, name, t, walDir)
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t.shards = t.newShards()
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// Initialise some metrics.
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shardCapacity.WithLabelValues(name).Set(float64(t.cfg.Capacity))
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t.pendingSamplesMetric.Set(0)
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return t
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}
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// Append queues a sample to be sent to the remote storage. Blocks until all samples are
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// enqueued on their shards or a shutdown signal is received.
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func (t *QueueManager) Append(s []tsdb.RefSample) bool {
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type enqueuable struct {
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ts prompb.TimeSeries
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ref uint64
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}
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tempSamples := make([]enqueuable, 0, len(s))
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t.seriesMtx.Lock()
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for _, sample := range s {
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// If we have no labels for the series, due to relabelling or otherwise, don't send the sample.
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if _, ok := t.seriesLabels[sample.Ref]; !ok {
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t.droppedSamplesTotal.Inc()
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t.samplesDropped.incr(1)
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if _, ok := t.droppedSeries[sample.Ref]; !ok {
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level.Info(t.logger).Log("msg", "dropped sample for series that was not explicitly dropped via relabelling", "ref", sample.Ref)
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}
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continue
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}
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tempSamples = append(tempSamples, enqueuable{
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ts: prompb.TimeSeries{
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Labels: t.seriesLabels[sample.Ref],
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Samples: []prompb.Sample{
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prompb.Sample{
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Value: float64(sample.V),
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Timestamp: sample.T,
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},
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},
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},
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ref: sample.Ref,
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})
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}
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t.seriesMtx.Unlock()
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outer:
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for _, sample := range tempSamples {
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// This will only loop if the queues are being resharded.
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backoff := t.cfg.MinBackoff
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for {
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select {
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case <-t.quit:
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return false
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default:
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}
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if t.shards.enqueue(sample.ref, sample.ts) {
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continue outer
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}
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t.enqueueRetriesMetric.Inc()
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time.Sleep(time.Duration(backoff))
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backoff = backoff * 2
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if backoff > t.cfg.MaxBackoff {
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backoff = t.cfg.MaxBackoff
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}
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}
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}
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return true
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}
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// Start the queue manager sending samples to the remote storage.
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// Does not block.
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func (t *QueueManager) Start() {
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t.shards.start(t.numShards)
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t.watcher.Start()
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t.wg.Add(2)
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go t.updateShardsLoop()
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go t.reshardLoop()
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}
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// Stop stops sending samples to the remote storage and waits for pending
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// sends to complete.
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func (t *QueueManager) Stop() {
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level.Info(t.logger).Log("msg", "Stopping remote storage...")
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defer level.Info(t.logger).Log("msg", "Remote storage stopped.")
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close(t.quit)
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t.wg.Wait()
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// Wait for all QueueManager routines to end before stopping shards and WAL watcher. This
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// is to ensure we don't end up executing a reshard and shards.stop() at the same time, which
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// causes a closed channel panic.
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t.shards.stop()
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t.watcher.Stop()
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// On shutdown, release the strings in the labels from the intern pool.
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t.seriesMtx.Lock()
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defer t.seriesMtx.Unlock()
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for _, labels := range t.seriesLabels {
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release(labels)
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}
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}
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// StoreSeries keeps track of which series we know about for lookups when sending samples to remote.
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func (t *QueueManager) StoreSeries(series []tsdb.RefSeries, index int) {
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temp := make(map[uint64][]prompb.Label, len(series))
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for _, s := range series {
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ls := processExternalLabels(s.Labels, t.externalLabels)
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rl := relabel.Process(ls, t.relabelConfigs...)
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if len(rl) == 0 {
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t.droppedSeries[s.Ref] = struct{}{}
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continue
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}
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temp[s.Ref] = labelsToLabelsProto(rl)
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}
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t.seriesMtx.Lock()
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defer t.seriesMtx.Unlock()
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for ref, labels := range temp {
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t.seriesSegmentIndexes[ref] = index
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// We should not ever be replacing a series labels in the map, but just
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// in case we do we need to ensure we do not leak the replaced interned
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// strings.
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if orig, ok := t.seriesLabels[ref]; ok {
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release(orig)
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}
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t.seriesLabels[ref] = labels
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}
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}
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// SeriesReset is used when reading a checkpoint. WAL Watcher should have
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// stored series records with the checkpoints index number, so we can now
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// delete any ref ID's lower than that # from the two maps.
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func (t *QueueManager) SeriesReset(index int) {
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t.seriesMtx.Lock()
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defer t.seriesMtx.Unlock()
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// Check for series that are in segments older than the checkpoint
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// that were not also present in the checkpoint.
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for k, v := range t.seriesSegmentIndexes {
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if v < index {
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delete(t.seriesSegmentIndexes, k)
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release(t.seriesLabels[k])
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delete(t.seriesLabels, k)
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}
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}
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}
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func release(ls []prompb.Label) {
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for _, l := range ls {
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interner.release(l.Name)
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interner.release(l.Value)
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}
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}
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// processExternalLabels merges externalLabels into ls. If ls contains
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// a label in externalLabels, the value in ls wins.
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func processExternalLabels(ls tsdbLabels.Labels, externalLabels labels.Labels) labels.Labels {
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i, j, result := 0, 0, make(labels.Labels, 0, len(ls)+len(externalLabels))
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for i < len(ls) && j < len(externalLabels) {
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if ls[i].Name < externalLabels[j].Name {
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result = append(result, labels.Label{
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Name: ls[i].Name,
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Value: ls[i].Value,
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})
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i++
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} else if ls[i].Name > externalLabels[j].Name {
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result = append(result, externalLabels[j])
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j++
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} else {
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result = append(result, labels.Label{
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Name: ls[i].Name,
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Value: ls[i].Value,
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})
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i++
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j++
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}
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}
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for ; i < len(ls); i++ {
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result = append(result, labels.Label{
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Name: ls[i].Name,
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Value: ls[i].Value,
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})
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}
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result = append(result, externalLabels[j:]...)
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return result
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}
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func (t *QueueManager) updateShardsLoop() {
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defer t.wg.Done()
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ticker := time.NewTicker(shardUpdateDuration)
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defer ticker.Stop()
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for {
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select {
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case <-ticker.C:
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t.calculateDesiredShards()
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case <-t.quit:
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return
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}
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}
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}
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func (t *QueueManager) calculateDesiredShards() {
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t.samplesOut.tick()
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t.samplesDropped.tick()
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t.samplesOutDuration.tick()
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// We use the number of incoming samples as a prediction of how much work we
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// will need to do next iteration. We add to this any pending samples
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// (received - send) so we can catch up with any backlog. We use the average
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// outgoing batch latency to work out how many shards we need.
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var (
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samplesIn = t.samplesIn.rate()
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samplesOut = t.samplesOut.rate()
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samplesKeptRatio = samplesOut / (t.samplesDropped.rate() + samplesOut)
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samplesOutDuration = t.samplesOutDuration.rate()
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highestSent = t.highestSentTimestampMetric.Get()
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highestRecv = highestTimestamp.Get()
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samplesPending = (highestRecv - highestSent) * samplesIn * samplesKeptRatio
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)
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// We use an integral accumulator, like in a PID, to help dampen oscillation.
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t.integralAccumulator = t.integralAccumulator + (samplesPending * 0.1)
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if samplesOut <= 0 {
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return
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}
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var (
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timePerSample = samplesOutDuration / samplesOut
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desiredShards = (timePerSample * samplesPending) / float64(time.Second)
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)
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level.Debug(t.logger).Log("msg", "QueueManager.caclulateDesiredShards",
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"samplesIn", samplesIn,
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"samplesOut", samplesOut,
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"samplesKeptRatio", samplesKeptRatio,
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"samplesPending", samplesPending,
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"samplesOutDuration", samplesOutDuration,
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"timePerSample", timePerSample,
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"desiredShards", desiredShards,
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"highestSent", highestSent,
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"highestRecv", highestRecv)
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// Changes in the number of shards must be greater than shardToleranceFraction.
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var (
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lowerBound = float64(t.numShards) * (1. - shardToleranceFraction)
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upperBound = float64(t.numShards) * (1. + shardToleranceFraction)
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)
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level.Debug(t.logger).Log("msg", "QueueManager.updateShardsLoop",
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"lowerBound", lowerBound, "desiredShards", desiredShards, "upperBound", upperBound)
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if lowerBound <= desiredShards && desiredShards <= upperBound {
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return
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}
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numShards := int(math.Ceil(desiredShards))
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if numShards > t.cfg.MaxShards {
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numShards = t.cfg.MaxShards
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} else if numShards < t.cfg.MinShards {
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numShards = t.cfg.MinShards
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}
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if numShards == t.numShards {
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return
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}
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// Resharding can take some time, and we want this loop
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// to stay close to shardUpdateDuration.
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select {
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case t.reshardChan <- numShards:
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level.Info(t.logger).Log("msg", "Remote storage resharding", "from", t.numShards, "to", numShards)
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t.numShards = numShards
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default:
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level.Info(t.logger).Log("msg", "Currently resharding, skipping.")
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}
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}
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func (t *QueueManager) reshardLoop() {
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defer t.wg.Done()
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for {
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select {
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case numShards := <-t.reshardChan:
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// We start the newShards after we have stopped (the therefore completely
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// flushed) the oldShards, to guarantee we only every deliver samples in
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// 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
|
|
}
|