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454ecf3f52
In a way, our instants were also ranges, just with the staleness delta as range length. They are no treated equally, just that in one case, the range length is set as range, in the other the staleness delta. However, there are "real" instants where start and and time of a query is the same. In those cases, we only want to return a single value (the one closest before or at the equal start and end time). If that value is the last sample in the series, odds are we have it already in the series object. In that case, there is no need to pin or load any chunks. A special singleSampleSeriesIterator is created for that. This should greatly speed up instant queries as they happen frequently for rule evaluations.
111 lines
5.1 KiB
Go
111 lines
5.1 KiB
Go
// Copyright 2014 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 local
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import (
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"time"
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"github.com/prometheus/client_golang/prometheus"
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"github.com/prometheus/common/model"
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"github.com/prometheus/prometheus/storage/metric"
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)
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// Storage ingests and manages samples, along with various indexes. All methods
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// are goroutine-safe. Storage implements storage.SampleAppender.
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type Storage interface {
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prometheus.Collector
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// Append stores a sample in the Storage. Multiple samples for the same
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// fingerprint need to be submitted in chronological order, from oldest
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// to newest. When Append has returned, the appended sample might not be
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// queryable immediately. (Use WaitForIndexing to wait for complete
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// processing.) The implementation might remove labels with empty value
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// from the provided Sample as those labels are considered equivalent to
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// a label not present at all.
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Append(*model.Sample) error
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// NeedsThrottling returns true if the Storage has too many chunks in memory
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// already or has too many chunks waiting for persistence.
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NeedsThrottling() bool
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// NewPreloader returns a new Preloader which allows preloading and pinning
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// series data into memory for use within a query.
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NewPreloader() Preloader
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// MetricsForLabelMatchers returns the metrics from storage that satisfy the given
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// label matchers. At least one label matcher must be specified that does not
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// match the empty string.
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MetricsForLabelMatchers(...*metric.LabelMatcher) map[model.Fingerprint]metric.Metric
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// LastSamplePairForFingerprint returns the last sample pair that has
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// been ingested for the provided fingerprint. If this instance of the
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// Storage has never ingested a sample for the provided fingerprint (or
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// the last ingestion is so long ago that the series has been archived),
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// ZeroSamplePair is returned.
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LastSamplePairForFingerprint(model.Fingerprint) model.SamplePair
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// Get all of the label values that are associated with a given label name.
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LabelValuesForLabelName(model.LabelName) model.LabelValues
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// Get the metric associated with the provided fingerprint.
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MetricForFingerprint(model.Fingerprint) metric.Metric
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// Drop all time series associated with the given fingerprints.
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DropMetricsForFingerprints(...model.Fingerprint)
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// Run the various maintenance loops in goroutines. Returns when the
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// storage is ready to use. Keeps everything running in the background
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// until Stop is called.
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Start() error
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// Stop shuts down the Storage gracefully, flushes all pending
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// operations, stops all maintenance loops,and frees all resources.
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Stop() error
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// WaitForIndexing returns once all samples in the storage are
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// indexed. Indexing is needed for FingerprintsForLabelMatchers and
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// LabelValuesForLabelName and may lag behind.
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WaitForIndexing()
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}
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// SeriesIterator enables efficient access of sample values in a series. Its
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// methods are not goroutine-safe. A SeriesIterator iterates over a snapshot of
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// a series, i.e. it is safe to continue using a SeriesIterator after or during
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// modifying the corresponding series, but the iterator will represent the state
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// of the series prior the modification.
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type SeriesIterator interface {
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// Gets the value that is closest before the given time. In case a value
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// exist at precisely the given time, that value is returned. If no
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// applicable value exists, ZeroSamplePair is returned.
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ValueAtOrBeforeTime(model.Time) model.SamplePair
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// Gets the boundary values of an interval: the first and last value
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// within a given interval.
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BoundaryValues(metric.Interval) []model.SamplePair
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// Gets all values contained within a given interval.
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RangeValues(metric.Interval) []model.SamplePair
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}
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// A Preloader preloads series data necessary for a query into memory, pins it
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// until released via Close(), and returns an iterator for the pinned data. Its
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// methods are generally not goroutine-safe.
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type Preloader interface {
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PreloadRange(
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fp model.Fingerprint,
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from model.Time, through model.Time,
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) (SeriesIterator, error)
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PreloadInstant(
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fp model.Fingerprint,
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timestamp model.Time, stalenessDelta time.Duration,
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) (SeriesIterator, error)
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// Close unpins any previously requested series data from memory.
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Close()
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}
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// ZeroSamplePair is the pseudo zero-value of model.SamplePair used by the local
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// package to signal a non-existing sample. It is a SamplePair with timestamp
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// model.Earliest and value 0.0. Note that the natural zero value of SamplePair
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// has a timestamp of 0, which is possible to appear in a real SamplePair and
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// thus not suitable to signal a non-existing SamplePair.
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var ZeroSamplePair = model.SamplePair{Timestamp: model.Earliest}
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