mirror of
https://github.com/prometheus/prometheus.git
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b3e34c6658
This commit introduces to Prometheus a batch database sample curator, which corroborates the high watermarks for sample series against the curation watermark table to see whether a curator of a given type needs to be run. The curator is an abstract executor, which runs various curation strategies across the database. It remarks the progress for each type of curation processor that runs for a given sample series. A curation procesor is responsible for effectuating the underlying batch changes that are request. In this commit, we introduce the CompactionProcessor, which takes several bits of runtime metadata and combine sparse sample entries in the database together to form larger groups. For instance, for a given series it would be possible to have the curator effectuate the following grouping: - Samples Older than Two Weeks: Grouped into Bunches of 10000 - Samples Older than One Week: Grouped into Bunches of 1000 - Samples Older than One Day: Grouped into Bunches of 100 - Samples Older than One Hour: Grouped into Bunches of 10 The benefits hereof of such a compaction are 1. a smaller search space in the database keyspace, 2. better employment of compression for repetious values, and 3. reduced seek times.
97 lines
4.2 KiB
Go
97 lines
4.2 KiB
Go
// Copyright 2013 Prometheus Team
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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 metric
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import (
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"github.com/prometheus/client_golang"
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"github.com/prometheus/client_golang/maths"
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"github.com/prometheus/client_golang/metrics"
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"time"
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)
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const (
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operation = "operation"
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success = "success"
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failure = "failure"
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result = "result"
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appendFingerprints = "append_fingerprints"
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appendLabelNameFingerprint = "append_label_name_fingerprint"
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appendLabelPairFingerprint = "append_label_pair_fingerprint"
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appendSample = "append_sample"
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appendSamples = "append_samples"
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findUnindexedMetrics = "find_unindexed_metrics"
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flushMemory = "flush_memory"
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getBoundaryValues = "get_boundary_values"
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getFingerprintsForLabelName = "get_fingerprints_for_label_name"
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getFingerprintsForLabelSet = "get_fingerprints_for_labelset"
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getLabelNameFingerprints = "get_label_name_fingerprints"
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getMetricForFingerprint = "get_metric_for_fingerprint"
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getRangeValues = "get_range_values"
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getValueAtTime = "get_value_at_time"
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hasIndexMetric = "has_index_metric"
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hasLabelName = "has_label_name"
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hasLabelPair = "has_label_pair"
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indexFingerprints = "index_fingerprints"
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indexLabelNames = "index_label_names"
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indexLabelPairs = "index_label_pairs"
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indexMetric = "index_metric"
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indexMetrics = "index_metrics"
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rebuildDiskFrontier = "rebuild_disk_frontier"
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refreshHighWatermarks = "refresh_high_watermarks"
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renderView = "render_view"
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setLabelNameFingerprints = "set_label_name_fingerprints"
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setLabelPairFingerprints = "set_label_pair_fingerprints"
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writeMemory = "write_memory"
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cutOff = "recency_threshold"
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processorName = "processor"
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)
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var (
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diskLatencyHistogram = &metrics.HistogramSpecification{
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Starts: metrics.LogarithmicSizedBucketsFor(0, 5000),
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BucketBuilder: metrics.AccumulatingBucketBuilder(metrics.EvictAndReplaceWith(10, maths.Average), 100),
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ReportablePercentiles: []float64{0.01, 0.05, 0.5, 0.90, 0.99},
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}
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curationDuration = metrics.NewCounter()
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curationDurations = metrics.NewHistogram(diskLatencyHistogram)
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curationFilterOperations = metrics.NewCounter()
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storageOperations = metrics.NewCounter()
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storageOperationDurations = metrics.NewCounter()
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storageLatency = metrics.NewHistogram(diskLatencyHistogram)
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queueSizes = metrics.NewGauge()
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)
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func recordOutcome(duration time.Duration, err error, success, failure map[string]string) {
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labels := success
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if err != nil {
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labels = failure
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}
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storageOperations.Increment(labels)
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asFloat := float64(duration / time.Microsecond)
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storageLatency.Add(labels, asFloat)
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storageOperationDurations.IncrementBy(labels, asFloat)
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}
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func init() {
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registry.Register("prometheus_metric_disk_operations_total", "Total number of metric-related disk operations.", registry.NilLabels, storageOperations)
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registry.Register("prometheus_metric_disk_latency_microseconds", "Latency for metric disk operations in microseconds.", registry.NilLabels, storageLatency)
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registry.Register("prometheus_storage_operation_time_total_microseconds", "The total time spent performing a given storage operation.", registry.NilLabels, storageOperationDurations)
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registry.Register("prometheus_storage_queue_sizes_total", "The various sizes and capacities of the storage queues.", registry.NilLabels, queueSizes)
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registry.Register("curation_filter_operations_total", "The number of curation filter operations completed.", registry.NilLabels, curationFilterOperations)
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}
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