client_golang/model/sample.go

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// 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 model
// Sample is a sample value with a timestamp and a metric.
type Sample struct {
Metric Metric
Value SampleValue
Add custom Timestamp type for sample times. So far we've been using Go's native time.Time for anything related to sample timestamps. Since the range of time.Time is much bigger than what we need, this has created two problems: - there could be time.Time values which were out of the range/precision of the time type that we persist to disk, therefore causing incorrectly ordered keys. One bug caused by this was: https://github.com/prometheus/prometheus/issues/367 It would be good to use a timestamp type that's more closely aligned with what the underlying storage supports. - sizeof(time.Time) is 192, while Prometheus should be ok with a single 64-bit Unix timestamp (possibly even a 32-bit one). Since we store samples in large numbers, this seriously affects memory usage. Furthermore, copying/working with the data will be faster if it's smaller. *MEMORY USAGE RESULTS* Initial memory usage comparisons for a running Prometheus with 1 timeseries and 100,000 samples show roughly a 13% decrease in total (VIRT) memory usage. In my tests, this advantage for some reason decreased a bit the more samples the timeseries had (to 5-7% for millions of samples). This I can't fully explain, but perhaps garbage collection issues were involved. *WHEN TO USE THE NEW TIMESTAMP TYPE* The new clientmodel.Timestamp type should be used whenever time calculations are either directly or indirectly related to sample timestamps. For example: - the timestamp of a sample itself - all kinds of watermarks - anything that may become or is compared to a sample timestamp (like the timestamp passed into Target.Scrape()). When to still use time.Time: - for measuring durations/times not related to sample timestamps, like duration telemetry exporting, timers that indicate how frequently to execute some action, etc. Change-Id: I253a467388774280c10400fda122369ff77c1730
2013-10-29 19:36:58 +04:00
Timestamp Timestamp
}
// Equal compares first the metrics, then the timestamp, then the value.
func (s *Sample) Equal(o *Sample) bool {
if s == o {
return true
}
if !s.Metric.Equal(o.Metric) {
return false
}
if !s.Timestamp.Equal(o.Timestamp) {
return false
}
if !s.Value.Equal(o.Value) {
return false
}
return true
}
// Samples is a sortable Sample slice. It implements sort.Interface.
type Samples []*Sample
func (s Samples) Len() int {
return len(s)
}
// Less compares first the metrics, then the timestamp.
func (s Samples) Less(i, j int) bool {
switch {
case s[i].Metric.Before(s[j].Metric):
return true
case s[j].Metric.Before(s[i].Metric):
return false
case s[i].Timestamp.Before(s[j].Timestamp):
return true
default:
return false
}
}
func (s Samples) Swap(i, j int) {
s[i], s[j] = s[j], s[i]
}
// Equal compares two sets of samples and returns true if they are equal.
func (s Samples) Equal(o Samples) bool {
if len(s) != len(o) {
return false
}
for i, sample := range s {
if !sample.Equal(o[i]) {
return false
}
}
return true
}