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Fix DropMetricsForFingerprints

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It now deletes the series file also for archived series.

Also, fix a naming error in a doc comment.
pull/1075/head
beorn7 9 years ago
parent d6ed1df4fb
commit daeccdd0e9
3 changed files with 58 additions and 24 deletions
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2
storage/local/persistence.go
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@ -1059,7 +1059,7 @@ func (p *persistence) indexMetric(fp model.Fingerprint, m model.Metric) {
// indexes used for fingerprintsForLabelPair, labelValuesForLabelName, and
// fingerprintsModifiedBefore. The index of fingerprints to archived metrics is
// not affected by this removal. (In fact, never call this method for an
// archived metric. To purge an archived metric, call purgeArchivedFingerprint.)
// archived metric. To purge an archived metric, call purgeArchivedMetric.)
// If the queue is full, this method blocks until the metric can be queued. This
// method is goroutine-safe.
func (p *persistence) unindexMetric(fp model.Fingerprint, m model.Metric) {

7
storage/local/storage.go
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@ -518,12 +518,13 @@ func (s *memorySeriesStorage) DropMetricsForFingerprints(fps ...model.Fingerprin
s.fpToSeries.del(fp)
s.numSeries.Dec()
s.persistence.unindexMetric(fp, series.metric)
if _, err := s.persistence.deleteSeriesFile(fp); err != nil {
log.Errorf("Error deleting series file for %v: %v", fp, err)
}
} else if err := s.persistence.purgeArchivedMetric(fp); err != nil {
log.Errorf("Error purging metric with fingerprint %v: %v", fp, err)
}
// Attempt to delete series file in any case.
if _, err := s.persistence.deleteSeriesFile(fp); err != nil {
log.Errorf("Error deleting series file for %v: %v", fp, err)
}
s.fpLocker.Unlock(fp)
}

73
storage/local/storage_test.go
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@ -17,6 +17,7 @@ import (
"fmt"
"hash/fnv"
"math/rand"
"os"
"reflect"
"testing"
"testing/quick"
@ -438,16 +439,29 @@ func TestDropMetrics(t *testing.T) {
s, closer := NewTestStorage(t, 1)
defer closer.Close()
chunkFileExists := func(fp model.Fingerprint) (bool, error) {
f, err := s.persistence.openChunkFileForReading(fp)
if err == nil {
f.Close()
return true, nil
}
if os.IsNotExist(err) {
return false, nil
}
return false, err
}
m1 := model.Metric{model.MetricNameLabel: "test", "n1": "v1"}
m2 := model.Metric{model.MetricNameLabel: "test", "n1": "v2"}
m3 := model.Metric{model.MetricNameLabel: "test", "n1": "v3"}
N := 120000
for j, m := range []model.Metric{m1, m2} {
for j, m := range []model.Metric{m1, m2, m3} {
for i := 0; i < N; i++ {
smpl := &model.Sample{
Metric: m,
Timestamp: insertStart.Add(time.Duration(i) * time.Millisecond), // 1 minute intervals.
Timestamp: insertStart.Add(time.Duration(i) * time.Millisecond), // 1 millisecond intervals.
Value: model.SampleValue(j),
}
s.Append(smpl)
@ -455,37 +469,49 @@ func TestDropMetrics(t *testing.T) {
}
s.WaitForIndexing()
fps := s.fingerprintsForLabelPairs(model.LabelPair{Name: model.MetricNameLabel, Value: "test"})
if len(fps) != 2 {
t.Fatalf("unexpected number of fingerprints: %d", len(fps))
// Archive m3, but first maintain it so that at least something is written to disk.
fpToBeArchived := m3.FastFingerprint()
s.maintainMemorySeries(fpToBeArchived, 0)
s.fpLocker.Lock(fpToBeArchived)
s.fpToSeries.del(fpToBeArchived)
if err := s.persistence.archiveMetric(
fpToBeArchived, m3, 0, insertStart.Add(time.Duration(N-1)*time.Millisecond),
); err != nil {
t.Error(err)
}
s.fpLocker.Unlock(fpToBeArchived)
var fpList model.Fingerprints
for fp := range fps {
it := s.NewIterator(fp)
if vals := it.RangeValues(metric.Interval{OldestInclusive: insertStart, NewestInclusive: now}); len(vals) != N {
t.Fatalf("unexpected number of samples: %d", len(vals))
}
fpList = append(fpList, fp)
fps := s.fingerprintsForLabelPairs(model.LabelPair{Name: model.MetricNameLabel, Value: "test"})
if len(fps) != 3 {
t.Errorf("unexpected number of fingerprints: %d", len(fps))
}
fpList := model.Fingerprints{m1.FastFingerprint(), m2.FastFingerprint(), fpToBeArchived}
s.DropMetricsForFingerprints(fpList[0])
s.WaitForIndexing()
fps2 := s.fingerprintsForLabelPairs(model.LabelPair{
Name: model.MetricNameLabel, Value: "test",
})
if len(fps2) != 1 {
t.Fatalf("unexpected number of fingerprints: %d", len(fps2))
if len(fps2) != 2 {
t.Errorf("unexpected number of fingerprints: %d", len(fps2))
}
it := s.NewIterator(fpList[0])
if vals := it.RangeValues(metric.Interval{OldestInclusive: insertStart, NewestInclusive: now}); len(vals) != 0 {
t.Fatalf("unexpected number of samples: %d", len(vals))
t.Errorf("unexpected number of samples: %d", len(vals))
}
it = s.NewIterator(fpList[1])
if vals := it.RangeValues(metric.Interval{OldestInclusive: insertStart, NewestInclusive: now}); len(vals) != N {
t.Fatalf("unexpected number of samples: %d", len(vals))
t.Errorf("unexpected number of samples: %d", len(vals))
}
exists, err := chunkFileExists(fpList[2])
if err != nil {
t.Fatal(err)
}
if !exists {
t.Errorf("chunk file does not exist for fp=%v", fpList[2])
}
s.DropMetricsForFingerprints(fpList...)
@ -495,16 +521,23 @@ func TestDropMetrics(t *testing.T) {
Name: model.MetricNameLabel, Value: "test",
})
if len(fps3) != 0 {
t.Fatalf("unexpected number of fingerprints: %d", len(fps3))
t.Errorf("unexpected number of fingerprints: %d", len(fps3))
}
it = s.NewIterator(fpList[0])
if vals := it.RangeValues(metric.Interval{OldestInclusive: insertStart, NewestInclusive: now}); len(vals) != 0 {
t.Fatalf("unexpected number of samples: %d", len(vals))
t.Errorf("unexpected number of samples: %d", len(vals))
}
it = s.NewIterator(fpList[1])
if vals := it.RangeValues(metric.Interval{OldestInclusive: insertStart, NewestInclusive: now}); len(vals) != 0 {
t.Fatalf("unexpected number of samples: %d", len(vals))
t.Errorf("unexpected number of samples: %d", len(vals))
}
exists, err = chunkFileExists(fpList[2])
if err != nil {
t.Fatal(err)
}
if exists {
t.Errorf("chunk file still exists for fp=%v", fpList[2])
}
}
@ -533,7 +566,7 @@ func TestLoop(t *testing.T) {
}
storage := NewMemorySeriesStorage(o)
if err := storage.Start(); err != nil {
t.Fatalf("Error starting storage: %s", err)
t.Errorf("Error starting storage: %s", err)
}
for _, s := range samples {
storage.Append(s)

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