mirror of
https://github.com/prometheus/prometheus.git
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af91fb8e31
This is done by bucketing chunks by fingerprint. If the persisting to disk falls behind, more and more chunks are in the queue. As soon as there are "double hits", we will now persist both chunks in one go, doubling the disk throughput (assuming it is limited by disk seeks). Should even more pile up so that we end wit "triple hits", we will persist those first, and so on. Even if we have millions of time series, this will still help, assuming not all of them are growing with the same speed. Series that get many samples and/or are not very compressable will accumulate chunks faster, and they will soon get double- or triple-writes. To improve the chance of double writes, -storage.local.persistence-queue-capacity could be set to a higher value. However, that will slow down shutdown a lot (as the queue has to be worked through). So we leave it to the user to set it to a really high value. A more fundamental solution would be to checkpoint not only head chunks, but also chunks still in the persist queue. That would be quite complicated for a rather limited use-case (running many time series with high ingestion rate on slow spinning disks).
758 lines
22 KiB
Go
758 lines
22 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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"fmt"
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"math/rand"
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"reflect"
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"testing"
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"testing/quick"
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"time"
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"github.com/golang/glog"
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clientmodel "github.com/prometheus/client_golang/model"
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"github.com/prometheus/prometheus/storage/metric"
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"github.com/prometheus/prometheus/utility/test"
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)
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func TestGetFingerprintsForLabelMatchers(t *testing.T) {
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}
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// TestLoop is just a smoke test for the loop method, if we can switch it on and
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// off without disaster.
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func TestLoop(t *testing.T) {
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samples := make(clientmodel.Samples, 1000)
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for i := range samples {
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samples[i] = &clientmodel.Sample{
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Timestamp: clientmodel.Timestamp(2 * i),
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Value: clientmodel.SampleValue(float64(i) * 0.2),
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}
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}
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directory := test.NewTemporaryDirectory("test_storage", t)
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defer directory.Close()
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o := &MemorySeriesStorageOptions{
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MemoryChunks: 50,
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PersistenceRetentionPeriod: 24 * 7 * time.Hour,
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PersistenceStoragePath: directory.Path(),
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CheckpointInterval: 250 * time.Millisecond,
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}
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storage, err := NewMemorySeriesStorage(o)
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if err != nil {
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t.Fatalf("Error creating storage: %s", err)
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}
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storage.Start()
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storage.AppendSamples(samples)
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time.Sleep(time.Second)
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storage.Stop()
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}
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func TestChunk(t *testing.T) {
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samples := make(clientmodel.Samples, 500000)
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for i := range samples {
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samples[i] = &clientmodel.Sample{
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Timestamp: clientmodel.Timestamp(i),
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Value: clientmodel.SampleValue(float64(i) * 0.2),
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}
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}
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s, closer := NewTestStorage(t)
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defer closer.Close()
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s.AppendSamples(samples)
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s.WaitForIndexing()
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for m := range s.(*memorySeriesStorage).fpToSeries.iter() {
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s.(*memorySeriesStorage).fpLocker.Lock(m.fp)
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var values metric.Values
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for _, cd := range m.series.chunkDescs {
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if cd.isEvicted() {
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continue
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}
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for sample := range cd.chunk.values() {
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values = append(values, *sample)
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}
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}
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for i, v := range values {
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if samples[i].Timestamp != v.Timestamp {
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t.Errorf("%d. Got %v; want %v", i, v.Timestamp, samples[i].Timestamp)
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}
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if samples[i].Value != v.Value {
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t.Errorf("%d. Got %v; want %v", i, v.Value, samples[i].Value)
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}
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}
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s.(*memorySeriesStorage).fpLocker.Unlock(m.fp)
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}
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glog.Info("test done, closing")
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}
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func TestGetValueAtTime(t *testing.T) {
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samples := make(clientmodel.Samples, 1000)
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for i := range samples {
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samples[i] = &clientmodel.Sample{
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Timestamp: clientmodel.Timestamp(2 * i),
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Value: clientmodel.SampleValue(float64(i) * 0.2),
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}
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}
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s, closer := NewTestStorage(t)
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defer closer.Close()
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s.AppendSamples(samples)
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s.WaitForIndexing()
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fp := clientmodel.Metric{}.Fingerprint()
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it := s.NewIterator(fp)
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// #1 Exactly on a sample.
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for i, expected := range samples {
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actual := it.GetValueAtTime(expected.Timestamp)
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if len(actual) != 1 {
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t.Fatalf("1.%d. Expected exactly one result, got %d.", i, len(actual))
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}
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if expected.Timestamp != actual[0].Timestamp {
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t.Errorf("1.%d. Got %v; want %v", i, actual[0].Timestamp, expected.Timestamp)
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}
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if expected.Value != actual[0].Value {
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t.Errorf("1.%d. Got %v; want %v", i, actual[0].Value, expected.Value)
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}
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}
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// #2 Between samples.
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for i, expected1 := range samples {
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if i == len(samples)-1 {
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continue
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}
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expected2 := samples[i+1]
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actual := it.GetValueAtTime(expected1.Timestamp + 1)
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if len(actual) != 2 {
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t.Fatalf("2.%d. Expected exactly 2 results, got %d.", i, len(actual))
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}
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if expected1.Timestamp != actual[0].Timestamp {
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t.Errorf("2.%d. Got %v; want %v", i, actual[0].Timestamp, expected1.Timestamp)
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}
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if expected1.Value != actual[0].Value {
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t.Errorf("2.%d. Got %v; want %v", i, actual[0].Value, expected1.Value)
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}
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if expected2.Timestamp != actual[1].Timestamp {
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t.Errorf("2.%d. Got %v; want %v", i, actual[1].Timestamp, expected1.Timestamp)
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}
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if expected2.Value != actual[1].Value {
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t.Errorf("2.%d. Got %v; want %v", i, actual[1].Value, expected1.Value)
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}
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}
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// #3 Corner cases: Just before the first sample, just after the last.
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expected := samples[0]
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actual := it.GetValueAtTime(expected.Timestamp - 1)
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if len(actual) != 1 {
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t.Fatalf("3.1. Expected exactly one result, got %d.", len(actual))
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}
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if expected.Timestamp != actual[0].Timestamp {
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t.Errorf("3.1. Got %v; want %v", actual[0].Timestamp, expected.Timestamp)
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}
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if expected.Value != actual[0].Value {
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t.Errorf("3.1. Got %v; want %v", actual[0].Value, expected.Value)
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}
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expected = samples[len(samples)-1]
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actual = it.GetValueAtTime(expected.Timestamp + 1)
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if len(actual) != 1 {
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t.Fatalf("3.2. Expected exactly one result, got %d.", len(actual))
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}
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if expected.Timestamp != actual[0].Timestamp {
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t.Errorf("3.2. Got %v; want %v", actual[0].Timestamp, expected.Timestamp)
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}
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if expected.Value != actual[0].Value {
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t.Errorf("3.2. Got %v; want %v", actual[0].Value, expected.Value)
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}
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}
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func TestGetRangeValues(t *testing.T) {
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samples := make(clientmodel.Samples, 1000)
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for i := range samples {
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samples[i] = &clientmodel.Sample{
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Timestamp: clientmodel.Timestamp(2 * i),
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Value: clientmodel.SampleValue(float64(i) * 0.2),
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}
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}
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s, closer := NewTestStorage(t)
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defer closer.Close()
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s.AppendSamples(samples)
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s.WaitForIndexing()
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fp := clientmodel.Metric{}.Fingerprint()
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it := s.NewIterator(fp)
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// #1 Zero length interval at sample.
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for i, expected := range samples {
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actual := it.GetRangeValues(metric.Interval{
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OldestInclusive: expected.Timestamp,
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NewestInclusive: expected.Timestamp,
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})
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if len(actual) != 1 {
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t.Fatalf("1.%d. Expected exactly one result, got %d.", i, len(actual))
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}
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if expected.Timestamp != actual[0].Timestamp {
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t.Errorf("1.%d. Got %v; want %v.", i, actual[0].Timestamp, expected.Timestamp)
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}
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if expected.Value != actual[0].Value {
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t.Errorf("1.%d. Got %v; want %v.", i, actual[0].Value, expected.Value)
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}
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}
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// #2 Zero length interval off sample.
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for i, expected := range samples {
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actual := it.GetRangeValues(metric.Interval{
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OldestInclusive: expected.Timestamp + 1,
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NewestInclusive: expected.Timestamp + 1,
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})
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if len(actual) != 0 {
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t.Fatalf("2.%d. Expected no result, got %d.", i, len(actual))
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}
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}
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// #3 2sec interval around sample.
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for i, expected := range samples {
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actual := it.GetRangeValues(metric.Interval{
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OldestInclusive: expected.Timestamp - 1,
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NewestInclusive: expected.Timestamp + 1,
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})
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if len(actual) != 1 {
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t.Fatalf("3.%d. Expected exactly one result, got %d.", i, len(actual))
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}
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if expected.Timestamp != actual[0].Timestamp {
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t.Errorf("3.%d. Got %v; want %v.", i, actual[0].Timestamp, expected.Timestamp)
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}
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if expected.Value != actual[0].Value {
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t.Errorf("3.%d. Got %v; want %v.", i, actual[0].Value, expected.Value)
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}
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}
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// #4 2sec interval sample to sample.
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for i, expected1 := range samples {
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if i == len(samples)-1 {
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continue
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}
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expected2 := samples[i+1]
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actual := it.GetRangeValues(metric.Interval{
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OldestInclusive: expected1.Timestamp,
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NewestInclusive: expected1.Timestamp + 2,
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})
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if len(actual) != 2 {
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t.Fatalf("4.%d. Expected exactly 2 results, got %d.", i, len(actual))
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}
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if expected1.Timestamp != actual[0].Timestamp {
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t.Errorf("4.%d. Got %v for 1st result; want %v.", i, actual[0].Timestamp, expected1.Timestamp)
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}
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if expected1.Value != actual[0].Value {
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t.Errorf("4.%d. Got %v for 1st result; want %v.", i, actual[0].Value, expected1.Value)
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}
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if expected2.Timestamp != actual[1].Timestamp {
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t.Errorf("4.%d. Got %v for 2nd result; want %v.", i, actual[1].Timestamp, expected2.Timestamp)
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}
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if expected2.Value != actual[1].Value {
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t.Errorf("4.%d. Got %v for 2nd result; want %v.", i, actual[1].Value, expected2.Value)
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}
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}
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// #5 corner cases: Interval ends at first sample, interval starts
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// at last sample, interval entirely before/after samples.
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expected := samples[0]
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actual := it.GetRangeValues(metric.Interval{
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OldestInclusive: expected.Timestamp - 2,
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NewestInclusive: expected.Timestamp,
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})
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if len(actual) != 1 {
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t.Fatalf("5.1. Expected exactly one result, got %d.", len(actual))
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}
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if expected.Timestamp != actual[0].Timestamp {
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t.Errorf("5.1. Got %v; want %v.", actual[0].Timestamp, expected.Timestamp)
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}
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if expected.Value != actual[0].Value {
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t.Errorf("5.1. Got %v; want %v.", actual[0].Value, expected.Value)
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}
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expected = samples[len(samples)-1]
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actual = it.GetRangeValues(metric.Interval{
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OldestInclusive: expected.Timestamp,
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NewestInclusive: expected.Timestamp + 2,
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})
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if len(actual) != 1 {
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t.Fatalf("5.2. Expected exactly one result, got %d.", len(actual))
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}
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if expected.Timestamp != actual[0].Timestamp {
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t.Errorf("5.2. Got %v; want %v.", actual[0].Timestamp, expected.Timestamp)
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}
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if expected.Value != actual[0].Value {
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t.Errorf("5.2. Got %v; want %v.", actual[0].Value, expected.Value)
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}
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firstSample := samples[0]
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actual = it.GetRangeValues(metric.Interval{
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OldestInclusive: firstSample.Timestamp - 4,
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NewestInclusive: firstSample.Timestamp - 2,
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})
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if len(actual) != 0 {
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t.Fatalf("5.3. Expected no results, got %d.", len(actual))
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}
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lastSample := samples[len(samples)-1]
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actual = it.GetRangeValues(metric.Interval{
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OldestInclusive: lastSample.Timestamp + 2,
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NewestInclusive: lastSample.Timestamp + 4,
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})
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if len(actual) != 0 {
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t.Fatalf("5.3. Expected no results, got %d.", len(actual))
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}
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}
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func TestEvictAndPurgeSeries(t *testing.T) {
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samples := make(clientmodel.Samples, 1000)
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for i := range samples {
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samples[i] = &clientmodel.Sample{
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Timestamp: clientmodel.Timestamp(2 * i),
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Value: clientmodel.SampleValue(float64(i) * 0.2),
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}
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}
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s, closer := NewTestStorage(t)
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defer closer.Close()
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ms := s.(*memorySeriesStorage) // Going to test the internal purgeSeries method.
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s.AppendSamples(samples)
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s.WaitForIndexing()
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fp := clientmodel.Metric{}.Fingerprint()
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// Purge ~half of the chunks.
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ms.purgeSeries(fp, 1000)
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it := s.NewIterator(fp)
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actual := it.GetBoundaryValues(metric.Interval{
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OldestInclusive: 0,
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NewestInclusive: 10000,
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})
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if len(actual) != 2 {
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t.Fatal("expected two results after purging half of series")
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}
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if actual[0].Timestamp < 800 || actual[0].Timestamp > 1000 {
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t.Errorf("1st timestamp out of expected range: %v", actual[0].Timestamp)
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}
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want := clientmodel.Timestamp(1998)
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if actual[1].Timestamp != want {
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t.Errorf("2nd timestamp: want %v, got %v", want, actual[1].Timestamp)
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}
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// Purge everything.
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ms.purgeSeries(fp, 10000)
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it = s.NewIterator(fp)
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actual = it.GetBoundaryValues(metric.Interval{
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OldestInclusive: 0,
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NewestInclusive: 10000,
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})
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if len(actual) != 0 {
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t.Fatal("expected zero results after purging the whole series")
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}
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// Recreate series.
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s.AppendSamples(samples)
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s.WaitForIndexing()
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series, ok := ms.fpToSeries.get(fp)
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if !ok {
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t.Fatal("could not find series")
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}
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// Persist head chunk so we can safely archive.
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series.headChunkPersisted = true
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ms.persistQueue <- persistRequest{fp, series.head()}
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time.Sleep(time.Second) // Give time for persisting to happen.
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// Archive metrics.
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ms.fpToSeries.del(fp)
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if err := ms.persistence.archiveMetric(
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fp, series.metric, series.firstTime(), series.head().lastTime(),
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); err != nil {
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t.Fatal(err)
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}
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archived, _, _, err := ms.persistence.hasArchivedMetric(fp)
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if err != nil {
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t.Fatal(err)
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}
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if !archived {
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t.Fatal("not archived")
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}
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// Purge ~half of the chunks of an archived series.
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ms.purgeSeries(fp, 1000)
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archived, _, _, err = ms.persistence.hasArchivedMetric(fp)
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if err != nil {
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t.Fatal(err)
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}
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if !archived {
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t.Fatal("archived series dropped although only half of the chunks purged")
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}
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// Purge everything.
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ms.purgeSeries(fp, 10000)
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archived, _, _, err = ms.persistence.hasArchivedMetric(fp)
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if err != nil {
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t.Fatal(err)
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}
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if archived {
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t.Fatal("archived series not dropped")
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}
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}
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func BenchmarkAppend(b *testing.B) {
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samples := make(clientmodel.Samples, b.N)
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for i := range samples {
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samples[i] = &clientmodel.Sample{
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Metric: clientmodel.Metric{
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clientmodel.MetricNameLabel: clientmodel.LabelValue(fmt.Sprintf("test_metric_%d", i%10)),
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"label1": clientmodel.LabelValue(fmt.Sprintf("test_metric_%d", i%10)),
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"label2": clientmodel.LabelValue(fmt.Sprintf("test_metric_%d", i%10)),
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},
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Timestamp: clientmodel.Timestamp(i),
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Value: clientmodel.SampleValue(i),
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}
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}
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b.ResetTimer()
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s, closer := NewTestStorage(b)
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defer closer.Close()
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s.AppendSamples(samples)
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}
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// Append a large number of random samples and then check if we can get them out
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// of the storage alright.
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func TestFuzz(t *testing.T) {
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if testing.Short() {
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t.Skip("Skipping test in short mode.")
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}
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check := func(seed int64) bool {
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rand.Seed(seed)
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s, c := NewTestStorage(t)
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defer c.Close()
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samples := createRandomSamples()
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s.AppendSamples(samples)
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s.WaitForIndexing()
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return verifyStorage(t, s, samples, 24*7*time.Hour)
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}
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if err := quick.Check(check, nil); err != nil {
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t.Fatal(err)
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}
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}
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// BenchmarkFuzz is the benchmark version of TestFuzz. However, it will run
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// several append and verify operations in parallel, if GOMAXPROC is set
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// accordingly. Also, the storage options are set such that evictions,
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// checkpoints, and purging will happen concurrently, too. This benchmark will
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// have a very long runtime (up to minutes). You can use it as an actual
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// benchmark. Run it like this:
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//
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// go test -cpu 1,2,4,8 -short -bench BenchmarkFuzz -benchmem
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//
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// You can also use it as a test for races. In that case, run it like this (will
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// make things even slower):
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//
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// go test -race -cpu 8 -short -bench BenchmarkFuzz
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func BenchmarkFuzz(b *testing.B) {
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b.StopTimer()
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rand.Seed(42)
|
|
directory := test.NewTemporaryDirectory("test_storage", b)
|
|
defer directory.Close()
|
|
o := &MemorySeriesStorageOptions{
|
|
MemoryChunks: 100,
|
|
PersistenceRetentionPeriod: time.Hour,
|
|
PersistenceStoragePath: directory.Path(),
|
|
CheckpointInterval: 3 * time.Second,
|
|
}
|
|
s, err := NewMemorySeriesStorage(o)
|
|
if err != nil {
|
|
b.Fatalf("Error creating storage: %s", err)
|
|
}
|
|
s.Start()
|
|
defer s.Stop()
|
|
b.StartTimer()
|
|
|
|
b.RunParallel(func(pb *testing.PB) {
|
|
var allSamples clientmodel.Samples
|
|
for pb.Next() {
|
|
newSamples := createRandomSamples()
|
|
allSamples = append(allSamples, newSamples[:len(newSamples)/2]...)
|
|
s.AppendSamples(newSamples[:len(newSamples)/2])
|
|
verifyStorage(b, s, allSamples, o.PersistenceRetentionPeriod)
|
|
allSamples = append(allSamples, newSamples[len(newSamples)/2:]...)
|
|
s.AppendSamples(newSamples[len(newSamples)/2:])
|
|
verifyStorage(b, s, allSamples, o.PersistenceRetentionPeriod)
|
|
}
|
|
})
|
|
}
|
|
|
|
func createRandomSamples() clientmodel.Samples {
|
|
type valueCreator func() clientmodel.SampleValue
|
|
type deltaApplier func(clientmodel.SampleValue) clientmodel.SampleValue
|
|
|
|
var (
|
|
maxMetrics = 5
|
|
maxCycles = 500
|
|
maxStreakLength = 500
|
|
maxTimeDelta = 1000
|
|
maxTimeDeltaFactor = 10
|
|
timestamp = clientmodel.Now() - clientmodel.Timestamp(maxTimeDelta*maxTimeDeltaFactor*maxCycles*maxStreakLength/16) // So that some timestamps are in the future.
|
|
generators = []struct {
|
|
createValue valueCreator
|
|
applyDelta []deltaApplier
|
|
}{
|
|
{ // "Boolean".
|
|
createValue: func() clientmodel.SampleValue {
|
|
return clientmodel.SampleValue(rand.Intn(2))
|
|
},
|
|
applyDelta: []deltaApplier{
|
|
func(_ clientmodel.SampleValue) clientmodel.SampleValue {
|
|
return clientmodel.SampleValue(rand.Intn(2))
|
|
},
|
|
},
|
|
},
|
|
{ // Integer with int deltas of various byte length.
|
|
createValue: func() clientmodel.SampleValue {
|
|
return clientmodel.SampleValue(rand.Int63() - 1<<62)
|
|
},
|
|
applyDelta: []deltaApplier{
|
|
func(v clientmodel.SampleValue) clientmodel.SampleValue {
|
|
return clientmodel.SampleValue(rand.Intn(1<<8) - 1<<7 + int(v))
|
|
},
|
|
func(v clientmodel.SampleValue) clientmodel.SampleValue {
|
|
return clientmodel.SampleValue(rand.Intn(1<<16) - 1<<15 + int(v))
|
|
},
|
|
func(v clientmodel.SampleValue) clientmodel.SampleValue {
|
|
return clientmodel.SampleValue(rand.Intn(1<<32) - 1<<31 + int(v))
|
|
},
|
|
},
|
|
},
|
|
{ // Float with float32 and float64 deltas.
|
|
createValue: func() clientmodel.SampleValue {
|
|
return clientmodel.SampleValue(rand.NormFloat64())
|
|
},
|
|
applyDelta: []deltaApplier{
|
|
func(v clientmodel.SampleValue) clientmodel.SampleValue {
|
|
return v + clientmodel.SampleValue(float32(rand.NormFloat64()))
|
|
},
|
|
func(v clientmodel.SampleValue) clientmodel.SampleValue {
|
|
return v + clientmodel.SampleValue(rand.NormFloat64())
|
|
},
|
|
},
|
|
},
|
|
}
|
|
)
|
|
|
|
result := clientmodel.Samples{}
|
|
|
|
metrics := []clientmodel.Metric{}
|
|
for n := rand.Intn(maxMetrics); n >= 0; n-- {
|
|
metrics = append(metrics, clientmodel.Metric{
|
|
clientmodel.LabelName(fmt.Sprintf("labelname_%d", n+1)): clientmodel.LabelValue(fmt.Sprintf("labelvalue_%d", rand.Int())),
|
|
})
|
|
}
|
|
|
|
for n := rand.Intn(maxCycles); n >= 0; n-- {
|
|
// Pick a metric for this cycle.
|
|
metric := metrics[rand.Intn(len(metrics))]
|
|
timeDelta := rand.Intn(maxTimeDelta) + 1
|
|
generator := generators[rand.Intn(len(generators))]
|
|
createValue := generator.createValue
|
|
applyDelta := generator.applyDelta[rand.Intn(len(generator.applyDelta))]
|
|
incTimestamp := func() { timestamp += clientmodel.Timestamp(timeDelta * (rand.Intn(maxTimeDeltaFactor) + 1)) }
|
|
switch rand.Intn(4) {
|
|
case 0: // A single sample.
|
|
result = append(result, &clientmodel.Sample{
|
|
Metric: metric,
|
|
Value: createValue(),
|
|
Timestamp: timestamp,
|
|
})
|
|
incTimestamp()
|
|
case 1: // A streak of random sample values.
|
|
for n := rand.Intn(maxStreakLength); n >= 0; n-- {
|
|
result = append(result, &clientmodel.Sample{
|
|
Metric: metric,
|
|
Value: createValue(),
|
|
Timestamp: timestamp,
|
|
})
|
|
incTimestamp()
|
|
}
|
|
case 2: // A streak of sample values with incremental changes.
|
|
value := createValue()
|
|
for n := rand.Intn(maxStreakLength); n >= 0; n-- {
|
|
result = append(result, &clientmodel.Sample{
|
|
Metric: metric,
|
|
Value: value,
|
|
Timestamp: timestamp,
|
|
})
|
|
incTimestamp()
|
|
value = applyDelta(value)
|
|
}
|
|
case 3: // A streak of constant sample values.
|
|
value := createValue()
|
|
for n := rand.Intn(maxStreakLength); n >= 0; n-- {
|
|
result = append(result, &clientmodel.Sample{
|
|
Metric: metric,
|
|
Value: value,
|
|
Timestamp: timestamp,
|
|
})
|
|
incTimestamp()
|
|
}
|
|
}
|
|
}
|
|
|
|
return result
|
|
}
|
|
|
|
func verifyStorage(t testing.TB, s Storage, samples clientmodel.Samples, maxAge time.Duration) bool {
|
|
result := true
|
|
for _, i := range rand.Perm(len(samples)) {
|
|
sample := samples[i]
|
|
if sample.Timestamp.Before(clientmodel.TimestampFromTime(time.Now().Add(-maxAge))) {
|
|
continue
|
|
// TODO: Once we have a guaranteed cutoff at the
|
|
// retention period, we can verify here that no results
|
|
// are returned.
|
|
}
|
|
fp := sample.Metric.Fingerprint()
|
|
p := s.NewPreloader()
|
|
p.PreloadRange(fp, sample.Timestamp, sample.Timestamp, time.Hour)
|
|
found := s.NewIterator(fp).GetValueAtTime(sample.Timestamp)
|
|
if len(found) != 1 {
|
|
t.Errorf("Sample %#v: Expected exactly one value, found %d.", sample, len(found))
|
|
result = false
|
|
p.Close()
|
|
continue
|
|
}
|
|
want := float64(sample.Value)
|
|
got := float64(found[0].Value)
|
|
if want != got || sample.Timestamp != found[0].Timestamp {
|
|
t.Errorf(
|
|
"Value (or timestamp) mismatch, want %f (at time %v), got %f (at time %v).",
|
|
want, sample.Timestamp, got, found[0].Timestamp,
|
|
)
|
|
result = false
|
|
}
|
|
p.Close()
|
|
}
|
|
return result
|
|
}
|
|
|
|
func TestChunkMaps(t *testing.T) {
|
|
cm := chunkMaps{}
|
|
|
|
cd1 := &chunkDesc{refCount: 1} // Abuse refCount as identifier.
|
|
cd21 := &chunkDesc{refCount: 21}
|
|
cd22 := &chunkDesc{refCount: 22}
|
|
cd31 := &chunkDesc{refCount: 31}
|
|
cd32 := &chunkDesc{refCount: 32}
|
|
cd33 := &chunkDesc{refCount: 33}
|
|
cd41 := &chunkDesc{refCount: 41}
|
|
cd42 := &chunkDesc{refCount: 42}
|
|
cd43 := &chunkDesc{refCount: 43}
|
|
cd44 := &chunkDesc{refCount: 44}
|
|
cd51 := &chunkDesc{refCount: 51}
|
|
cd52 := &chunkDesc{refCount: 52}
|
|
cd53 := &chunkDesc{refCount: 53}
|
|
cd54 := &chunkDesc{refCount: 54}
|
|
cd55 := &chunkDesc{refCount: 55}
|
|
|
|
cm.add(5, cd51)
|
|
cm.add(3, cd31)
|
|
cm.add(5, cd52)
|
|
cm.add(1, cd1)
|
|
cm.add(4, cd41)
|
|
cm.add(4, cd42)
|
|
cm.add(5, cd53)
|
|
cm.add(3, cd32)
|
|
cm.add(2, cd21)
|
|
cm.add(5, cd54)
|
|
cm.add(3, cd33)
|
|
cm.add(4, cd43)
|
|
cm.add(2, cd22)
|
|
cm.add(4, cd44)
|
|
cm.add(5, cd55)
|
|
|
|
var fpWant, fpGot clientmodel.Fingerprint
|
|
var cdsWant, cdsGot []*chunkDesc
|
|
|
|
fpWant = 5
|
|
cdsWant = []*chunkDesc{cd51, cd52, cd53, cd54, cd55}
|
|
fpGot, cdsGot = cm.pop()
|
|
if fpWant != fpGot {
|
|
t.Errorf("Want fingerprint %s, got %s.", fpWant, fpGot)
|
|
}
|
|
if !reflect.DeepEqual(cdsWant, cdsGot) {
|
|
t.Errorf("Want chunk descriptors %v, got %v.", cdsWant, cdsGot)
|
|
}
|
|
|
|
fpWant = 4
|
|
cdsWant = []*chunkDesc{cd41, cd42, cd43, cd44}
|
|
fpGot, cdsGot = cm.pop()
|
|
if fpWant != fpGot {
|
|
t.Errorf("Want fingerprint %s, got %s.", fpWant, fpGot)
|
|
}
|
|
if !reflect.DeepEqual(cdsWant, cdsGot) {
|
|
t.Errorf("Want chunk descriptors %v, got %v.", cdsWant, cdsGot)
|
|
}
|
|
|
|
fpWant = 3
|
|
cdsWant = []*chunkDesc{cd31, cd32, cd33}
|
|
fpGot, cdsGot = cm.pop()
|
|
if fpWant != fpGot {
|
|
t.Errorf("Want fingerprint %s, got %s.", fpWant, fpGot)
|
|
}
|
|
if !reflect.DeepEqual(cdsWant, cdsGot) {
|
|
t.Errorf("Want chunk descriptors %v, got %v.", cdsWant, cdsGot)
|
|
}
|
|
|
|
fpWant = 2
|
|
cdsWant = []*chunkDesc{cd21, cd22}
|
|
fpGot, cdsGot = cm.pop()
|
|
if fpWant != fpGot {
|
|
t.Errorf("Want fingerprint %s, got %s.", fpWant, fpGot)
|
|
}
|
|
if !reflect.DeepEqual(cdsWant, cdsGot) {
|
|
t.Errorf("Want chunk descriptors %v, got %v.", cdsWant, cdsGot)
|
|
}
|
|
|
|
fpWant = 1
|
|
cdsWant = []*chunkDesc{cd1}
|
|
fpGot, cdsGot = cm.pop()
|
|
if fpWant != fpGot {
|
|
t.Errorf("Want fingerprint %s, got %s.", fpWant, fpGot)
|
|
}
|
|
if !reflect.DeepEqual(cdsWant, cdsGot) {
|
|
t.Errorf("Want chunk descriptors %v, got %v.", cdsWant, cdsGot)
|
|
}
|
|
|
|
}
|