VictoriaMetrics/lib/storage/storage_test.go

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2019-05-22 21:16:55 +00:00
package storage
import (
"fmt"
"math/rand"
"os"
"path/filepath"
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"reflect"
"sort"
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"strings"
"testing"
"testing/quick"
"time"
"github.com/VictoriaMetrics/VictoriaMetrics/lib/decimal"
"github.com/VictoriaMetrics/VictoriaMetrics/lib/fasttime"
"github.com/VictoriaMetrics/VictoriaMetrics/lib/uint64set"
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)
func TestReplaceAlternateRegexpsWithGraphiteWildcards(t *testing.T) {
f := func(q, resultExpected string) {
t.Helper()
result := replaceAlternateRegexpsWithGraphiteWildcards([]byte(q))
if string(result) != resultExpected {
t.Fatalf("unexpected result for %s\ngot\n%s\nwant\n%s", q, result, resultExpected)
}
}
f("", "")
f("foo", "foo")
f("foo(bar", "foo(bar")
f("foo.(bar|baz", "foo.(bar|baz")
f("foo.(bar).x", "foo.{bar}.x")
f("foo.(bar|baz).*.{x,y}", "foo.{bar,baz}.*.{x,y}")
f("foo.(bar|baz).*.{x,y}(z|aa)", "foo.{bar,baz}.*.{x,y}{z,aa}")
f("foo(.*)", "foo*")
}
func TestGetRegexpForGraphiteNodeQuery(t *testing.T) {
f := func(q, expectedRegexp string) {
t.Helper()
re, err := getRegexpForGraphiteQuery(q)
if err != nil {
t.Fatalf("unexpected error for query=%q: %s", q, err)
}
reStr := re.String()
if reStr != expectedRegexp {
t.Fatalf("unexpected regexp for query %q; got %q want %q", q, reStr, expectedRegexp)
}
}
f(``, `^$`)
f(`*`, `^[^.]*$`)
f(`foo.`, `^foo\.$`)
f(`foo.bar`, `^foo\.bar$`)
f(`{foo,b*ar,b[a-z]}`, `^(?:foo|b[^.]*ar|b[a-z])$`)
f(`[-a-zx.]`, `^[-a-zx.]$`)
f(`**`, `^[^.]*[^.]*$`)
f(`a*[de]{x,y}z`, `^a[^.]*[de](?:x|y)z$`)
f(`foo{bar`, `^foo\{bar$`)
f(`foo{ba,r`, `^foo\{ba,r$`)
f(`foo[bar`, `^foo\[bar$`)
f(`foo{bar}`, `^foobar$`)
f(`foo{bar,,b{{a,b*},z},[x-y]*z}a`, `^foo(?:bar||b(?:(?:a|b[^.]*)|z)|[x-y][^.]*z)a$`)
}
func TestDateMetricIDCacheSerial(t *testing.T) {
c := newDateMetricIDCache()
if err := testDateMetricIDCache(c, false); err != nil {
t.Fatalf("unexpected error: %s", err)
}
}
func TestDateMetricIDCacheConcurrent(t *testing.T) {
c := newDateMetricIDCache()
ch := make(chan error, 5)
for i := 0; i < 5; i++ {
go func() {
ch <- testDateMetricIDCache(c, true)
}()
}
for i := 0; i < 5; i++ {
select {
case err := <-ch:
if err != nil {
t.Fatalf("unexpected error: %s", err)
}
case <-time.After(time.Second * 5):
t.Fatalf("timeout")
}
}
}
func testDateMetricIDCache(c *dateMetricIDCache, concurrent bool) error {
type dmk struct {
lib/storage: pre-create timeseries before indexDB rotation (#4652) * lib/storage: pre-create timeseries before indexDB rotation during an hour before indexDB rotation start creating records at the next indexDB it must improve performance during switch for the next indexDB and remove ingestion issues. Since there is no need for creation new index records for timeseries already ingested into current indexDB https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4563 * lib/storage: further work on indexdb rotation optimization - Document the change at docs/CHAGNELOG.md - Move back various caches from indexDB to Storage. This makes the change less intrusive. The dateMetricIDCache now takes into account indexDB generation, so it stores (date, metricID) entries for both the current and the next indexDB. - Consolidate the code responsible for idbNext pre-filling into prefillNextIndexDB() function. This improves code readability and maintainability a bit. - Rewrite and simplify the code responsible for calculating the next retention timestamp. Add various tests for corner cases of this code. - Remove indexdb pre-filling from RegisterMetricNames() function, since this function is rarely called. It is OK to add indexdb entries on demand in this function. This simplifies the code. Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1401 * docs/CHANGELOG.md: refer to https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4563 --------- Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
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generation uint64
date uint64
metricID uint64
}
m := make(map[dmk]bool)
for i := 0; i < 1e5; i++ {
lib/storage: pre-create timeseries before indexDB rotation (#4652) * lib/storage: pre-create timeseries before indexDB rotation during an hour before indexDB rotation start creating records at the next indexDB it must improve performance during switch for the next indexDB and remove ingestion issues. Since there is no need for creation new index records for timeseries already ingested into current indexDB https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4563 * lib/storage: further work on indexdb rotation optimization - Document the change at docs/CHAGNELOG.md - Move back various caches from indexDB to Storage. This makes the change less intrusive. The dateMetricIDCache now takes into account indexDB generation, so it stores (date, metricID) entries for both the current and the next indexDB. - Consolidate the code responsible for idbNext pre-filling into prefillNextIndexDB() function. This improves code readability and maintainability a bit. - Rewrite and simplify the code responsible for calculating the next retention timestamp. Add various tests for corner cases of this code. - Remove indexdb pre-filling from RegisterMetricNames() function, since this function is rarely called. It is OK to add indexdb entries on demand in this function. This simplifies the code. Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1401 * docs/CHANGELOG.md: refer to https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4563 --------- Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
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generation := uint64(i) % 2
date := uint64(i) % 3
metricID := uint64(i) % 1237
lib/storage: pre-create timeseries before indexDB rotation (#4652) * lib/storage: pre-create timeseries before indexDB rotation during an hour before indexDB rotation start creating records at the next indexDB it must improve performance during switch for the next indexDB and remove ingestion issues. Since there is no need for creation new index records for timeseries already ingested into current indexDB https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4563 * lib/storage: further work on indexdb rotation optimization - Document the change at docs/CHAGNELOG.md - Move back various caches from indexDB to Storage. This makes the change less intrusive. The dateMetricIDCache now takes into account indexDB generation, so it stores (date, metricID) entries for both the current and the next indexDB. - Consolidate the code responsible for idbNext pre-filling into prefillNextIndexDB() function. This improves code readability and maintainability a bit. - Rewrite and simplify the code responsible for calculating the next retention timestamp. Add various tests for corner cases of this code. - Remove indexdb pre-filling from RegisterMetricNames() function, since this function is rarely called. It is OK to add indexdb entries on demand in this function. This simplifies the code. Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1401 * docs/CHANGELOG.md: refer to https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4563 --------- Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
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if !concurrent && c.Has(generation, date, metricID) {
if !m[dmk{generation, date, metricID}] {
return fmt.Errorf("c.Has(%d, %d, %d) must return false, but returned true", generation, date, metricID)
}
continue
}
lib/storage: pre-create timeseries before indexDB rotation (#4652) * lib/storage: pre-create timeseries before indexDB rotation during an hour before indexDB rotation start creating records at the next indexDB it must improve performance during switch for the next indexDB and remove ingestion issues. Since there is no need for creation new index records for timeseries already ingested into current indexDB https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4563 * lib/storage: further work on indexdb rotation optimization - Document the change at docs/CHAGNELOG.md - Move back various caches from indexDB to Storage. This makes the change less intrusive. The dateMetricIDCache now takes into account indexDB generation, so it stores (date, metricID) entries for both the current and the next indexDB. - Consolidate the code responsible for idbNext pre-filling into prefillNextIndexDB() function. This improves code readability and maintainability a bit. - Rewrite and simplify the code responsible for calculating the next retention timestamp. Add various tests for corner cases of this code. - Remove indexdb pre-filling from RegisterMetricNames() function, since this function is rarely called. It is OK to add indexdb entries on demand in this function. This simplifies the code. Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1401 * docs/CHANGELOG.md: refer to https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4563 --------- Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
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c.Set(generation, date, metricID)
m[dmk{generation, date, metricID}] = true
if !concurrent && !c.Has(generation, date, metricID) {
return fmt.Errorf("c.Has(%d, %d, %d) must return true, but returned false", generation, date, metricID)
}
if i%11234 == 0 {
c.mu.Lock()
c.syncLocked()
c.mu.Unlock()
}
if i%34323 == 0 {
lib/storage: pre-create timeseries before indexDB rotation (#4652) * lib/storage: pre-create timeseries before indexDB rotation during an hour before indexDB rotation start creating records at the next indexDB it must improve performance during switch for the next indexDB and remove ingestion issues. Since there is no need for creation new index records for timeseries already ingested into current indexDB https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4563 * lib/storage: further work on indexdb rotation optimization - Document the change at docs/CHAGNELOG.md - Move back various caches from indexDB to Storage. This makes the change less intrusive. The dateMetricIDCache now takes into account indexDB generation, so it stores (date, metricID) entries for both the current and the next indexDB. - Consolidate the code responsible for idbNext pre-filling into prefillNextIndexDB() function. This improves code readability and maintainability a bit. - Rewrite and simplify the code responsible for calculating the next retention timestamp. Add various tests for corner cases of this code. - Remove indexdb pre-filling from RegisterMetricNames() function, since this function is rarely called. It is OK to add indexdb entries on demand in this function. This simplifies the code. Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1401 * docs/CHANGELOG.md: refer to https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4563 --------- Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
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c.mu.Lock()
c.resetLocked()
c.mu.Unlock()
m = make(map[dmk]bool)
}
}
// Verify fast path after sync.
for i := 0; i < 1e5; i++ {
lib/storage: pre-create timeseries before indexDB rotation (#4652) * lib/storage: pre-create timeseries before indexDB rotation during an hour before indexDB rotation start creating records at the next indexDB it must improve performance during switch for the next indexDB and remove ingestion issues. Since there is no need for creation new index records for timeseries already ingested into current indexDB https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4563 * lib/storage: further work on indexdb rotation optimization - Document the change at docs/CHAGNELOG.md - Move back various caches from indexDB to Storage. This makes the change less intrusive. The dateMetricIDCache now takes into account indexDB generation, so it stores (date, metricID) entries for both the current and the next indexDB. - Consolidate the code responsible for idbNext pre-filling into prefillNextIndexDB() function. This improves code readability and maintainability a bit. - Rewrite and simplify the code responsible for calculating the next retention timestamp. Add various tests for corner cases of this code. - Remove indexdb pre-filling from RegisterMetricNames() function, since this function is rarely called. It is OK to add indexdb entries on demand in this function. This simplifies the code. Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1401 * docs/CHANGELOG.md: refer to https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4563 --------- Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
2023-07-22 22:20:21 +00:00
generation := uint64(i) % 2
date := uint64(i) % 3
metricID := uint64(i) % 123
lib/storage: pre-create timeseries before indexDB rotation (#4652) * lib/storage: pre-create timeseries before indexDB rotation during an hour before indexDB rotation start creating records at the next indexDB it must improve performance during switch for the next indexDB and remove ingestion issues. Since there is no need for creation new index records for timeseries already ingested into current indexDB https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4563 * lib/storage: further work on indexdb rotation optimization - Document the change at docs/CHAGNELOG.md - Move back various caches from indexDB to Storage. This makes the change less intrusive. The dateMetricIDCache now takes into account indexDB generation, so it stores (date, metricID) entries for both the current and the next indexDB. - Consolidate the code responsible for idbNext pre-filling into prefillNextIndexDB() function. This improves code readability and maintainability a bit. - Rewrite and simplify the code responsible for calculating the next retention timestamp. Add various tests for corner cases of this code. - Remove indexdb pre-filling from RegisterMetricNames() function, since this function is rarely called. It is OK to add indexdb entries on demand in this function. This simplifies the code. Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1401 * docs/CHANGELOG.md: refer to https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4563 --------- Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
2023-07-22 22:20:21 +00:00
c.Set(generation, date, metricID)
}
c.mu.Lock()
c.syncLocked()
c.mu.Unlock()
for i := 0; i < 1e5; i++ {
lib/storage: pre-create timeseries before indexDB rotation (#4652) * lib/storage: pre-create timeseries before indexDB rotation during an hour before indexDB rotation start creating records at the next indexDB it must improve performance during switch for the next indexDB and remove ingestion issues. Since there is no need for creation new index records for timeseries already ingested into current indexDB https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4563 * lib/storage: further work on indexdb rotation optimization - Document the change at docs/CHAGNELOG.md - Move back various caches from indexDB to Storage. This makes the change less intrusive. The dateMetricIDCache now takes into account indexDB generation, so it stores (date, metricID) entries for both the current and the next indexDB. - Consolidate the code responsible for idbNext pre-filling into prefillNextIndexDB() function. This improves code readability and maintainability a bit. - Rewrite and simplify the code responsible for calculating the next retention timestamp. Add various tests for corner cases of this code. - Remove indexdb pre-filling from RegisterMetricNames() function, since this function is rarely called. It is OK to add indexdb entries on demand in this function. This simplifies the code. Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1401 * docs/CHANGELOG.md: refer to https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4563 --------- Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
2023-07-22 22:20:21 +00:00
generation := uint64(i) % 2
date := uint64(i) % 3
metricID := uint64(i) % 123
lib/storage: pre-create timeseries before indexDB rotation (#4652) * lib/storage: pre-create timeseries before indexDB rotation during an hour before indexDB rotation start creating records at the next indexDB it must improve performance during switch for the next indexDB and remove ingestion issues. Since there is no need for creation new index records for timeseries already ingested into current indexDB https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4563 * lib/storage: further work on indexdb rotation optimization - Document the change at docs/CHAGNELOG.md - Move back various caches from indexDB to Storage. This makes the change less intrusive. The dateMetricIDCache now takes into account indexDB generation, so it stores (date, metricID) entries for both the current and the next indexDB. - Consolidate the code responsible for idbNext pre-filling into prefillNextIndexDB() function. This improves code readability and maintainability a bit. - Rewrite and simplify the code responsible for calculating the next retention timestamp. Add various tests for corner cases of this code. - Remove indexdb pre-filling from RegisterMetricNames() function, since this function is rarely called. It is OK to add indexdb entries on demand in this function. This simplifies the code. Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1401 * docs/CHANGELOG.md: refer to https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4563 --------- Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
2023-07-22 22:20:21 +00:00
if !concurrent && !c.Has(generation, date, metricID) {
return fmt.Errorf("c.Has(%d, %d, %d) must return true after sync", generation, date, metricID)
}
}
// Verify c.Reset
if n := c.EntriesCount(); !concurrent && n < 123 {
return fmt.Errorf("c.EntriesCount must return at least 123; returned %d", n)
}
lib/storage: pre-create timeseries before indexDB rotation (#4652) * lib/storage: pre-create timeseries before indexDB rotation during an hour before indexDB rotation start creating records at the next indexDB it must improve performance during switch for the next indexDB and remove ingestion issues. Since there is no need for creation new index records for timeseries already ingested into current indexDB https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4563 * lib/storage: further work on indexdb rotation optimization - Document the change at docs/CHAGNELOG.md - Move back various caches from indexDB to Storage. This makes the change less intrusive. The dateMetricIDCache now takes into account indexDB generation, so it stores (date, metricID) entries for both the current and the next indexDB. - Consolidate the code responsible for idbNext pre-filling into prefillNextIndexDB() function. This improves code readability and maintainability a bit. - Rewrite and simplify the code responsible for calculating the next retention timestamp. Add various tests for corner cases of this code. - Remove indexdb pre-filling from RegisterMetricNames() function, since this function is rarely called. It is OK to add indexdb entries on demand in this function. This simplifies the code. Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1401 * docs/CHANGELOG.md: refer to https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4563 --------- Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
2023-07-22 22:20:21 +00:00
c.mu.Lock()
c.resetLocked()
c.mu.Unlock()
if n := c.EntriesCount(); !concurrent && n > 0 {
return fmt.Errorf("c.EntriesCount must return 0 after reset; returned %d", n)
}
return nil
}
func TestUpdateCurrHourMetricIDs(t *testing.T) {
newStorage := func() *Storage {
var s Storage
s.currHourMetricIDs.Store(&hourMetricIDs{})
s.prevHourMetricIDs.Store(&hourMetricIDs{})
return &s
}
t.Run("empty_pending_metric_ids_stale_curr_hour", func(t *testing.T) {
s := newStorage()
hour := fasttime.UnixHour()
if hour%24 == 0 {
hour++
}
hmOrig := &hourMetricIDs{
m: &uint64set.Set{},
hour: hour - 1,
}
hmOrig.m.Add(12)
hmOrig.m.Add(34)
s.currHourMetricIDs.Store(hmOrig)
s.updateCurrHourMetricIDs(hour)
hmCurr := s.currHourMetricIDs.Load()
if hmCurr.hour != hour {
2019-11-11 22:16:42 +00:00
// It is possible new hour occurred. Update the hour and verify it again.
hour = uint64(timestampFromTime(time.Now())) / msecPerHour
if hmCurr.hour != hour {
t.Fatalf("unexpected hmCurr.hour; got %d; want %d", hmCurr.hour, hour)
}
}
if hmCurr.m.Len() != 0 {
t.Fatalf("unexpected length of hm.m; got %d; want %d", hmCurr.m.Len(), 0)
}
hmPrev := s.prevHourMetricIDs.Load()
if !reflect.DeepEqual(hmPrev, hmOrig) {
t.Fatalf("unexpected hmPrev; got %v; want %v", hmPrev, hmOrig)
}
if len(s.pendingHourEntries) != 0 {
t.Fatalf("unexpected len(s.pendingHourEntries); got %d; want %d", len(s.pendingHourEntries), 0)
}
})
t.Run("empty_pending_metric_ids_valid_curr_hour", func(t *testing.T) {
s := newStorage()
hour := fasttime.UnixHour()
hmOrig := &hourMetricIDs{
m: &uint64set.Set{},
hour: hour,
}
hmOrig.m.Add(12)
hmOrig.m.Add(34)
s.currHourMetricIDs.Store(hmOrig)
s.updateCurrHourMetricIDs(hour)
hmCurr := s.currHourMetricIDs.Load()
if hmCurr.hour != hour {
2019-11-11 22:16:42 +00:00
// It is possible new hour occurred. Update the hour and verify it again.
hour = uint64(timestampFromTime(time.Now())) / msecPerHour
if hmCurr.hour != hour {
t.Fatalf("unexpected hmCurr.hour; got %d; want %d", hmCurr.hour, hour)
}
// Do not run other checks, since they may fail.
return
}
if !reflect.DeepEqual(hmCurr, hmOrig) {
t.Fatalf("unexpected hmCurr; got %v; want %v", hmCurr, hmOrig)
}
hmPrev := s.prevHourMetricIDs.Load()
hmEmpty := &hourMetricIDs{}
if !reflect.DeepEqual(hmPrev, hmEmpty) {
t.Fatalf("unexpected hmPrev; got %v; want %v", hmPrev, hmEmpty)
}
if len(s.pendingHourEntries) != 0 {
t.Fatalf("unexpected len(s.pendingHourEntries); got %d; want %d", len(s.pendingHourEntries), 0)
}
})
t.Run("nonempty_pending_metric_ids_stale_curr_hour", func(t *testing.T) {
s := newStorage()
s.pendingHourEntries = []pendingHourMetricIDEntry{
{AccountID: 123, ProjectID: 431, MetricID: 343},
{AccountID: 123, ProjectID: 431, MetricID: 32424},
{AccountID: 1, ProjectID: 2, MetricID: 8293432},
}
mExpected := &uint64set.Set{}
for _, e := range s.pendingHourEntries {
mExpected.Add(e.MetricID)
}
byTenantExpected := make(map[accountProjectKey]*uint64set.Set)
for _, e := range s.pendingHourEntries {
k := accountProjectKey{
AccountID: e.AccountID,
ProjectID: e.ProjectID,
}
x := byTenantExpected[k]
if x == nil {
x = &uint64set.Set{}
byTenantExpected[k] = x
}
x.Add(e.MetricID)
}
hour := fasttime.UnixHour()
if hour%24 == 0 {
hour++
}
hmOrig := &hourMetricIDs{
m: &uint64set.Set{},
hour: hour - 1,
}
hmOrig.m.Add(12)
hmOrig.m.Add(34)
s.currHourMetricIDs.Store(hmOrig)
s.updateCurrHourMetricIDs(hour)
hmCurr := s.currHourMetricIDs.Load()
if hmCurr.hour != hour {
2019-11-11 22:16:42 +00:00
// It is possible new hour occurred. Update the hour and verify it again.
hour = uint64(timestampFromTime(time.Now())) / msecPerHour
if hmCurr.hour != hour {
t.Fatalf("unexpected hmCurr.hour; got %d; want %d", hmCurr.hour, hour)
}
}
if !hmCurr.m.Equal(mExpected) {
t.Fatalf("unexpected hm.m; got %v; want %v", hmCurr.m, mExpected)
}
if !reflect.DeepEqual(hmCurr.byTenant, byTenantExpected) {
t.Fatalf("unexpected hmPrev.byTenant; got %v; want %v", hmCurr.byTenant, byTenantExpected)
}
hmPrev := s.prevHourMetricIDs.Load()
if !reflect.DeepEqual(hmPrev, hmOrig) {
t.Fatalf("unexpected hmPrev; got %v; want %v", hmPrev, hmOrig)
}
if len(s.pendingHourEntries) != 0 {
t.Fatalf("unexpected len(s.pendingHourEntries); got %d; want %d", len(s.pendingHourEntries), 0)
}
})
t.Run("nonempty_pending_metric_ids_valid_curr_hour", func(t *testing.T) {
s := newStorage()
s.pendingHourEntries = []pendingHourMetricIDEntry{
{AccountID: 123, ProjectID: 431, MetricID: 343},
{AccountID: 123, ProjectID: 431, MetricID: 32424},
{AccountID: 1, ProjectID: 2, MetricID: 8293432},
}
mExpected := &uint64set.Set{}
for _, e := range s.pendingHourEntries {
mExpected.Add(e.MetricID)
}
byTenantExpected := make(map[accountProjectKey]*uint64set.Set)
for _, e := range s.pendingHourEntries {
k := accountProjectKey{
AccountID: e.AccountID,
ProjectID: e.ProjectID,
}
x := byTenantExpected[k]
if x == nil {
x = &uint64set.Set{}
byTenantExpected[k] = x
}
x.Add(e.MetricID)
}
hour := fasttime.UnixHour()
hmOrig := &hourMetricIDs{
m: &uint64set.Set{},
hour: hour,
}
hmOrig.m.Add(12)
hmOrig.m.Add(34)
s.currHourMetricIDs.Store(hmOrig)
s.updateCurrHourMetricIDs(hour)
hmCurr := s.currHourMetricIDs.Load()
if hmCurr.hour != hour {
// It is possible new hour occurred. Update the hour and verify it again.
hour = uint64(timestampFromTime(time.Now())) / msecPerHour
if hmCurr.hour != hour {
t.Fatalf("unexpected hmCurr.hour; got %d; want %d", hmCurr.hour, hour)
}
// Do not run other checks, since they may fail.
return
}
m := mExpected.Clone()
hmOrig.m.ForEach(func(part []uint64) bool {
for _, metricID := range part {
m.Add(metricID)
}
return true
})
if !hmCurr.m.Equal(m) {
t.Fatalf("unexpected hm.m; got %v; want %v", hmCurr.m, m)
}
if !reflect.DeepEqual(hmCurr.byTenant, byTenantExpected) {
t.Fatalf("unexpected hmPrev.byTenant; got %v; want %v", hmCurr.byTenant, byTenantExpected)
}
hmPrev := s.prevHourMetricIDs.Load()
hmEmpty := &hourMetricIDs{}
if !reflect.DeepEqual(hmPrev, hmEmpty) {
t.Fatalf("unexpected hmPrev; got %v; want %v", hmPrev, hmEmpty)
}
if len(s.pendingHourEntries) != 0 {
t.Fatalf("unexpected s.pendingHourEntries.Len(); got %d; want %d", len(s.pendingHourEntries), 0)
}
})
t.Run("nonempty_pending_metric_ids_valid_curr_hour_start_of_day", func(t *testing.T) {
s := newStorage()
s.pendingHourEntries = []pendingHourMetricIDEntry{
{AccountID: 123, ProjectID: 431, MetricID: 343},
{AccountID: 123, ProjectID: 431, MetricID: 32424},
{AccountID: 1, ProjectID: 2, MetricID: 8293432},
}
mExpected := &uint64set.Set{}
for _, e := range s.pendingHourEntries {
mExpected.Add(e.MetricID)
}
byTenantExpected := make(map[accountProjectKey]*uint64set.Set)
for _, e := range s.pendingHourEntries {
k := accountProjectKey{
AccountID: e.AccountID,
ProjectID: e.ProjectID,
}
x := byTenantExpected[k]
if x == nil {
x = &uint64set.Set{}
byTenantExpected[k] = x
}
x.Add(e.MetricID)
}
hour := fasttime.UnixHour()
hour -= hour % 24
hmOrig := &hourMetricIDs{
m: &uint64set.Set{},
hour: hour,
}
hmOrig.m.Add(12)
hmOrig.m.Add(34)
s.currHourMetricIDs.Store(hmOrig)
s.updateCurrHourMetricIDs(hour)
hmCurr := s.currHourMetricIDs.Load()
if hmCurr.hour != hour {
2019-11-11 22:16:42 +00:00
// It is possible new hour occurred. Update the hour and verify it again.
hour = uint64(timestampFromTime(time.Now())) / msecPerHour
if hmCurr.hour != hour {
t.Fatalf("unexpected hmCurr.hour; got %d; want %d", hmCurr.hour, hour)
}
// Do not run other checks, since they may fail.
return
}
m := mExpected.Clone()
hmOrig.m.ForEach(func(part []uint64) bool {
for _, metricID := range part {
m.Add(metricID)
}
return true
})
if !hmCurr.m.Equal(m) {
t.Fatalf("unexpected hm.m; got %v; want %v", hmCurr.m, m)
}
if !reflect.DeepEqual(hmCurr.byTenant, byTenantExpected) {
t.Fatalf("unexpected hmPrev.byTenant; got %v; want %v", hmCurr.byTenant, byTenantExpected)
}
hmPrev := s.prevHourMetricIDs.Load()
hmEmpty := &hourMetricIDs{}
if !reflect.DeepEqual(hmPrev, hmEmpty) {
t.Fatalf("unexpected hmPrev; got %v; want %v", hmPrev, hmEmpty)
}
if len(s.pendingHourEntries) != 0 {
t.Fatalf("unexpected s.pendingHourEntries.Len(); got %d; want %d", len(s.pendingHourEntries), 0)
}
})
t.Run("nonempty_pending_metric_ids_from_previous_hour_new_day", func(t *testing.T) {
s := newStorage()
hour := fasttime.UnixHour()
hour -= hour % 24
s.pendingHourEntries = []pendingHourMetricIDEntry{
{AccountID: 123, ProjectID: 431, MetricID: 343},
{AccountID: 123, ProjectID: 431, MetricID: 32424},
{AccountID: 1, ProjectID: 2, MetricID: 8293432},
}
hmOrig := &hourMetricIDs{
m: &uint64set.Set{},
hour: hour - 1,
}
s.currHourMetricIDs.Store(hmOrig)
s.updateCurrHourMetricIDs(hour)
hmCurr := s.currHourMetricIDs.Load()
if hmCurr.hour != hour {
t.Fatalf("unexpected hmCurr.hour; got %d; want %d", hmCurr.hour, hour)
}
if hmCurr.m.Len() != 0 {
t.Fatalf("unexpected non-empty hmCurr.m; got %v", hmCurr.m.AppendTo(nil))
}
byTenantExpected := make(map[accountProjectKey]*uint64set.Set)
if !reflect.DeepEqual(hmCurr.byTenant, byTenantExpected) {
t.Fatalf("unexpected hmPrev.byTenant; got %v; want %v", hmCurr.byTenant, byTenantExpected)
}
hmPrev := s.prevHourMetricIDs.Load()
if !reflect.DeepEqual(hmPrev, hmOrig) {
t.Fatalf("unexpected hmPrev; got %v; want %v", hmPrev, hmOrig)
}
if len(s.pendingHourEntries) != 0 {
t.Fatalf("unexpected s.pendingHourEntries.Len(); got %d; want %d", len(s.pendingHourEntries), 0)
}
})
}
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func TestMetricRowMarshalUnmarshal(t *testing.T) {
var buf []byte
typ := reflect.TypeOf(&MetricRow{})
rng := rand.New(rand.NewSource(1))
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for i := 0; i < 1000; i++ {
v, ok := quick.Value(typ, rng)
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if !ok {
t.Fatalf("cannot create random MetricRow via quick.Value")
}
mr1 := v.Interface().(*MetricRow)
if mr1 == nil {
continue
}
buf = mr1.Marshal(buf[:0])
var mr2 MetricRow
tail, err := mr2.UnmarshalX(buf)
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if err != nil {
t.Fatalf("cannot unmarshal mr1=%s: %s", mr1, err)
}
if len(tail) > 0 {
t.Fatalf("non-empty tail returned after MetricRow.Unmarshal for mr1=%s", mr1)
}
if mr1.MetricNameRaw == nil {
mr1.MetricNameRaw = []byte{}
}
if mr2.MetricNameRaw == nil {
mr2.MetricNameRaw = []byte{}
}
if !reflect.DeepEqual(mr1, &mr2) {
t.Fatalf("mr1 should match mr2; got\nmr1=%s\nmr2=%s", mr1, &mr2)
}
}
}
lib/storage: pre-create timeseries before indexDB rotation (#4652) * lib/storage: pre-create timeseries before indexDB rotation during an hour before indexDB rotation start creating records at the next indexDB it must improve performance during switch for the next indexDB and remove ingestion issues. Since there is no need for creation new index records for timeseries already ingested into current indexDB https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4563 * lib/storage: further work on indexdb rotation optimization - Document the change at docs/CHAGNELOG.md - Move back various caches from indexDB to Storage. This makes the change less intrusive. The dateMetricIDCache now takes into account indexDB generation, so it stores (date, metricID) entries for both the current and the next indexDB. - Consolidate the code responsible for idbNext pre-filling into prefillNextIndexDB() function. This improves code readability and maintainability a bit. - Rewrite and simplify the code responsible for calculating the next retention timestamp. Add various tests for corner cases of this code. - Remove indexdb pre-filling from RegisterMetricNames() function, since this function is rarely called. It is OK to add indexdb entries on demand in this function. This simplifies the code. Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1401 * docs/CHANGELOG.md: refer to https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4563 --------- Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
2023-07-22 22:20:21 +00:00
func TestNextRetentionDeadlineSeconds(t *testing.T) {
f := func(currentTime string, retention, offset time.Duration, deadlineExpected string) {
t.Helper()
lib/storage: pre-create timeseries before indexDB rotation (#4652) * lib/storage: pre-create timeseries before indexDB rotation during an hour before indexDB rotation start creating records at the next indexDB it must improve performance during switch for the next indexDB and remove ingestion issues. Since there is no need for creation new index records for timeseries already ingested into current indexDB https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4563 * lib/storage: further work on indexdb rotation optimization - Document the change at docs/CHAGNELOG.md - Move back various caches from indexDB to Storage. This makes the change less intrusive. The dateMetricIDCache now takes into account indexDB generation, so it stores (date, metricID) entries for both the current and the next indexDB. - Consolidate the code responsible for idbNext pre-filling into prefillNextIndexDB() function. This improves code readability and maintainability a bit. - Rewrite and simplify the code responsible for calculating the next retention timestamp. Add various tests for corner cases of this code. - Remove indexdb pre-filling from RegisterMetricNames() function, since this function is rarely called. It is OK to add indexdb entries on demand in this function. This simplifies the code. Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1401 * docs/CHANGELOG.md: refer to https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4563 --------- Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
2023-07-22 22:20:21 +00:00
now, err := time.Parse(time.RFC3339, currentTime)
if err != nil {
t.Fatalf("cannot parse currentTime=%q: %s", currentTime, err)
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}
lib/storage: pre-create timeseries before indexDB rotation (#4652) * lib/storage: pre-create timeseries before indexDB rotation during an hour before indexDB rotation start creating records at the next indexDB it must improve performance during switch for the next indexDB and remove ingestion issues. Since there is no need for creation new index records for timeseries already ingested into current indexDB https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4563 * lib/storage: further work on indexdb rotation optimization - Document the change at docs/CHAGNELOG.md - Move back various caches from indexDB to Storage. This makes the change less intrusive. The dateMetricIDCache now takes into account indexDB generation, so it stores (date, metricID) entries for both the current and the next indexDB. - Consolidate the code responsible for idbNext pre-filling into prefillNextIndexDB() function. This improves code readability and maintainability a bit. - Rewrite and simplify the code responsible for calculating the next retention timestamp. Add various tests for corner cases of this code. - Remove indexdb pre-filling from RegisterMetricNames() function, since this function is rarely called. It is OK to add indexdb entries on demand in this function. This simplifies the code. Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1401 * docs/CHANGELOG.md: refer to https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4563 --------- Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
2023-07-22 22:20:21 +00:00
d := nextRetentionDeadlineSeconds(now.Unix(), int64(retention.Seconds()), int64(offset.Seconds()))
deadline := time.Unix(d, 0).UTC().Format(time.RFC3339)
if deadline != deadlineExpected {
t.Fatalf("unexpected deadline; got %s; want %s", deadline, deadlineExpected)
}
}
lib/storage: pre-create timeseries before indexDB rotation (#4652) * lib/storage: pre-create timeseries before indexDB rotation during an hour before indexDB rotation start creating records at the next indexDB it must improve performance during switch for the next indexDB and remove ingestion issues. Since there is no need for creation new index records for timeseries already ingested into current indexDB https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4563 * lib/storage: further work on indexdb rotation optimization - Document the change at docs/CHAGNELOG.md - Move back various caches from indexDB to Storage. This makes the change less intrusive. The dateMetricIDCache now takes into account indexDB generation, so it stores (date, metricID) entries for both the current and the next indexDB. - Consolidate the code responsible for idbNext pre-filling into prefillNextIndexDB() function. This improves code readability and maintainability a bit. - Rewrite and simplify the code responsible for calculating the next retention timestamp. Add various tests for corner cases of this code. - Remove indexdb pre-filling from RegisterMetricNames() function, since this function is rarely called. It is OK to add indexdb entries on demand in this function. This simplifies the code. Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1401 * docs/CHANGELOG.md: refer to https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4563 --------- Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
2023-07-22 22:20:21 +00:00
f("2023-07-22T12:44:35Z", 24*time.Hour, 0, "2023-07-23T04:00:00Z")
f("2023-07-22T03:44:35Z", 24*time.Hour, 0, "2023-07-22T04:00:00Z")
f("2023-07-22T04:44:35Z", 24*time.Hour, 0, "2023-07-23T04:00:00Z")
f("2023-07-22T23:44:35Z", 24*time.Hour, 0, "2023-07-23T04:00:00Z")
f("2023-07-23T03:59:35Z", 24*time.Hour, 0, "2023-07-23T04:00:00Z")
f("2023-07-22T12:44:35Z", 24*time.Hour, 2*time.Hour, "2023-07-23T02:00:00Z")
f("2023-07-22T01:44:35Z", 24*time.Hour, 2*time.Hour, "2023-07-22T02:00:00Z")
f("2023-07-22T02:44:35Z", 24*time.Hour, 2*time.Hour, "2023-07-23T02:00:00Z")
f("2023-07-22T23:44:35Z", 24*time.Hour, 2*time.Hour, "2023-07-23T02:00:00Z")
f("2023-07-23T01:59:35Z", 24*time.Hour, 2*time.Hour, "2023-07-23T02:00:00Z")
f("2023-07-22T12:44:35Z", 24*time.Hour, -5*time.Hour, "2023-07-23T09:00:00Z")
f("2023-07-22T08:44:35Z", 24*time.Hour, -5*time.Hour, "2023-07-22T09:00:00Z")
f("2023-07-22T09:44:35Z", 24*time.Hour, -5*time.Hour, "2023-07-23T09:00:00Z")
f("2023-07-22T12:44:35Z", 24*time.Hour, -12*time.Hour, "2023-07-22T16:00:00Z")
f("2023-07-22T15:44:35Z", 24*time.Hour, -12*time.Hour, "2023-07-22T16:00:00Z")
f("2023-07-22T16:44:35Z", 24*time.Hour, -12*time.Hour, "2023-07-23T16:00:00Z")
f("2023-07-22T12:44:35Z", 24*time.Hour, -18*time.Hour, "2023-07-22T22:00:00Z")
f("2023-07-22T21:44:35Z", 24*time.Hour, -18*time.Hour, "2023-07-22T22:00:00Z")
f("2023-07-22T22:44:35Z", 24*time.Hour, -18*time.Hour, "2023-07-23T22:00:00Z")
f("2023-07-22T12:44:35Z", 24*time.Hour, 18*time.Hour, "2023-07-23T10:00:00Z")
f("2023-07-22T09:44:35Z", 24*time.Hour, 18*time.Hour, "2023-07-22T10:00:00Z")
f("2023-07-22T10:44:35Z", 24*time.Hour, 18*time.Hour, "2023-07-23T10:00:00Z")
f("2023-07-22T12:44:35Z", 24*time.Hour, 37*time.Hour, "2023-07-22T15:00:00Z")
f("2023-07-22T14:44:35Z", 24*time.Hour, 37*time.Hour, "2023-07-22T15:00:00Z")
f("2023-07-22T15:44:35Z", 24*time.Hour, 37*time.Hour, "2023-07-23T15:00:00Z")
2019-05-22 21:16:55 +00:00
}
func TestStorageOpenClose(t *testing.T) {
path := "TestStorageOpenClose"
for i := 0; i < 10; i++ {
s := MustOpenStorage(path, -1, 1e5, 1e6)
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s.MustClose()
}
if err := os.RemoveAll(path); err != nil {
t.Fatalf("cannot remove %q: %s", path, err)
}
}
func TestStorageRandTimestamps(t *testing.T) {
path := "TestStorageRandTimestamps"
retentionMsecs := int64(10 * msecsPerMonth)
s := MustOpenStorage(path, retentionMsecs, 0, 0)
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t.Run("serial", func(t *testing.T) {
for i := 0; i < 3; i++ {
if err := testStorageRandTimestamps(s); err != nil {
t.Fatalf("error on iteration %d: %s", i, err)
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}
s.MustClose()
s = MustOpenStorage(path, retentionMsecs, 0, 0)
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}
})
t.Run("concurrent", func(t *testing.T) {
ch := make(chan error, 3)
for i := 0; i < cap(ch); i++ {
go func() {
var err error
for i := 0; i < 2; i++ {
err = testStorageRandTimestamps(s)
}
ch <- err
}()
}
tt := time.NewTimer(time.Second * 10)
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for i := 0; i < cap(ch); i++ {
select {
case err := <-ch:
if err != nil {
t.Fatalf("error on iteration %d: %s", i, err)
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}
case <-tt.C:
t.Fatalf("timeout on iteration %d", i)
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}
}
})
s.MustClose()
if err := os.RemoveAll(path); err != nil {
t.Fatalf("cannot remove %q: %s", path, err)
}
}
func testStorageRandTimestamps(s *Storage) error {
currentTime := timestampFromTime(time.Now())
const rowsPerAdd = 5e3
const addsCount = 3
rng := rand.New(rand.NewSource(1))
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for i := 0; i < addsCount; i++ {
var mrs []MetricRow
var mn MetricName
mn.Tags = []Tag{
{[]byte("job"), []byte("webservice")},
{[]byte("instance"), []byte("1.2.3.4")},
}
for j := 0; j < rowsPerAdd; j++ {
mn.MetricGroup = []byte(fmt.Sprintf("metric_%d", rng.Intn(100)))
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metricNameRaw := mn.marshalRaw(nil)
timestamp := currentTime - int64((rng.Float64()-0.2)*float64(2*s.retentionMsecs))
value := rng.NormFloat64() * 1e11
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mr := MetricRow{
MetricNameRaw: metricNameRaw,
Timestamp: timestamp,
Value: value,
}
mrs = append(mrs, mr)
}
if err := s.AddRows(mrs, defaultPrecisionBits); err != nil {
errStr := err.Error()
if !strings.Contains(errStr, "too big timestamp") && !strings.Contains(errStr, "too small timestamp") {
return fmt.Errorf("unexpected error when adding mrs: %w", err)
2019-05-22 21:16:55 +00:00
}
}
}
// Verify the storage contains rows.
var m Metrics
s.UpdateMetrics(&m)
if rowsCount := m.TableMetrics.TotalRowsCount(); rowsCount == 0 {
return fmt.Errorf("expecting at least one row in storage")
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}
return nil
}
func TestStorageDeleteSeries(t *testing.T) {
path := "TestStorageDeleteSeries"
s := MustOpenStorage(path, 0, 0, 0)
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// Verify no label names exist
lns, err := s.SearchLabelNamesWithFiltersOnTimeRange(nil, 0, 0, nil, TimeRange{}, 1e5, 1e9, noDeadline)
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if err != nil {
t.Fatalf("error in SearchLabelNamesWithFiltersOnTimeRange() at the start: %s", err)
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}
if len(lns) != 0 {
t.Fatalf("found non-empty tag keys at the start: %q", lns)
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}
t.Run("serial", func(t *testing.T) {
for i := 0; i < 3; i++ {
if err = testStorageDeleteSeries(s, 0); err != nil {
t.Fatalf("unexpected error on iteration %d: %s", i, err)
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}
// Re-open the storage in order to check how deleted metricIDs
// are persisted.
s.MustClose()
s = MustOpenStorage(path, 0, 0, 0)
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}
})
t.Run("concurrent", func(t *testing.T) {
ch := make(chan error, 3)
for i := 0; i < cap(ch); i++ {
go func(workerNum int) {
var err error
for j := 0; j < 2; j++ {
err = testStorageDeleteSeries(s, workerNum)
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if err != nil {
break
}
}
ch <- err
}(i)
}
tt := time.NewTimer(30 * time.Second)
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for i := 0; i < cap(ch); i++ {
select {
case err := <-ch:
if err != nil {
t.Fatalf("unexpected error on iteration %d: %s", i, err)
2019-05-22 21:16:55 +00:00
}
case <-tt.C:
t.Fatalf("timeout on iteration %d", i)
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}
}
})
// Verify no more tag keys exist
lns, err = s.SearchLabelNamesWithFiltersOnTimeRange(nil, 0, 0, nil, TimeRange{}, 1e5, 1e9, noDeadline)
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if err != nil {
t.Fatalf("error in SearchLabelNamesWithFiltersOnTimeRange after the test: %s", err)
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}
if len(lns) != 0 {
t.Fatalf("found non-empty tag keys after the test: %q", lns)
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}
s.MustClose()
if err := os.RemoveAll(path); err != nil {
t.Fatalf("cannot remove %q: %s", path, err)
}
}
func testStorageDeleteSeries(s *Storage, workerNum int) error {
rng := rand.New(rand.NewSource(1))
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const rowsPerMetric = 100
const metricsCount = 30
workerTag := []byte(fmt.Sprintf("workerTag_%d", workerNum))
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accountID := uint32(workerNum)
projectID := uint32(123)
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lnsAll := make(map[string]bool)
lnsAll["__name__"] = true
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for i := 0; i < metricsCount; i++ {
var mrs []MetricRow
var mn MetricName
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mn.AccountID = accountID
mn.ProjectID = projectID
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job := fmt.Sprintf("job_%d_%d", i, workerNum)
instance := fmt.Sprintf("instance_%d_%d", i, workerNum)
mn.Tags = []Tag{
{[]byte("job"), []byte(job)},
{[]byte("instance"), []byte(instance)},
{workerTag, []byte("foobar")},
}
for i := range mn.Tags {
lnsAll[string(mn.Tags[i].Key)] = true
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}
mn.MetricGroup = []byte(fmt.Sprintf("metric_%d_%d", i, workerNum))
metricNameRaw := mn.marshalRaw(nil)
for j := 0; j < rowsPerMetric; j++ {
timestamp := rng.Int63n(1e10)
value := rng.NormFloat64() * 1e6
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mr := MetricRow{
MetricNameRaw: metricNameRaw,
Timestamp: timestamp,
Value: value,
}
mrs = append(mrs, mr)
}
if err := s.AddRows(mrs, defaultPrecisionBits); err != nil {
return fmt.Errorf("unexpected error when adding mrs: %w", err)
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}
}
s.DebugFlush()
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// Verify tag values exist
tvs, err := s.SearchLabelValuesWithFiltersOnTimeRange(nil, accountID, projectID, string(workerTag), nil, TimeRange{}, 1e5, 1e9, noDeadline)
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if err != nil {
return fmt.Errorf("error in SearchLabelValuesWithFiltersOnTimeRange before metrics removal: %w", err)
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}
if len(tvs) == 0 {
return fmt.Errorf("unexpected empty number of tag values for workerTag")
}
// Verify tag keys exist
lns, err := s.SearchLabelNamesWithFiltersOnTimeRange(nil, accountID, projectID, nil, TimeRange{}, 1e5, 1e9, noDeadline)
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if err != nil {
return fmt.Errorf("error in SearchLabelNamesWithFiltersOnTimeRange before metrics removal: %w", err)
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}
if err := checkLabelNames(lns, lnsAll); err != nil {
return fmt.Errorf("unexpected label names before metrics removal: %w", err)
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}
var sr Search
tr := TimeRange{
MinTimestamp: 0,
MaxTimestamp: 2e10,
}
metricBlocksCount := func(tfs *TagFilters) int {
// Verify the number of blocks
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n := 0
sr.Init(nil, s, []*TagFilters{tfs}, tr, 1e5, noDeadline)
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for sr.NextMetricBlock() {
n++
}
sr.MustClose()
return n
}
for i := 0; i < metricsCount; i++ {
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tfs := NewTagFilters(accountID, projectID)
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if err := tfs.Add(nil, []byte("metric_.+"), false, true); err != nil {
return fmt.Errorf("cannot add regexp tag filter: %w", err)
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}
job := fmt.Sprintf("job_%d_%d", i, workerNum)
if err := tfs.Add([]byte("job"), []byte(job), false, false); err != nil {
return fmt.Errorf("cannot add job tag filter: %w", err)
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}
if n := metricBlocksCount(tfs); n == 0 {
return fmt.Errorf("expecting non-zero number of metric blocks for tfs=%s", tfs)
}
deletedCount, err := s.DeleteSeries(nil, []*TagFilters{tfs})
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if err != nil {
return fmt.Errorf("cannot delete metrics: %w", err)
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}
if deletedCount == 0 {
return fmt.Errorf("expecting non-zero number of deleted metrics on iteration %d", i)
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}
if n := metricBlocksCount(tfs); n != 0 {
return fmt.Errorf("expecting zero metric blocks after DeleteSeries call for tfs=%s; got %d blocks", tfs, n)
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}
// Try deleting empty tfss
deletedCount, err = s.DeleteSeries(nil, nil)
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if err != nil {
return fmt.Errorf("cannot delete empty tfss: %w", err)
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}
if deletedCount != 0 {
return fmt.Errorf("expecting zero deleted metrics for empty tfss; got %d", deletedCount)
}
}
// Make sure no more metrics left for the given workerNum
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tfs := NewTagFilters(accountID, projectID)
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if err := tfs.Add(nil, []byte(fmt.Sprintf("metric_.+_%d", workerNum)), false, true); err != nil {
return fmt.Errorf("cannot add regexp tag filter for worker metrics: %w", err)
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}
if n := metricBlocksCount(tfs); n != 0 {
return fmt.Errorf("expecting zero metric blocks after deleting all the metrics; got %d blocks", n)
}
tvs, err = s.SearchLabelValuesWithFiltersOnTimeRange(nil, accountID, projectID, string(workerTag), nil, TimeRange{}, 1e5, 1e9, noDeadline)
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if err != nil {
return fmt.Errorf("error in SearchLabelValuesWithFiltersOnTimeRange after all the metrics are removed: %w", err)
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}
if len(tvs) != 0 {
return fmt.Errorf("found non-empty tag values for %q after metrics removal: %q", workerTag, tvs)
}
return nil
}
func checkLabelNames(lns []string, lnsExpected map[string]bool) error {
if len(lns) < len(lnsExpected) {
return fmt.Errorf("unexpected number of label names found; got %d; want at least %d; lns=%q, lnsExpected=%v", len(lns), len(lnsExpected), lns, lnsExpected)
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}
hasItem := func(s string, lns []string) bool {
for _, labelName := range lns {
if s == labelName {
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return true
}
}
return false
}
for labelName := range lnsExpected {
if !hasItem(labelName, lns) {
return fmt.Errorf("cannot find %q in label names %q", labelName, lns)
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}
}
return nil
}
func TestStorageRegisterMetricNamesSerial(t *testing.T) {
path := "TestStorageRegisterMetricNamesSerial"
s := MustOpenStorage(path, 0, 0, 0)
if err := testStorageRegisterMetricNames(s); err != nil {
t.Fatalf("unexpected error: %s", err)
}
s.MustClose()
if err := os.RemoveAll(path); err != nil {
t.Fatalf("cannot remove %q: %s", path, err)
}
}
func TestStorageRegisterMetricNamesConcurrent(t *testing.T) {
path := "TestStorageRegisterMetricNamesConcurrent"
s := MustOpenStorage(path, 0, 0, 0)
ch := make(chan error, 3)
for i := 0; i < cap(ch); i++ {
go func() {
ch <- testStorageRegisterMetricNames(s)
}()
}
for i := 0; i < cap(ch); i++ {
select {
case err := <-ch:
if err != nil {
t.Fatalf("unexpected error: %s", err)
}
case <-time.After(10 * time.Second):
t.Fatalf("timeout")
}
}
s.MustClose()
if err := os.RemoveAll(path); err != nil {
t.Fatalf("cannot remove %q: %s", path, err)
}
}
func testStorageRegisterMetricNames(s *Storage) error {
const metricsPerAdd = 1e3
const addsCount = 10
const accountID = 123
const projectID = 421
addIDsMap := make(map[string]struct{})
for i := 0; i < addsCount; i++ {
var mrs []MetricRow
var mn MetricName
addID := fmt.Sprintf("%d", i)
addIDsMap[addID] = struct{}{}
mn.AccountID = accountID
mn.ProjectID = projectID
mn.Tags = []Tag{
{[]byte("job"), []byte("webservice")},
{[]byte("instance"), []byte("1.2.3.4")},
{[]byte("add_id"), []byte(addID)},
}
now := timestampFromTime(time.Now())
for j := 0; j < metricsPerAdd; j++ {
mn.MetricGroup = []byte(fmt.Sprintf("metric_%d", j))
metricNameRaw := mn.marshalRaw(nil)
mr := MetricRow{
MetricNameRaw: metricNameRaw,
Timestamp: now,
}
mrs = append(mrs, mr)
}
lib/storage: switch from global to per-day index for `MetricName -> TSID` mapping Previously all the newly ingested time series were registered in global `MetricName -> TSID` index. This index was used during data ingestion for locating the TSID (internal series id) for the given canonical metric name (the canonical metric name consists of metric name plus all its labels sorted by label names). The `MetricName -> TSID` index is stored on disk in order to make sure that the data isn't lost on VictoriaMetrics restart or unclean shutdown. The lookup in this index is relatively slow, since VictoriaMetrics needs to read the corresponding data block from disk, unpack it, put the unpacked block into `indexdb/dataBlocks` cache, and then search for the given `MetricName -> TSID` entry there. So VictoriaMetrics uses in-memory cache for speeding up the lookup for active time series. This cache is named `storage/tsid`. If this cache capacity is enough for all the currently ingested active time series, then VictoriaMetrics works fast, since it doesn't need to read the data from disk. VictoriaMetrics starts reading data from `MetricName -> TSID` on-disk index in the following cases: - If `storage/tsid` cache capacity isn't enough for active time series. Then just increase available memory for VictoriaMetrics or reduce the number of active time series ingested into VictoriaMetrics. - If new time series is ingested into VictoriaMetrics. In this case it cannot find the needed entry in the `storage/tsid` cache, so it needs to consult on-disk `MetricName -> TSID` index, since it doesn't know that the index has no the corresponding entry too. This is a typical event under high churn rate, when old time series are constantly substituted with new time series. Reading the data from `MetricName -> TSID` index is slow, so inserts, which lead to reading this index, are counted as slow inserts, and they can be monitored via `vm_slow_row_inserts_total` metric exposed by VictoriaMetrics. Prior to this commit the `MetricName -> TSID` index was global, e.g. it contained entries sorted by `MetricName` for all the time series ever ingested into VictoriaMetrics during the configured -retentionPeriod. This index can become very large under high churn rate and long retention. VictoriaMetrics caches data from this index in `indexdb/dataBlocks` in-memory cache for speeding up index lookups. The `indexdb/dataBlocks` cache may occupy significant share of available memory for storing recently accessed blocks at `MetricName -> TSID` index when searching for newly ingested time series. This commit switches from global `MetricName -> TSID` index to per-day index. This allows significantly reducing the amounts of data, which needs to be cached in `indexdb/dataBlocks`, since now VictoriaMetrics consults only the index for the current day when new time series is ingested into it. The downside of this change is increased indexdb size on disk for workloads without high churn rate, e.g. with static time series, which do no change over time, since now VictoriaMetrics needs to store identical `MetricName -> TSID` entries for static time series for every day. This change removes an optimization for reducing CPU and disk IO spikes at indexdb rotation, since it didn't work correctly - see https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1401 . At the same time the change fixes the issue, which could result in lost access to time series, which stop receving new samples during the first hour after indexdb rotation - see https://github.com/VictoriaMetrics/VictoriaMetrics/issues/2698 The issue with the increased CPU and disk IO usage during indexdb rotation will be addressed in a separate commit according to https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1401#issuecomment-1553488685 This is a follow-up for 1f28b46ae9350795af41cbfc3ca0e8a5af084fce
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s.RegisterMetricNames(nil, mrs)
}
var addIDsExpected []string
for k := range addIDsMap {
addIDsExpected = append(addIDsExpected, k)
}
sort.Strings(addIDsExpected)
// Verify the storage contains the added metric names.
s.DebugFlush()
// Verify that SearchLabelNamesWithFiltersOnTimeRange returns correct result.
lnsExpected := []string{
"__name__",
"add_id",
"instance",
"job",
}
lns, err := s.SearchLabelNamesWithFiltersOnTimeRange(nil, accountID, projectID, nil, TimeRange{}, 100, 1e9, noDeadline)
if err != nil {
return fmt.Errorf("error in SearchLabelNamesWithFiltersOnTimeRange: %w", err)
}
sort.Strings(lns)
if !reflect.DeepEqual(lns, lnsExpected) {
return fmt.Errorf("unexpected label names returned from SearchLabelNamesWithFiltersOnTimeRange;\ngot\n%q\nwant\n%q", lns, lnsExpected)
}
// Verify that SearchLabelNamesWithFiltersOnTimeRange returns empty results for incorrect accountID, projectID
lns, err = s.SearchLabelNamesWithFiltersOnTimeRange(nil, accountID+1, projectID+1, nil, TimeRange{}, 100, 1e9, noDeadline)
if err != nil {
return fmt.Errorf("error in SearchTagKeys for incorrect accountID, projectID: %w", err)
}
if len(lns) > 0 {
return fmt.Errorf("SearchTagKeys with incorrect accountID, projectID returns unexpected non-empty result:\n%q", lns)
}
// Verify that SearchLabelNamesWithFiltersOnTimeRange with the specified time range returns correct result.
now := timestampFromTime(time.Now())
start := now - msecPerDay
end := now + 60*1000
tr := TimeRange{
MinTimestamp: start,
MaxTimestamp: end,
}
lns, err = s.SearchLabelNamesWithFiltersOnTimeRange(nil, accountID, projectID, nil, tr, 100, 1e9, noDeadline)
if err != nil {
return fmt.Errorf("error in SearchLabelNamesWithFiltersOnTimeRange: %w", err)
}
sort.Strings(lns)
if !reflect.DeepEqual(lns, lnsExpected) {
return fmt.Errorf("unexpected label names returned from SearchLabelNamesWithFiltersOnTimeRange;\ngot\n%q\nwant\n%q", lns, lnsExpected)
}
// Verify that SearchLabelNamesWithFiltersOnTimeRange with the specified time range returns empty results for incrorrect accountID, projectID
lns, err = s.SearchLabelNamesWithFiltersOnTimeRange(nil, accountID+1, projectID+1, nil, tr, 100, 1e9, noDeadline)
if err != nil {
return fmt.Errorf("error in SearchTagKeysOnTimeRange for incorrect accountID, projectID: %w", err)
}
if len(lns) > 0 {
return fmt.Errorf("SearchTagKeysOnTimeRange with incorrect accountID, projectID returns unexpected non-empty result:\n%q", lns)
}
// Verify that SearchLabelValuesWithFiltersOnTimeRange returns correct result.
addIDs, err := s.SearchLabelValuesWithFiltersOnTimeRange(nil, accountID, projectID, "add_id", nil, TimeRange{}, addsCount+100, 1e9, noDeadline)
if err != nil {
return fmt.Errorf("error in SearchLabelValuesWithFiltersOnTimeRange: %w", err)
}
sort.Strings(addIDs)
if !reflect.DeepEqual(addIDs, addIDsExpected) {
return fmt.Errorf("unexpected tag values returned from SearchLabelValuesWithFiltersOnTimeRange;\ngot\n%q\nwant\n%q", addIDs, addIDsExpected)
}
// Verify that SearchLabelValuesWithFiltersOnTimeRange return empty results for incorrect accountID, projectID
addIDs, err = s.SearchLabelValuesWithFiltersOnTimeRange(nil, accountID+1, projectID+1, "add_id", nil, TimeRange{}, addsCount+100, 1e9, noDeadline)
if err != nil {
return fmt.Errorf("error in SearchTagValues for incorrect accountID, projectID: %w", err)
}
if len(addIDs) > 0 {
return fmt.Errorf("SearchTagValues with incorrect accountID, projectID returns unexpected non-empty result:\n%q", addIDs)
}
// Verify that SearchLabelValuesWithFiltersOnTimeRange with the specified time range returns correct result.
addIDs, err = s.SearchLabelValuesWithFiltersOnTimeRange(nil, accountID, projectID, "add_id", nil, tr, addsCount+100, 1e9, noDeadline)
if err != nil {
return fmt.Errorf("error in SearchLabelValuesWithFiltersOnTimeRange: %w", err)
}
sort.Strings(addIDs)
if !reflect.DeepEqual(addIDs, addIDsExpected) {
return fmt.Errorf("unexpected tag values returned from SearchLabelValuesWithFiltersOnTimeRange;\ngot\n%q\nwant\n%q", addIDs, addIDsExpected)
}
// Verify that SearchLabelValuesWithFiltersOnTimeRange returns empty results for incorrect accountID, projectID
addIDs, err = s.SearchLabelValuesWithFiltersOnTimeRange(nil, accountID+1, projectID+1, "addd_id", nil, tr, addsCount+100, 1e9, noDeadline)
if err != nil {
return fmt.Errorf("error in SearchLabelValuesWithFiltersOnTimeRange for incorrect accoundID, projectID: %w", err)
}
if len(addIDs) > 0 {
return fmt.Errorf("SearchLabelValuesWithFiltersOnTimeRange with incorrect accountID, projectID returns unexpected non-empty result:\n%q", addIDs)
}
// Verify that SearchMetricNames returns correct result.
tfs := NewTagFilters(accountID, projectID)
if err := tfs.Add([]byte("add_id"), []byte("0"), false, false); err != nil {
return fmt.Errorf("unexpected error in TagFilters.Add: %w", err)
}
metricNames, err := s.SearchMetricNames(nil, []*TagFilters{tfs}, tr, metricsPerAdd*addsCount*100+100, noDeadline)
if err != nil {
return fmt.Errorf("error in SearchMetricNames: %w", err)
}
if len(metricNames) < metricsPerAdd {
return fmt.Errorf("unexpected number of metricNames returned from SearchMetricNames; got %d; want at least %d", len(metricNames), int(metricsPerAdd))
}
var mn MetricName
for i, metricName := range metricNames {
if err := mn.UnmarshalString(metricName); err != nil {
return fmt.Errorf("cannot unmarshal metricName=%q: %w", metricName, err)
}
addID := mn.GetTagValue("add_id")
if string(addID) != "0" {
return fmt.Errorf("unexpected addID for metricName #%d; got %q; want %q", i, addID, "0")
}
job := mn.GetTagValue("job")
if string(job) != "webservice" {
return fmt.Errorf("unexpected job for metricName #%d; got %q; want %q", i, job, "webservice")
}
}
// Verify that SearchMetricNames returns empty results for incorrect accountID, projectID
tfs = NewTagFilters(accountID+1, projectID+1)
if err := tfs.Add([]byte("add_id"), []byte("0"), false, false); err != nil {
return fmt.Errorf("unexpected error in TagFilters.Add: %w", err)
}
metricNames, err = s.SearchMetricNames(nil, []*TagFilters{tfs}, tr, metricsPerAdd*addsCount*100+100, noDeadline)
if err != nil {
return fmt.Errorf("error in SearchMetricNames for incorrect accountID, projectID: %w", err)
}
if len(metricNames) > 0 {
return fmt.Errorf("SearchMetricNames with incorrect accountID, projectID returns unexpected non-empty result:\n%+v", metricNames)
}
return nil
}
func TestStorageAddRowsSerial(t *testing.T) {
rng := rand.New(rand.NewSource(1))
path := "TestStorageAddRowsSerial"
retentionMsecs := int64(msecsPerMonth * 10)
s := MustOpenStorage(path, retentionMsecs, 1e5, 1e5)
if err := testStorageAddRows(rng, s); err != nil {
t.Fatalf("unexpected error: %s", err)
}
s.MustClose()
if err := os.RemoveAll(path); err != nil {
t.Fatalf("cannot remove %q: %s", path, err)
}
}
func TestStorageAddRowsConcurrent(t *testing.T) {
path := "TestStorageAddRowsConcurrent"
retentionMsecs := int64(msecsPerMonth * 10)
s := MustOpenStorage(path, retentionMsecs, 1e5, 1e5)
ch := make(chan error, 3)
for i := 0; i < cap(ch); i++ {
go func(n int) {
rLocal := rand.New(rand.NewSource(int64(n)))
ch <- testStorageAddRows(rLocal, s)
}(i)
}
for i := 0; i < cap(ch); i++ {
select {
case err := <-ch:
if err != nil {
t.Fatalf("unexpected error: %s", err)
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}
case <-time.After(10 * time.Second):
t.Fatalf("timeout")
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}
}
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s.MustClose()
if err := os.RemoveAll(path); err != nil {
t.Fatalf("cannot remove %q: %s", path, err)
}
}
func testGenerateMetricRowsForTenant(accountID, projectID uint32, rng *rand.Rand, rows uint64, timestampMin, timestampMax int64) []MetricRow {
var mrs []MetricRow
var mn MetricName
mn.Tags = []Tag{
{[]byte("job"), []byte("webservice")},
{[]byte("instance"), []byte("1.2.3.4")},
}
for i := 0; i < int(rows); i++ {
mn.AccountID = accountID
mn.ProjectID = projectID
mn.MetricGroup = []byte(fmt.Sprintf("metric_%d", i))
metricNameRaw := mn.marshalRaw(nil)
timestamp := rng.Int63n(timestampMax-timestampMin) + timestampMin
value := rng.NormFloat64() * 1e6
mr := MetricRow{
MetricNameRaw: metricNameRaw,
Timestamp: timestamp,
Value: value,
}
mrs = append(mrs, mr)
}
return mrs
}
func testGenerateMetricRows(rng *rand.Rand, rows uint64, timestampMin, timestampMax int64) []MetricRow {
lib/index: reduce read/write load after indexDB rotation (#2177) * lib/index: reduce read/write load after indexDB rotation IndexDB in VM is responsible for storing TSID - ID's used for identifying time series. The index is stored on disk and used by both ingestion and read path. IndexDB is stored separately to data parts and is global for all stored data. It can't be deleted partially as VM deletes data parts. Instead, indexDB is rotated once in `retention` interval. The rotation procedure means that `current` indexDB becomes `previous`, and new freshly created indexDB struct becomes `current`. So in any time, VM holds indexDB for current and previous retention periods. When time series is ingested or queried, VM checks if its TSID is present in `current` indexDB. If it is missing, it checks the `previous` indexDB. If TSID was found, it gets copied to the `current` indexDB. In this way `current` indexDB stores only series which were active during the retention period. To improve indexDB lookups, VM uses a cache layer called `tsidCache`. Both write and read path consult `tsidCache` and on miss the relad lookup happens. When rotation happens, VM resets the `tsidCache`. This is needed for ingestion path to trigger `current` indexDB re-population. Since index re-population requires additional resources, every index rotation event may cause some extra load on CPU and disk. While it may be unnoticeable for most of the cases, for systems with very high number of unique series each rotation may lead to performance degradation for some period of time. This PR makes an attempt to smooth out resource usage after the rotation. The changes are following: 1. `tsidCache` is no longer reset after the rotation; 2. Instead, each entry in `tsidCache` gains a notion of indexDB to which they belong; 3. On ingestion path after the rotation we check if requested TSID was found in `tsidCache`. Then we have 3 branches: 3.1 Fast path. It was found, and belongs to the `current` indexDB. Return TSID. 3.2 Slow path. It wasn't found, so we generate it from scratch, add to `current` indexDB, add it to `tsidCache`. 3.3 Smooth path. It was found but does not belong to the `current` indexDB. In this case, we add it to the `current` indexDB with some probability. The probability is based on time passed since the last rotation with some threshold. The more time has passed since rotation the higher is chance to re-populate `current` indexDB. The default re-population interval in this PR is set to `1h`, during which entries from `previous` index supposed to slowly re-populate `current` index. The new metric `vm_timeseries_repopulated_total` was added to identify how many TSIDs were moved from `previous` indexDB to the `current` indexDB. This metric supposed to grow only during the first `1h` after the last rotation. https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1401 Signed-off-by: hagen1778 <roman@victoriametrics.com> * wip * wip Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
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var mrs []MetricRow
var mn MetricName
mn.Tags = []Tag{
{[]byte("job"), []byte("webservice")},
{[]byte("instance"), []byte("1.2.3.4")},
}
for i := 0; i < int(rows); i++ {
mn.AccountID = uint32(rand.Intn(2))
mn.ProjectID = uint32(rand.Intn(3))
mn.MetricGroup = []byte(fmt.Sprintf("metric_%d", i))
metricNameRaw := mn.marshalRaw(nil)
timestamp := rng.Int63n(timestampMax-timestampMin) + timestampMin
value := rng.NormFloat64() * 1e6
lib/index: reduce read/write load after indexDB rotation (#2177) * lib/index: reduce read/write load after indexDB rotation IndexDB in VM is responsible for storing TSID - ID's used for identifying time series. The index is stored on disk and used by both ingestion and read path. IndexDB is stored separately to data parts and is global for all stored data. It can't be deleted partially as VM deletes data parts. Instead, indexDB is rotated once in `retention` interval. The rotation procedure means that `current` indexDB becomes `previous`, and new freshly created indexDB struct becomes `current`. So in any time, VM holds indexDB for current and previous retention periods. When time series is ingested or queried, VM checks if its TSID is present in `current` indexDB. If it is missing, it checks the `previous` indexDB. If TSID was found, it gets copied to the `current` indexDB. In this way `current` indexDB stores only series which were active during the retention period. To improve indexDB lookups, VM uses a cache layer called `tsidCache`. Both write and read path consult `tsidCache` and on miss the relad lookup happens. When rotation happens, VM resets the `tsidCache`. This is needed for ingestion path to trigger `current` indexDB re-population. Since index re-population requires additional resources, every index rotation event may cause some extra load on CPU and disk. While it may be unnoticeable for most of the cases, for systems with very high number of unique series each rotation may lead to performance degradation for some period of time. This PR makes an attempt to smooth out resource usage after the rotation. The changes are following: 1. `tsidCache` is no longer reset after the rotation; 2. Instead, each entry in `tsidCache` gains a notion of indexDB to which they belong; 3. On ingestion path after the rotation we check if requested TSID was found in `tsidCache`. Then we have 3 branches: 3.1 Fast path. It was found, and belongs to the `current` indexDB. Return TSID. 3.2 Slow path. It wasn't found, so we generate it from scratch, add to `current` indexDB, add it to `tsidCache`. 3.3 Smooth path. It was found but does not belong to the `current` indexDB. In this case, we add it to the `current` indexDB with some probability. The probability is based on time passed since the last rotation with some threshold. The more time has passed since rotation the higher is chance to re-populate `current` indexDB. The default re-population interval in this PR is set to `1h`, during which entries from `previous` index supposed to slowly re-populate `current` index. The new metric `vm_timeseries_repopulated_total` was added to identify how many TSIDs were moved from `previous` indexDB to the `current` indexDB. This metric supposed to grow only during the first `1h` after the last rotation. https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1401 Signed-off-by: hagen1778 <roman@victoriametrics.com> * wip * wip Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
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mr := MetricRow{
MetricNameRaw: metricNameRaw,
Timestamp: timestamp,
Value: value,
}
mrs = append(mrs, mr)
}
return mrs
}
func testStorageAddRows(rng *rand.Rand, s *Storage) error {
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const rowsPerAdd = 1e3
const addsCount = 10
maxTimestamp := timestampFromTime(time.Now())
minTimestamp := maxTimestamp - s.retentionMsecs + 3600*1000
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for i := 0; i < addsCount; i++ {
mrs := testGenerateMetricRows(rng, rowsPerAdd, minTimestamp, maxTimestamp)
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if err := s.AddRows(mrs, defaultPrecisionBits); err != nil {
return fmt.Errorf("unexpected error when adding mrs: %w", err)
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}
}
// Verify the storage contains rows.
lib/index: reduce read/write load after indexDB rotation (#2177) * lib/index: reduce read/write load after indexDB rotation IndexDB in VM is responsible for storing TSID - ID's used for identifying time series. The index is stored on disk and used by both ingestion and read path. IndexDB is stored separately to data parts and is global for all stored data. It can't be deleted partially as VM deletes data parts. Instead, indexDB is rotated once in `retention` interval. The rotation procedure means that `current` indexDB becomes `previous`, and new freshly created indexDB struct becomes `current`. So in any time, VM holds indexDB for current and previous retention periods. When time series is ingested or queried, VM checks if its TSID is present in `current` indexDB. If it is missing, it checks the `previous` indexDB. If TSID was found, it gets copied to the `current` indexDB. In this way `current` indexDB stores only series which were active during the retention period. To improve indexDB lookups, VM uses a cache layer called `tsidCache`. Both write and read path consult `tsidCache` and on miss the relad lookup happens. When rotation happens, VM resets the `tsidCache`. This is needed for ingestion path to trigger `current` indexDB re-population. Since index re-population requires additional resources, every index rotation event may cause some extra load on CPU and disk. While it may be unnoticeable for most of the cases, for systems with very high number of unique series each rotation may lead to performance degradation for some period of time. This PR makes an attempt to smooth out resource usage after the rotation. The changes are following: 1. `tsidCache` is no longer reset after the rotation; 2. Instead, each entry in `tsidCache` gains a notion of indexDB to which they belong; 3. On ingestion path after the rotation we check if requested TSID was found in `tsidCache`. Then we have 3 branches: 3.1 Fast path. It was found, and belongs to the `current` indexDB. Return TSID. 3.2 Slow path. It wasn't found, so we generate it from scratch, add to `current` indexDB, add it to `tsidCache`. 3.3 Smooth path. It was found but does not belong to the `current` indexDB. In this case, we add it to the `current` indexDB with some probability. The probability is based on time passed since the last rotation with some threshold. The more time has passed since rotation the higher is chance to re-populate `current` indexDB. The default re-population interval in this PR is set to `1h`, during which entries from `previous` index supposed to slowly re-populate `current` index. The new metric `vm_timeseries_repopulated_total` was added to identify how many TSIDs were moved from `previous` indexDB to the `current` indexDB. This metric supposed to grow only during the first `1h` after the last rotation. https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1401 Signed-off-by: hagen1778 <roman@victoriametrics.com> * wip * wip Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
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minRowsExpected := uint64(rowsPerAdd * addsCount)
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var m Metrics
s.UpdateMetrics(&m)
if rowsCount := m.TableMetrics.TotalRowsCount(); rowsCount < minRowsExpected {
return fmt.Errorf("expecting at least %d rows in the table; got %d", minRowsExpected, rowsCount)
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}
// Try creating a snapshot from the storage.
snapshotName, err := s.CreateSnapshot(0)
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if err != nil {
return fmt.Errorf("cannot create snapshot from the storage: %w", err)
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}
// Verify the snapshot is visible
snapshots, err := s.ListSnapshots()
if err != nil {
return fmt.Errorf("cannot list snapshots: %w", err)
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}
if !containsString(snapshots, snapshotName) {
return fmt.Errorf("cannot find snapshot %q in %q", snapshotName, snapshots)
}
// Try opening the storage from snapshot.
snapshotPath := filepath.Join(s.path, snapshotsDirname, snapshotName)
s1 := MustOpenStorage(snapshotPath, 0, 0, 0)
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// Verify the snapshot contains rows
var m1 Metrics
s1.UpdateMetrics(&m1)
if rowsCount := m1.TableMetrics.TotalRowsCount(); rowsCount < minRowsExpected {
return fmt.Errorf("snapshot %q must contain at least %d rows; got %d", snapshotPath, minRowsExpected, rowsCount)
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}
// Verify that force merge for the snapshot leaves at most a single part per partition.
// Zero parts are possible if the snapshot is created just after the partition has been created
// by concurrent goroutine, but it didn't put the data into it yet.
if err := s1.ForceMergePartitions(""); err != nil {
return fmt.Errorf("error when force merging partitions: %w", err)
}
ptws := s1.tb.GetPartitions(nil)
for _, ptw := range ptws {
pws := ptw.pt.GetParts(nil, true)
numParts := len(pws)
ptw.pt.PutParts(pws)
if numParts > 1 {
s1.tb.PutPartitions(ptws)
return fmt.Errorf("unexpected number of parts for partition %q after force merge; got %d; want at most 1", ptw.pt.name, numParts)
}
}
s1.tb.PutPartitions(ptws)
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s1.MustClose()
// Delete the snapshot and make sure it is no longer visible.
if err := s.DeleteSnapshot(snapshotName); err != nil {
return fmt.Errorf("cannot delete snapshot %q: %w", snapshotName, err)
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}
snapshots, err = s.ListSnapshots()
if err != nil {
return fmt.Errorf("cannot list snapshots: %w", err)
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}
if containsString(snapshots, snapshotName) {
return fmt.Errorf("snapshot %q must be deleted, but is still visible in %q", snapshotName, snapshots)
}
return nil
}
func TestStorageRotateIndexDB(t *testing.T) {
path := "TestStorageRotateIndexDB"
s := MustOpenStorage(path, 0, 0, 0)
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// Start indexDB rotater in a separate goroutine
stopCh := make(chan struct{})
rotateDoneCh := make(chan struct{})
go func() {
for {
select {
case <-stopCh:
close(rotateDoneCh)
return
default:
time.Sleep(time.Millisecond)
s.mustRotateIndexDB(time.Now())
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}
}
}()
// Run concurrent workers that insert / select data from the storage.
ch := make(chan error, 3)
for i := 0; i < cap(ch); i++ {
go func(workerNum int) {
ch <- testStorageAddMetrics(s, workerNum)
}(i)
}
for i := 0; i < cap(ch); i++ {
select {
case err := <-ch:
if err != nil {
t.Fatalf("unexpected error: %s", err)
}
case <-time.After(10 * time.Second):
t.Fatalf("timeout")
}
}
close(stopCh)
<-rotateDoneCh
s.MustClose()
if err := os.RemoveAll(path); err != nil {
t.Fatalf("cannot remove %q: %s", path, err)
}
}
func testStorageAddMetrics(s *Storage, workerNum int) error {
rng := rand.New(rand.NewSource(1))
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const rowsCount = 1e3
var mn MetricName
mn.Tags = []Tag{
{[]byte("job"), []byte(fmt.Sprintf("webservice_%d", workerNum))},
{[]byte("instance"), []byte("1.2.3.4")},
}
for i := 0; i < rowsCount; i++ {
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mn.AccountID = 123
mn.ProjectID = uint32(i % 3)
mn.MetricGroup = []byte(fmt.Sprintf("metric_%d_%d", workerNum, rng.Intn(10)))
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metricNameRaw := mn.marshalRaw(nil)
timestamp := rng.Int63n(1e10)
value := rng.NormFloat64() * 1e6
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mr := MetricRow{
MetricNameRaw: metricNameRaw,
Timestamp: timestamp,
Value: value,
}
if err := s.AddRows([]MetricRow{mr}, defaultPrecisionBits); err != nil {
return fmt.Errorf("unexpected error when adding mrs: %w", err)
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}
}
// Verify the storage contains rows.
minRowsExpected := uint64(rowsCount)
var m Metrics
s.UpdateMetrics(&m)
if rowsCount := m.TableMetrics.TotalRowsCount(); rowsCount < minRowsExpected {
return fmt.Errorf("expecting at least %d rows in the table; got %d", minRowsExpected, rowsCount)
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}
return nil
}
func TestStorageDeleteStaleSnapshots(t *testing.T) {
rng := rand.New(rand.NewSource(1))
path := "TestStorageDeleteStaleSnapshots"
retentionMsecs := int64(msecsPerMonth * 10)
s := MustOpenStorage(path, retentionMsecs, 1e5, 1e5)
const rowsPerAdd = 1e3
const addsCount = 10
maxTimestamp := timestampFromTime(time.Now())
minTimestamp := maxTimestamp - s.retentionMsecs
for i := 0; i < addsCount; i++ {
mrs := testGenerateMetricRows(rng, rowsPerAdd, minTimestamp, maxTimestamp)
if err := s.AddRows(mrs, defaultPrecisionBits); err != nil {
t.Fatalf("unexpected error when adding mrs: %s", err)
}
}
// Try creating a snapshot from the storage.
snapshotName, err := s.CreateSnapshot(0)
if err != nil {
t.Fatalf("cannot create snapshot from the storage: %s", err)
}
// Delete snapshots older than 1 month
if err := s.DeleteStaleSnapshots(30 * 24 * time.Hour); err != nil {
t.Fatalf("error in DeleteStaleSnapshots(1 month): %s", err)
}
snapshots, err := s.ListSnapshots()
if err != nil {
t.Fatalf("cannot list snapshots: %s", err)
}
if len(snapshots) != 1 {
t.Fatalf("expecting one snapshot; got %q", snapshots)
}
if snapshots[0] != snapshotName {
t.Fatalf("snapshot %q is missing in %q", snapshotName, snapshots)
}
// Delete the snapshot which is older than 1 nanoseconds
time.Sleep(2 * time.Nanosecond)
if err := s.DeleteStaleSnapshots(time.Nanosecond); err != nil {
t.Fatalf("cannot delete snapshot %q: %s", snapshotName, err)
}
snapshots, err = s.ListSnapshots()
if err != nil {
t.Fatalf("cannot list snapshots: %s", err)
}
if len(snapshots) != 0 {
t.Fatalf("expecting zero snapshots; got %q", snapshots)
}
s.MustClose()
if err := os.RemoveAll(path); err != nil {
t.Fatalf("cannot remove %q: %s", path, err)
}
}
func TestStorageSeriesAreNotCreatedOnStaleMarkers(t *testing.T) {
path := "TestStorageSeriesAreNotCreatedOnStaleMarkers"
const accountID = 2344
const projectID = 89823
s := MustOpenStorage(path, -1, 1e5, 1e6)
tr := TimeRange{MinTimestamp: 0, MaxTimestamp: 2e10}
tfsAll := NewTagFilters(accountID, projectID)
if err := tfsAll.Add([]byte("__name__"), []byte(".*"), false, true); err != nil {
t.Fatalf("unexpected error in TagFilters.Add: %s", err)
}
findN := func(n int) {
t.Helper()
lns, err := s.SearchMetricNames(nil, []*TagFilters{tfsAll}, tr, 1e5, noDeadline)
if err != nil {
t.Fatalf("error in SearchLabelNamesWithFiltersOnTimeRange() at the start: %s", err)
}
if len(lns) != n {
fmt.Println(lns)
t.Fatalf("expected to find %d metric names, found %d instead", n, len(lns))
}
}
// db is empty, so should be search results
findN(0)
rng := rand.New(rand.NewSource(1))
mrs := testGenerateMetricRowsForTenant(accountID, projectID, rng, 20, tr.MinTimestamp, tr.MaxTimestamp)
// populate storage with some rows
if err := s.AddRows(mrs[:10], defaultPrecisionBits); err != nil {
t.Fatal("error when adding mrs: %w", err)
}
s.DebugFlush()
// verify ingested rows are searchable
findN(10)
// clean up ingested data
_, err := s.DeleteSeries(nil, []*TagFilters{tfsAll})
if err != nil {
t.Fatalf("DeleteSeries failed: %s", err)
}
// verify that data was actually deleted
findN(0)
// mark every 2nd row as stale, simulating a stale target
for i := 0; i < len(mrs); i = i + 2 {
mrs[i].Value = decimal.StaleNaN
}
if err := s.AddRows(mrs, defaultPrecisionBits); err != nil {
t.Fatal("error when adding mrs: %w", err)
}
s.DebugFlush()
// verify that rows marked as stale aren't searchable
findN(10)
s.MustClose()
if err := os.RemoveAll(path); err != nil {
t.Fatalf("cannot remove %q: %s", path, err)
}
}