minio/cmd/data-usage-cache.go

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// Copyright (c) 2015-2023 MinIO, Inc.
//
// This file is part of MinIO Object Storage stack
//
// This program is free software: you can redistribute it and/or modify
// it under the terms of the GNU Affero General Public License as published by
// the Free Software Foundation, either version 3 of the License, or
// (at your option) any later version.
//
// This program is distributed in the hope that it will be useful
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
// GNU Affero General Public License for more details.
//
// You should have received a copy of the GNU Affero General Public License
// along with this program. If not, see <http://www.gnu.org/licenses/>.
package cmd
import (
"context"
"errors"
"fmt"
"io"
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"math/rand"
"net/http"
"path"
"path/filepath"
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
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"sort"
"strings"
"time"
"github.com/cespare/xxhash/v2"
"github.com/dustin/go-humanize"
"github.com/klauspost/compress/zstd"
"github.com/minio/madmin-go/v3"
"github.com/minio/minio/internal/bucket/lifecycle"
"github.com/tinylib/msgp/msgp"
"github.com/valyala/bytebufferpool"
)
//go:generate msgp -file $GOFILE -unexported
// dataUsageHash is the hash type used.
type dataUsageHash string
// sizeHistogramV1 is size histogram V1, which has fewer intervals esp. between
// 1024B and 1MiB.
type sizeHistogramV1 [dataUsageBucketLenV1]uint64
// sizeHistogram is a size histogram.
type sizeHistogram [dataUsageBucketLen]uint64
// versionsHistogram is a histogram of number of versions in an object.
type versionsHistogram [dataUsageVersionLen]uint64
type dataUsageEntry struct {
Children dataUsageHashMap `msg:"ch"`
// These fields do no include any children.
Size int64 `msg:"sz"`
Objects uint64 `msg:"os"`
Versions uint64 `msg:"vs"` // Versions that are not delete markers.
DeleteMarkers uint64 `msg:"dms"`
ObjSizes sizeHistogram `msg:"szs"`
ObjVersions versionsHistogram `msg:"vh"`
ReplicationStats *replicationAllStats `msg:"rs,omitempty"`
AllTierStats *allTierStats `msg:"ats,omitempty"`
Compacted bool `msg:"c"`
}
// allTierStats is a collection of per-tier stats across all configured remote
// tiers.
type allTierStats struct {
Tiers map[string]tierStats `msg:"ts"`
}
func newAllTierStats() *allTierStats {
return &allTierStats{
Tiers: make(map[string]tierStats),
}
}
func (ats *allTierStats) addSizes(tiers map[string]tierStats) {
for tier, st := range tiers {
ats.Tiers[tier] = ats.Tiers[tier].add(st)
}
}
func (ats *allTierStats) merge(other *allTierStats) {
for tier, st := range other.Tiers {
ats.Tiers[tier] = ats.Tiers[tier].add(st)
}
}
func (ats *allTierStats) clone() *allTierStats {
if ats == nil {
return nil
}
dst := *ats
dst.Tiers = make(map[string]tierStats, len(ats.Tiers))
for tier, st := range ats.Tiers {
dst.Tiers[tier] = st
}
return &dst
}
func (ats *allTierStats) populateStats(stats map[string]madmin.TierStats) {
if ats == nil {
return
}
// Update stats for tiers as they become available.
for tier, st := range ats.Tiers {
stats[tier] = madmin.TierStats{
TotalSize: st.TotalSize,
NumVersions: st.NumVersions,
NumObjects: st.NumObjects,
}
}
return
}
// tierStats holds per-tier stats of a remote tier.
type tierStats struct {
TotalSize uint64 `msg:"ts"`
NumVersions int `msg:"nv"`
NumObjects int `msg:"no"`
}
func (ts tierStats) add(u tierStats) tierStats {
return tierStats{
TotalSize: ts.TotalSize + u.TotalSize,
NumVersions: ts.NumVersions + u.NumVersions,
NumObjects: ts.NumObjects + u.NumObjects,
}
}
//msgp:tuple replicationStatsV1
type replicationStatsV1 struct {
PendingSize uint64
ReplicatedSize uint64
FailedSize uint64
ReplicaSize uint64
FailedCount uint64
PendingCount uint64
MissedThresholdSize uint64
AfterThresholdSize uint64
MissedThresholdCount uint64
AfterThresholdCount uint64
}
func (rsv1 replicationStatsV1) Empty() bool {
return rsv1.ReplicatedSize == 0 &&
rsv1.FailedSize == 0 &&
rsv1.FailedCount == 0
}
//msgp:tuple replicationStats
type replicationStats struct {
PendingSize uint64
ReplicatedSize uint64
FailedSize uint64
FailedCount uint64
PendingCount uint64
MissedThresholdSize uint64
AfterThresholdSize uint64
MissedThresholdCount uint64
AfterThresholdCount uint64
ReplicatedCount uint64
}
func (rs replicationStats) Empty() bool {
return rs.ReplicatedSize == 0 &&
rs.FailedSize == 0 &&
rs.FailedCount == 0
}
type replicationAllStats struct {
Targets map[string]replicationStats `msg:"t,omitempty"`
ReplicaSize uint64 `msg:"r,omitempty"`
ReplicaCount uint64 `msg:"rc,omitempty"`
}
//msgp:tuple replicationAllStatsV1
type replicationAllStatsV1 struct {
Targets map[string]replicationStats
ReplicaSize uint64 `msg:"ReplicaSize,omitempty"`
ReplicaCount uint64 `msg:"ReplicaCount,omitempty"`
}
// empty returns true if the replicationAllStats is empty (contains no entries).
func (r *replicationAllStats) empty() bool {
if r == nil {
return true
}
if r.ReplicaSize != 0 || r.ReplicaCount != 0 {
return false
}
for _, v := range r.Targets {
if !v.Empty() {
return false
}
}
return true
}
// clone creates a deep-copy clone.
func (r *replicationAllStats) clone() *replicationAllStats {
if r == nil {
return nil
}
// Shallow copy
dst := *r
// Copy individual targets.
dst.Targets = make(map[string]replicationStats, len(r.Targets))
for k, v := range r.Targets {
dst.Targets[k] = v
}
return &dst
}
//msgp:encode ignore dataUsageEntryV2 dataUsageEntryV3 dataUsageEntryV4 dataUsageEntryV5 dataUsageEntryV6 dataUsageEntryV7
//msgp:marshal ignore dataUsageEntryV2 dataUsageEntryV3 dataUsageEntryV4 dataUsageEntryV5 dataUsageEntryV6 dataUsageEntryV7
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
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//msgp:tuple dataUsageEntryV2
type dataUsageEntryV2 struct {
// These fields do no include any children.
Size int64
Objects uint64
ObjSizes sizeHistogram
Children dataUsageHashMap
}
//msgp:tuple dataUsageEntryV3
type dataUsageEntryV3 struct {
// These fields do no include any children.
Size int64
ReplicatedSize uint64
ReplicationPendingSize uint64
ReplicationFailedSize uint64
ReplicaSize uint64
Objects uint64
ObjSizes sizeHistogram
Children dataUsageHashMap
}
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
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//msgp:tuple dataUsageEntryV4
type dataUsageEntryV4 struct {
Children dataUsageHashMap
// These fields do no include any children.
Size int64
Objects uint64
ObjSizes sizeHistogram
ReplicationStats replicationStatsV1
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
2021-05-11 21:36:15 -04:00
}
//msgp:tuple dataUsageEntryV5
type dataUsageEntryV5 struct {
Children dataUsageHashMap
// These fields do no include any children.
Size int64
Objects uint64
Versions uint64 // Versions that are not delete markers.
ObjSizes sizeHistogram
ReplicationStats *replicationStatsV1
Compacted bool
}
//msgp:tuple dataUsageEntryV6
type dataUsageEntryV6 struct {
Children dataUsageHashMap
// These fields do no include any children.
Size int64
Objects uint64
Versions uint64 // Versions that are not delete markers.
ObjSizes sizeHistogram
ReplicationStats *replicationAllStatsV1
Compacted bool
}
type dataUsageEntryV7 struct {
Children dataUsageHashMap `msg:"ch"`
// These fields do no include any children.
Size int64 `msg:"sz"`
Objects uint64 `msg:"os"`
Versions uint64 `msg:"vs"` // Versions that are not delete markers.
DeleteMarkers uint64 `msg:"dms"`
ObjSizes sizeHistogramV1 `msg:"szs"`
ObjVersions versionsHistogram `msg:"vh"`
ReplicationStats *replicationAllStats `msg:"rs,omitempty"`
AllTierStats *allTierStats `msg:"ats,omitempty"`
Compacted bool `msg:"c"`
}
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
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// dataUsageCache contains a cache of data usage entries latest version.
type dataUsageCache struct {
Info dataUsageCacheInfo
Cache map[string]dataUsageEntry
}
//msgp:encode ignore dataUsageCacheV2 dataUsageCacheV3 dataUsageCacheV4 dataUsageCacheV5 dataUsageCacheV6 dataUsageCacheV7
//msgp:marshal ignore dataUsageCacheV2 dataUsageCacheV3 dataUsageCacheV4 dataUsageCacheV5 dataUsageCacheV6 dataUsageCacheV7
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
2021-05-11 21:36:15 -04:00
// dataUsageCacheV2 contains a cache of data usage entries version 2.
type dataUsageCacheV2 struct {
Info dataUsageCacheInfo
Cache map[string]dataUsageEntryV2
}
// dataUsageCacheV3 contains a cache of data usage entries version 3.
type dataUsageCacheV3 struct {
Info dataUsageCacheInfo
Cache map[string]dataUsageEntryV3
}
// dataUsageCacheV4 contains a cache of data usage entries version 4.
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
2021-05-11 21:36:15 -04:00
type dataUsageCacheV4 struct {
Info dataUsageCacheInfo
Cache map[string]dataUsageEntryV4
}
// dataUsageCacheV5 contains a cache of data usage entries version 5.
type dataUsageCacheV5 struct {
Info dataUsageCacheInfo
Cache map[string]dataUsageEntryV5
}
// dataUsageCacheV6 contains a cache of data usage entries version 6.
type dataUsageCacheV6 struct {
Info dataUsageCacheInfo
Cache map[string]dataUsageEntryV6
}
// dataUsageCacheV7 contains a cache of data usage entries version 7.
type dataUsageCacheV7 struct {
Info dataUsageCacheInfo
Cache map[string]dataUsageEntryV7
}
//msgp:ignore dataUsageEntryInfo
type dataUsageEntryInfo struct {
Name string
Parent string
Entry dataUsageEntry
}
type dataUsageCacheInfo struct {
// Name of the bucket. Also root element.
Name string
NextCycle uint32
LastUpdate time.Time
// indicates if the disk is being healed and scanner
// should skip healing the disk
SkipHealing bool
// Active lifecycle, if any on the bucket
lifeCycle *lifecycle.Lifecycle `msg:"-"`
// optional updates channel.
// If set updates will be sent regularly to this channel.
// Will not be closed when returned.
updates chan<- dataUsageEntry `msg:"-"`
replication replicationConfig `msg:"-"`
}
func (e *dataUsageEntry) addSizes(summary sizeSummary) {
e.Size += summary.totalSize
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
2021-05-11 21:36:15 -04:00
e.Versions += summary.versions
e.DeleteMarkers += summary.deleteMarkers
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
2021-05-11 21:36:15 -04:00
e.ObjSizes.add(summary.totalSize)
e.ObjVersions.add(summary.versions)
if e.ReplicationStats == nil {
e.ReplicationStats = &replicationAllStats{
Targets: make(map[string]replicationStats),
}
} else if e.ReplicationStats.Targets == nil {
e.ReplicationStats.Targets = make(map[string]replicationStats)
}
e.ReplicationStats.ReplicaSize += uint64(summary.replicaSize)
e.ReplicationStats.ReplicaCount += uint64(summary.replicaCount)
for arn, st := range summary.replTargetStats {
tgtStat, ok := e.ReplicationStats.Targets[arn]
if !ok {
tgtStat = replicationStats{}
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
2021-05-11 21:36:15 -04:00
}
tgtStat.PendingSize += uint64(st.pendingSize)
tgtStat.FailedSize += uint64(st.failedSize)
tgtStat.ReplicatedSize += uint64(st.replicatedSize)
tgtStat.ReplicatedCount += uint64(st.replicatedCount)
tgtStat.FailedCount += st.failedCount
tgtStat.PendingCount += st.pendingCount
e.ReplicationStats.Targets[arn] = tgtStat
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
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}
if len(summary.tiers) != 0 {
if e.AllTierStats == nil {
e.AllTierStats = newAllTierStats()
}
e.AllTierStats.addSizes(summary.tiers)
}
}
// merge other data usage entry into this, excluding children.
func (e *dataUsageEntry) merge(other dataUsageEntry) {
e.Objects += other.Objects
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
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e.Versions += other.Versions
e.DeleteMarkers += other.DeleteMarkers
e.Size += other.Size
if other.ReplicationStats != nil {
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
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if e.ReplicationStats == nil {
e.ReplicationStats = &replicationAllStats{Targets: make(map[string]replicationStats)}
} else if e.ReplicationStats.Targets == nil {
e.ReplicationStats.Targets = make(map[string]replicationStats)
}
e.ReplicationStats.ReplicaSize += other.ReplicationStats.ReplicaSize
e.ReplicationStats.ReplicaCount += other.ReplicationStats.ReplicaCount
for arn, stat := range other.ReplicationStats.Targets {
st := e.ReplicationStats.Targets[arn]
e.ReplicationStats.Targets[arn] = replicationStats{
PendingSize: stat.PendingSize + st.PendingSize,
FailedSize: stat.FailedSize + st.FailedSize,
ReplicatedSize: stat.ReplicatedSize + st.ReplicatedSize,
PendingCount: stat.PendingCount + st.PendingCount,
FailedCount: stat.FailedCount + st.FailedCount,
ReplicatedCount: stat.ReplicatedCount + st.ReplicatedCount,
}
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
2021-05-11 21:36:15 -04:00
}
}
for i, v := range other.ObjSizes[:] {
e.ObjSizes[i] += v
}
for i, v := range other.ObjVersions[:] {
e.ObjVersions[i] += v
}
if other.AllTierStats != nil && len(other.AllTierStats.Tiers) != 0 {
if e.AllTierStats == nil {
e.AllTierStats = newAllTierStats()
}
e.AllTierStats.merge(other.AllTierStats)
}
}
// mod returns true if the hash mod cycles == cycle.
// If cycles is 0 false is always returned.
// If cycles is 1 true is always returned (as expected).
func (h dataUsageHash) mod(cycle uint32, cycles uint32) bool {
if cycles <= 1 {
return cycles == 1
}
return uint32(xxhash.Sum64String(string(h)))%cycles == cycle%cycles
}
// modAlt returns true if the hash mod cycles == cycle.
// This is out of sync with mod.
// If cycles is 0 false is always returned.
// If cycles is 1 true is always returned (as expected).
func (h dataUsageHash) modAlt(cycle uint32, cycles uint32) bool {
if cycles <= 1 {
return cycles == 1
}
return uint32(xxhash.Sum64String(string(h))>>32)%(cycles) == cycle%cycles
}
// addChild will add a child based on its hash.
// If it already exists it will not be added again.
func (e *dataUsageEntry) addChild(hash dataUsageHash) {
if _, ok := e.Children[hash.Key()]; ok {
return
}
if e.Children == nil {
e.Children = make(dataUsageHashMap, 1)
}
e.Children[hash.Key()] = struct{}{}
}
// Create a clone of the entry.
func (e dataUsageEntry) clone() dataUsageEntry {
// We operate on a copy from the receiver.
if e.Children != nil {
ch := make(dataUsageHashMap, len(e.Children))
for k, v := range e.Children {
ch[k] = v
}
e.Children = ch
}
if e.ReplicationStats != nil {
// Clone ReplicationStats
e.ReplicationStats = e.ReplicationStats.clone()
}
if e.AllTierStats != nil {
e.AllTierStats = e.AllTierStats.clone()
}
return e
}
// find a path in the cache.
// Returns nil if not found.
func (d *dataUsageCache) find(path string) *dataUsageEntry {
due, ok := d.Cache[hashPath(path).Key()]
if !ok {
return nil
}
return &due
}
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
2021-05-11 21:36:15 -04:00
// isCompacted returns whether an entry is compacted.
// Returns false if not found.
func (d *dataUsageCache) isCompacted(h dataUsageHash) bool {
due, ok := d.Cache[h.Key()]
if !ok {
return false
}
return due.Compacted
}
// findChildrenCopy returns a copy of the children of the supplied hash.
func (d *dataUsageCache) findChildrenCopy(h dataUsageHash) dataUsageHashMap {
ch := d.Cache[h.String()].Children
res := make(dataUsageHashMap, len(ch))
for k := range ch {
res[k] = struct{}{}
}
return res
}
// searchParent will search for the parent of h.
// This is an O(N*N) operation if there is no parent or it cannot be guessed.
func (d *dataUsageCache) searchParent(h dataUsageHash) *dataUsageHash {
want := h.Key()
if idx := strings.LastIndexByte(want, '/'); idx >= 0 {
if v := d.find(want[:idx]); v != nil {
_, ok := v.Children[want]
if ok {
found := hashPath(want[:idx])
return &found
}
}
}
for k, v := range d.Cache {
_, ok := v.Children[want]
if ok {
found := dataUsageHash(k)
return &found
}
}
return nil
}
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
2021-05-11 21:36:15 -04:00
// deleteRecursive will delete an entry recursively, but not change its parent.
func (d *dataUsageCache) deleteRecursive(h dataUsageHash) {
if existing, ok := d.Cache[h.String()]; ok {
// Delete first if there should be a loop.
delete(d.Cache, h.Key())
for child := range existing.Children {
d.deleteRecursive(dataUsageHash(child))
}
}
}
// dui converts the flattened version of the path to madmin.DataUsageInfo.
// As a side effect d will be flattened, use a clone if this is not ok.
func (d *dataUsageCache) dui(path string, buckets []BucketInfo) DataUsageInfo {
e := d.find(path)
if e == nil {
// No entry found, return empty.
return DataUsageInfo{}
}
flat := d.flatten(*e)
dui := DataUsageInfo{
LastUpdate: d.Info.LastUpdate,
ObjectsTotalCount: flat.Objects,
VersionsTotalCount: flat.Versions,
DeleteMarkersTotalCount: flat.DeleteMarkers,
ObjectsTotalSize: uint64(flat.Size),
BucketsCount: uint64(len(e.Children)),
BucketsUsage: d.bucketsUsageInfo(buckets),
TierStats: d.tiersUsageInfo(buckets),
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
2021-05-11 21:36:15 -04:00
}
return dui
}
// replace will add or replace an entry in the cache.
// If a parent is specified it will be added to that if not already there.
// If the parent does not exist, it will be added.
func (d *dataUsageCache) replace(path, parent string, e dataUsageEntry) {
hash := hashPath(path)
if d.Cache == nil {
d.Cache = make(map[string]dataUsageEntry, 100)
}
d.Cache[hash.Key()] = e
if parent != "" {
phash := hashPath(parent)
p := d.Cache[phash.Key()]
p.addChild(hash)
d.Cache[phash.Key()] = p
}
}
// replaceHashed add or replaces an entry to the cache based on its hash.
// If a parent is specified it will be added to that if not already there.
// If the parent does not exist, it will be added.
func (d *dataUsageCache) replaceHashed(hash dataUsageHash, parent *dataUsageHash, e dataUsageEntry) {
if d.Cache == nil {
d.Cache = make(map[string]dataUsageEntry, 100)
}
d.Cache[hash.Key()] = e
if parent != nil {
p := d.Cache[parent.Key()]
p.addChild(hash)
d.Cache[parent.Key()] = p
}
}
// copyWithChildren will copy entry with hash from src if it exists along with any children.
// If a parent is specified it will be added to that if not already there.
// If the parent does not exist, it will be added.
func (d *dataUsageCache) copyWithChildren(src *dataUsageCache, hash dataUsageHash, parent *dataUsageHash) {
if d.Cache == nil {
d.Cache = make(map[string]dataUsageEntry, 100)
}
e, ok := src.Cache[hash.String()]
if !ok {
return
}
d.Cache[hash.Key()] = e
for ch := range e.Children {
if ch == hash.Key() {
scannerLogIf(GlobalContext, errors.New("dataUsageCache.copyWithChildren: Circular reference"))
return
}
d.copyWithChildren(src, dataUsageHash(ch), &hash)
}
if parent != nil {
p := d.Cache[parent.Key()]
p.addChild(hash)
d.Cache[parent.Key()] = p
}
}
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
2021-05-11 21:36:15 -04:00
// reduceChildrenOf will reduce the recursive number of children to the limit
// by compacting the children with the least number of objects.
func (d *dataUsageCache) reduceChildrenOf(path dataUsageHash, limit int, compactSelf bool) {
e, ok := d.Cache[path.Key()]
if !ok {
return
}
if e.Compacted {
return
}
// If direct children have more, compact all.
if len(e.Children) > limit && compactSelf {
flat := d.sizeRecursive(path.Key())
flat.Compacted = true
d.deleteRecursive(path)
d.replaceHashed(path, nil, *flat)
return
}
total := d.totalChildrenRec(path.Key())
if total < limit {
return
}
// Appears to be printed with _MINIO_SERVER_DEBUG=off
// console.Debugf(" %d children found, compacting %v\n", total, path)
leaves := make([]struct {
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
2021-05-11 21:36:15 -04:00
objects uint64
path dataUsageHash
}, total)
// Collect current leaves that have children.
leaves = leaves[:0]
remove := total - limit
var add func(path dataUsageHash)
add = func(path dataUsageHash) {
e, ok := d.Cache[path.Key()]
if !ok {
return
}
if len(e.Children) == 0 {
return
}
sz := d.sizeRecursive(path.Key())
leaves = append(leaves, struct {
objects uint64
path dataUsageHash
}{objects: sz.Objects, path: path})
for ch := range e.Children {
add(dataUsageHash(ch))
}
}
// Add path recursively.
add(path)
sort.Slice(leaves, func(i, j int) bool {
return leaves[i].objects < leaves[j].objects
})
for remove > 0 && len(leaves) > 0 {
// Remove top entry.
e := leaves[0]
candidate := e.path
if candidate == path && !compactSelf {
// We should be the biggest,
// if we cannot compact ourself, we are done.
break
}
removing := d.totalChildrenRec(candidate.Key())
flat := d.sizeRecursive(candidate.Key())
if flat == nil {
leaves = leaves[1:]
continue
}
// Appears to be printed with _MINIO_SERVER_DEBUG=off
// console.Debugf("compacting %v, removing %d children\n", candidate, removing)
flat.Compacted = true
d.deleteRecursive(candidate)
d.replaceHashed(candidate, nil, *flat)
// Remove top entry and subtract removed children.
remove -= removing
leaves = leaves[1:]
}
}
// forceCompact will force compact the cache of the top entry.
// If the number of children is more than limit*100, it will compact self.
// When above the limit a cleanup will also be performed to remove any possible abandoned entries.
func (d *dataUsageCache) forceCompact(limit int) {
if d == nil || len(d.Cache) <= limit {
return
}
top := hashPath(d.Info.Name).Key()
topE := d.find(top)
if topE == nil {
scannerLogIf(GlobalContext, errors.New("forceCompact: root not found"))
return
}
// If off by 2 orders of magnitude, compact self and log error.
if len(topE.Children) > dataScannerForceCompactAtFolders {
// If we still have too many children, compact self.
scannerLogOnceIf(GlobalContext, fmt.Errorf("forceCompact: %q has %d children. Force compacting. Expect reduced scanner performance", d.Info.Name, len(topE.Children)), d.Info.Name)
d.reduceChildrenOf(hashPath(d.Info.Name), limit, true)
}
if len(d.Cache) <= limit {
return
}
// Check for abandoned entries.
found := make(map[string]struct{}, len(d.Cache))
// Mark all children recursively
var mark func(entry dataUsageEntry)
mark = func(entry dataUsageEntry) {
for k := range entry.Children {
found[k] = struct{}{}
if ch, ok := d.Cache[k]; ok {
mark(ch)
}
}
}
found[top] = struct{}{}
mark(*topE)
// Delete all entries not found.
for k := range d.Cache {
if _, ok := found[k]; !ok {
delete(d.Cache, k)
}
}
}
// StringAll returns a detailed string representation of all entries in the cache.
func (d *dataUsageCache) StringAll() string {
// Remove bloom filter from print.
s := fmt.Sprintf("info:%+v\n", d.Info)
for k, v := range d.Cache {
s += fmt.Sprintf("\t%v: %+v\n", k, v)
}
return strings.TrimSpace(s)
}
// String returns a human readable representation of the string.
func (h dataUsageHash) String() string {
return string(h)
}
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
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// Key returns the key.
func (h dataUsageHash) Key() string {
return string(h)
}
func (d *dataUsageCache) flattenChildrens(root dataUsageEntry) (m map[string]dataUsageEntry) {
m = make(map[string]dataUsageEntry)
for id := range root.Children {
e := d.Cache[id]
if len(e.Children) > 0 {
e = d.flatten(e)
}
m[id] = e
}
return m
}
// flatten all children of the root into the root element and return it.
func (d *dataUsageCache) flatten(root dataUsageEntry) dataUsageEntry {
for id := range root.Children {
e := d.Cache[id]
if len(e.Children) > 0 {
e = d.flatten(e)
}
root.merge(e)
}
root.Children = nil
return root
}
// add a size to the histogram.
func (h *sizeHistogram) add(size int64) {
// Fetch the histogram interval corresponding
// to the passed object size.
for i, interval := range ObjectsHistogramIntervals[:] {
if size >= interval.start && size <= interval.end {
h[i]++
break
}
}
}
// mergeV1 is used to migrate data usage cache from sizeHistogramV1 to
// sizeHistogram
func (h *sizeHistogram) mergeV1(v sizeHistogramV1) {
var oidx, nidx int
for oidx < len(v) {
intOld, intNew := ObjectsHistogramIntervalsV1[oidx], ObjectsHistogramIntervals[nidx]
// skip intervals that aren't common to both histograms
if intOld.start != intNew.start || intOld.end != intNew.end {
nidx++
continue
}
h[nidx] += v[oidx]
oidx++
nidx++
}
}
// toMap returns the map to a map[string]uint64.
func (h *sizeHistogram) toMap() map[string]uint64 {
res := make(map[string]uint64, dataUsageBucketLen)
var splCount uint64
for i, count := range h {
szInt := ObjectsHistogramIntervals[i]
switch {
case humanize.KiByte == szInt.start && szInt.end == humanize.MiByte-1:
// spl interval: [1024B, 1MiB)
res[szInt.name] = splCount
case humanize.KiByte <= szInt.start && szInt.end <= humanize.MiByte-1:
// intervals that fall within the spl interval above; they
// appear earlier in this array of intervals, see
// ObjectsHistogramIntervals
splCount += count
fallthrough
default:
res[szInt.name] = count
}
}
return res
}
// add a version count to the histogram.
func (h *versionsHistogram) add(versions uint64) {
// Fetch the histogram interval corresponding
// to the passed object size.
for i, interval := range ObjectsVersionCountIntervals[:] {
if versions >= uint64(interval.start) && versions <= uint64(interval.end) {
h[i]++
break
}
}
}
// toMap returns the map to a map[string]uint64.
func (h *versionsHistogram) toMap() map[string]uint64 {
res := make(map[string]uint64, dataUsageVersionLen)
for i, count := range h {
res[ObjectsVersionCountIntervals[i].name] = count
}
return res
}
func (d *dataUsageCache) tiersUsageInfo(buckets []BucketInfo) *allTierStats {
dst := newAllTierStats()
for _, bucket := range buckets {
e := d.find(bucket.Name)
if e == nil {
continue
}
flat := d.flatten(*e)
if flat.AllTierStats == nil {
continue
}
dst.merge(flat.AllTierStats)
}
if len(dst.Tiers) == 0 {
return nil
}
return dst
}
// bucketsUsageInfo returns the buckets usage info as a map, with
// key as bucket name
func (d *dataUsageCache) bucketsUsageInfo(buckets []BucketInfo) map[string]BucketUsageInfo {
dst := make(map[string]BucketUsageInfo, len(buckets))
for _, bucket := range buckets {
e := d.find(bucket.Name)
if e == nil {
continue
}
flat := d.flatten(*e)
bui := BucketUsageInfo{
Size: uint64(flat.Size),
VersionsCount: flat.Versions,
ObjectsCount: flat.Objects,
DeleteMarkersCount: flat.DeleteMarkers,
ObjectSizesHistogram: flat.ObjSizes.toMap(),
ObjectVersionsHistogram: flat.ObjVersions.toMap(),
}
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
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if flat.ReplicationStats != nil {
bui.ReplicaSize = flat.ReplicationStats.ReplicaSize
bui.ReplicaCount = flat.ReplicationStats.ReplicaCount
bui.ReplicationInfo = make(map[string]BucketTargetUsageInfo, len(flat.ReplicationStats.Targets))
for arn, stat := range flat.ReplicationStats.Targets {
bui.ReplicationInfo[arn] = BucketTargetUsageInfo{
ReplicationPendingSize: stat.PendingSize,
ReplicatedSize: stat.ReplicatedSize,
ReplicationFailedSize: stat.FailedSize,
ReplicationPendingCount: stat.PendingCount,
ReplicationFailedCount: stat.FailedCount,
ReplicatedCount: stat.ReplicatedCount,
}
}
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
2021-05-11 21:36:15 -04:00
}
dst[bucket.Name] = bui
}
return dst
}
// sizeRecursive returns the path as a flattened entry.
func (d *dataUsageCache) sizeRecursive(path string) *dataUsageEntry {
root := d.find(path)
if root == nil || len(root.Children) == 0 {
return root
}
flat := d.flatten(*root)
if flat.ReplicationStats.empty() {
flat.ReplicationStats = nil
}
return &flat
}
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
2021-05-11 21:36:15 -04:00
// totalChildrenRec returns the total number of children recorded.
func (d *dataUsageCache) totalChildrenRec(path string) int {
root := d.find(path)
if root == nil || len(root.Children) == 0 {
return 0
}
n := len(root.Children)
for ch := range root.Children {
n += d.totalChildrenRec(ch)
}
return n
}
// root returns the root of the cache.
func (d *dataUsageCache) root() *dataUsageEntry {
return d.find(d.Info.Name)
}
// rootHash returns the root of the cache.
func (d *dataUsageCache) rootHash() dataUsageHash {
return hashPath(d.Info.Name)
}
// clone returns a copy of the cache with no references to the existing.
func (d *dataUsageCache) clone() dataUsageCache {
clone := dataUsageCache{
Info: d.Info,
Cache: make(map[string]dataUsageEntry, len(d.Cache)),
}
for k, v := range d.Cache {
clone.Cache[k] = v.clone()
}
return clone
}
// merge root of other into d.
// children of root will be flattened before being merged.
// Last update time will be set to the last updated.
func (d *dataUsageCache) merge(other dataUsageCache) {
existingRoot := d.root()
otherRoot := other.root()
if existingRoot == nil && otherRoot == nil {
return
}
if otherRoot == nil {
return
}
if existingRoot == nil {
*d = other.clone()
return
}
if other.Info.LastUpdate.After(d.Info.LastUpdate) {
d.Info.LastUpdate = other.Info.LastUpdate
}
existingRoot.merge(*otherRoot)
eHash := d.rootHash()
for key := range otherRoot.Children {
entry := other.Cache[key]
flat := other.flatten(entry)
existing := d.Cache[key]
// If not found, merging simply adds.
existing.merge(flat)
d.replaceHashed(dataUsageHash(key), &eHash, existing)
}
}
type objectIO interface {
GetObjectNInfo(ctx context.Context, bucket, object string, rs *HTTPRangeSpec, h http.Header, opts ObjectOptions) (reader *GetObjectReader, err error)
PutObject(ctx context.Context, bucket, object string, data *PutObjReader, opts ObjectOptions) (objInfo ObjectInfo, err error)
}
// load the cache content with name from minioMetaBackgroundOpsBucket.
// Only backend errors are returned as errors.
2023-03-09 18:15:46 -05:00
// The loader is optimistic and has no locking, but tries 5 times before giving up.
// If the object is not found, a nil error with empty data usage cache is returned.
func (d *dataUsageCache) load(ctx context.Context, store objectIO, name string) error {
// By default, empty data usage cache
*d = dataUsageCache{}
load := func(name string, timeout time.Duration) (bool, error) {
// Abandon if more than time.Minute, so we don't hold up scanner.
// drive timeout by default is 2 minutes, we do not need to wait longer.
ctx, cancel := context.WithTimeout(ctx, timeout)
defer cancel()
r, err := store.GetObjectNInfo(ctx, minioMetaBucket, pathJoin(bucketMetaPrefix, name), nil, http.Header{}, ObjectOptions{NoLock: true})
2023-03-09 18:15:46 -05:00
if err != nil {
switch err.(type) {
case ObjectNotFound, BucketNotFound:
r, err = store.GetObjectNInfo(ctx, dataUsageBucket, name, nil, http.Header{}, ObjectOptions{NoLock: true})
if err != nil {
switch err.(type) {
case ObjectNotFound, BucketNotFound:
return false, nil
case InsufficientReadQuorum, StorageErr:
return true, nil
}
return false, err
}
err = d.deserialize(r)
r.Close()
return err != nil, nil
2023-03-09 18:15:46 -05:00
case InsufficientReadQuorum, StorageErr:
return true, nil
2023-03-09 18:15:46 -05:00
}
return false, err
}
err = d.deserialize(r)
r.Close()
return err != nil, nil
}
// Caches are read+written without locks,
retries := 0
for retries < 5 {
retry, err := load(name, time.Minute)
if err != nil {
return toObjectErr(err, dataUsageBucket, name)
2023-03-09 18:15:46 -05:00
}
if !retry {
break
}
retry, err = load(name+".bkp", 30*time.Second)
if err == nil && !retry {
// Only return when we have valid data from the backup
break
}
retries++
time.Sleep(time.Duration(rand.Int63n(int64(time.Second))))
}
if retries == 5 {
scannerLogOnceIf(ctx, fmt.Errorf("maximum retry reached to load the data usage cache `%s`", name), "retry-loading-data-usage-cache")
}
return nil
}
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// Maximum running concurrent saves on server.
var maxConcurrentScannerSaves = make(chan struct{}, 4)
// save the content of the cache to minioMetaBackgroundOpsBucket with the provided name.
2023-03-09 18:15:46 -05:00
// Note that no locking is done when saving.
func (d *dataUsageCache) save(ctx context.Context, store objectIO, name string) error {
select {
case <-ctx.Done():
return ctx.Err()
case maxConcurrentScannerSaves <- struct{}{}:
}
buf := bytebufferpool.Get()
defer func() {
<-maxConcurrentScannerSaves
buf.Reset()
bytebufferpool.Put(buf)
}()
if err := d.serializeTo(buf); err != nil {
return err
}
save := func(name string, timeout time.Duration) error {
// Abandon if more than a minute, so we don't hold up scanner.
ctx, cancel := context.WithTimeout(ctx, timeout)
defer cancel()
return saveConfig(ctx, store, pathJoin(bucketMetaPrefix, name), buf.Bytes())
}
defer save(name+".bkp", 5*time.Second) // Keep a backup as well
// drive timeout by default is 2 minutes, we do not need to wait longer.
return save(name, time.Minute)
}
// dataUsageCacheVer indicates the cache version.
// Bumping the cache version will drop data from previous versions
// and write new data with the new version.
const (
dataUsageCacheVerCurrent = 8
dataUsageCacheVerV7 = 7
dataUsageCacheVerV6 = 6
dataUsageCacheVerV5 = 5
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
2021-05-11 21:36:15 -04:00
dataUsageCacheVerV4 = 4
dataUsageCacheVerV3 = 3
dataUsageCacheVerV2 = 2
dataUsageCacheVerV1 = 1
)
// serialize the contents of the cache.
func (d *dataUsageCache) serializeTo(dst io.Writer) error {
// Add version and compress.
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
2021-05-11 21:36:15 -04:00
_, err := dst.Write([]byte{dataUsageCacheVerCurrent})
if err != nil {
return err
}
enc, err := zstd.NewWriter(dst,
zstd.WithEncoderLevel(zstd.SpeedFastest),
zstd.WithWindowSize(1<<20),
zstd.WithEncoderConcurrency(2))
if err != nil {
return err
}
mEnc := msgp.NewWriter(enc)
err = d.EncodeMsg(mEnc)
if err != nil {
return err
}
err = mEnc.Flush()
if err != nil {
return err
}
err = enc.Close()
if err != nil {
return err
}
return nil
}
// deserialize the supplied byte slice into the cache.
func (d *dataUsageCache) deserialize(r io.Reader) error {
var b [1]byte
n, _ := r.Read(b[:])
if n != 1 {
return io.ErrUnexpectedEOF
}
ver := int(b[0])
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
2021-05-11 21:36:15 -04:00
switch ver {
case dataUsageCacheVerV1:
return errors.New("cache version deprecated (will autoupdate)")
case dataUsageCacheVerV2:
// Zstd compressed.
dec, err := zstd.NewReader(r, zstd.WithDecoderConcurrency(2))
if err != nil {
return err
}
defer dec.Close()
dold := &dataUsageCacheV2{}
if err = dold.DecodeMsg(msgp.NewReader(dec)); err != nil {
return err
}
d.Info = dold.Info
d.Cache = make(map[string]dataUsageEntry, len(dold.Cache))
for k, v := range dold.Cache {
d.Cache[k] = dataUsageEntry{
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
2021-05-11 21:36:15 -04:00
Size: v.Size,
Objects: v.Objects,
ObjSizes: v.ObjSizes,
Children: v.Children,
Compacted: len(v.Children) == 0 && k != d.Info.Name,
}
}
return nil
case dataUsageCacheVerV3:
// Zstd compressed.
dec, err := zstd.NewReader(r, zstd.WithDecoderConcurrency(2))
if err != nil {
return err
}
defer dec.Close()
dold := &dataUsageCacheV3{}
if err = dold.DecodeMsg(msgp.NewReader(dec)); err != nil {
return err
}
d.Info = dold.Info
d.Cache = make(map[string]dataUsageEntry, len(dold.Cache))
for k, v := range dold.Cache {
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
2021-05-11 21:36:15 -04:00
due := dataUsageEntry{
Size: v.Size,
Objects: v.Objects,
ObjSizes: v.ObjSizes,
Children: v.Children,
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
2021-05-11 21:36:15 -04:00
}
if v.ReplicatedSize > 0 || v.ReplicaSize > 0 || v.ReplicationFailedSize > 0 || v.ReplicationPendingSize > 0 {
cfg, _ := getReplicationConfig(GlobalContext, d.Info.Name)
if cfg != nil && cfg.RoleArn != "" {
due.ReplicationStats = &replicationAllStats{
Targets: make(map[string]replicationStats),
}
due.ReplicationStats.ReplicaSize = v.ReplicaSize
due.ReplicationStats.Targets[cfg.RoleArn] = replicationStats{
ReplicatedSize: v.ReplicatedSize,
FailedSize: v.ReplicationFailedSize,
PendingSize: v.ReplicationPendingSize,
}
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
2021-05-11 21:36:15 -04:00
}
}
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
2021-05-11 21:36:15 -04:00
due.Compacted = len(due.Children) == 0 && k != d.Info.Name
d.Cache[k] = due
}
return nil
case dataUsageCacheVerV4:
// Zstd compressed.
dec, err := zstd.NewReader(r, zstd.WithDecoderConcurrency(2))
if err != nil {
return err
}
defer dec.Close()
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
2021-05-11 21:36:15 -04:00
dold := &dataUsageCacheV4{}
if err = dold.DecodeMsg(msgp.NewReader(dec)); err != nil {
return err
}
d.Info = dold.Info
d.Cache = make(map[string]dataUsageEntry, len(dold.Cache))
for k, v := range dold.Cache {
due := dataUsageEntry{
Size: v.Size,
Objects: v.Objects,
ObjSizes: v.ObjSizes,
Children: v.Children,
}
empty := replicationStatsV1{}
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
2021-05-11 21:36:15 -04:00
if v.ReplicationStats != empty {
cfg, _ := getReplicationConfig(GlobalContext, d.Info.Name)
if cfg != nil && cfg.RoleArn != "" {
due.ReplicationStats = &replicationAllStats{
Targets: make(map[string]replicationStats),
}
due.ReplicationStats.Targets[cfg.RoleArn] = replicationStats{
ReplicatedSize: v.ReplicationStats.ReplicatedSize,
FailedSize: v.ReplicationStats.FailedSize,
FailedCount: v.ReplicationStats.FailedCount,
PendingSize: v.ReplicationStats.PendingSize,
PendingCount: v.ReplicationStats.PendingCount,
}
due.ReplicationStats.ReplicaSize = v.ReplicationStats.ReplicaSize
}
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
2021-05-11 21:36:15 -04:00
}
due.Compacted = len(due.Children) == 0 && k != d.Info.Name
d.Cache[k] = due
}
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
2021-05-11 21:36:15 -04:00
// Populate compacted value and remove unneeded replica stats.
for k, e := range d.Cache {
if e.ReplicationStats != nil && len(e.ReplicationStats.Targets) == 0 {
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
2021-05-11 21:36:15 -04:00
e.ReplicationStats = nil
}
d.Cache[k] = e
}
return nil
case dataUsageCacheVerV5:
// Zstd compressed.
dec, err := zstd.NewReader(r, zstd.WithDecoderConcurrency(2))
if err != nil {
return err
}
defer dec.Close()
dold := &dataUsageCacheV5{}
if err = dold.DecodeMsg(msgp.NewReader(dec)); err != nil {
return err
}
d.Info = dold.Info
d.Cache = make(map[string]dataUsageEntry, len(dold.Cache))
for k, v := range dold.Cache {
due := dataUsageEntry{
Size: v.Size,
Objects: v.Objects,
ObjSizes: v.ObjSizes,
Children: v.Children,
}
if v.ReplicationStats != nil && !v.ReplicationStats.Empty() {
cfg, _ := getReplicationConfig(GlobalContext, d.Info.Name)
if cfg != nil && cfg.RoleArn != "" {
due.ReplicationStats = &replicationAllStats{
Targets: make(map[string]replicationStats),
}
d.Info.replication = replicationConfig{Config: cfg}
due.ReplicationStats.Targets[cfg.RoleArn] = replicationStats{
ReplicatedSize: v.ReplicationStats.ReplicatedSize,
FailedSize: v.ReplicationStats.FailedSize,
FailedCount: v.ReplicationStats.FailedCount,
PendingSize: v.ReplicationStats.PendingSize,
PendingCount: v.ReplicationStats.PendingCount,
}
due.ReplicationStats.ReplicaSize = v.ReplicationStats.ReplicaSize
}
}
due.Compacted = len(due.Children) == 0 && k != d.Info.Name
d.Cache[k] = due
}
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
2021-05-11 21:36:15 -04:00
// Populate compacted value and remove unneeded replica stats.
for k, e := range d.Cache {
if e.ReplicationStats != nil && len(e.ReplicationStats.Targets) == 0 {
e.ReplicationStats = nil
}
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
2021-05-11 21:36:15 -04:00
d.Cache[k] = e
}
return nil
case dataUsageCacheVerV6:
// Zstd compressed.
dec, err := zstd.NewReader(r, zstd.WithDecoderConcurrency(2))
if err != nil {
return err
}
defer dec.Close()
dold := &dataUsageCacheV6{}
if err = dold.DecodeMsg(msgp.NewReader(dec)); err != nil {
return err
}
d.Info = dold.Info
d.Cache = make(map[string]dataUsageEntry, len(dold.Cache))
for k, v := range dold.Cache {
var replicationStats *replicationAllStats
if v.ReplicationStats != nil {
replicationStats = &replicationAllStats{
Targets: v.ReplicationStats.Targets,
ReplicaSize: v.ReplicationStats.ReplicaSize,
ReplicaCount: v.ReplicationStats.ReplicaCount,
}
}
due := dataUsageEntry{
Children: v.Children,
Size: v.Size,
Objects: v.Objects,
Versions: v.Versions,
ObjSizes: v.ObjSizes,
ReplicationStats: replicationStats,
Compacted: v.Compacted,
}
d.Cache[k] = due
}
return nil
case dataUsageCacheVerV7:
// Zstd compressed.
dec, err := zstd.NewReader(r, zstd.WithDecoderConcurrency(2))
if err != nil {
return err
}
defer dec.Close()
dold := &dataUsageCacheV7{}
if err = dold.DecodeMsg(msgp.NewReader(dec)); err != nil {
return err
}
d.Info = dold.Info
d.Cache = make(map[string]dataUsageEntry, len(dold.Cache))
for k, v := range dold.Cache {
var szHist sizeHistogram
szHist.mergeV1(v.ObjSizes)
d.Cache[k] = dataUsageEntry{
Children: v.Children,
Size: v.Size,
Objects: v.Objects,
Versions: v.Versions,
ObjSizes: szHist,
ReplicationStats: v.ReplicationStats,
Compacted: v.Compacted,
}
}
return nil
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
2021-05-11 21:36:15 -04:00
case dataUsageCacheVerCurrent:
// Zstd compressed.
dec, err := zstd.NewReader(r, zstd.WithDecoderConcurrency(2))
if err != nil {
return err
}
defer dec.Close()
return d.DecodeMsg(msgp.NewReader(dec))
default:
return fmt.Errorf("dataUsageCache: unknown version: %d", ver)
}
}
// Trim this from start+end of hashes.
var hashPathCutSet = dataUsageRoot
func init() {
if dataUsageRoot != string(filepath.Separator) {
hashPathCutSet = dataUsageRoot + string(filepath.Separator)
}
}
// hashPath calculates a hash of the provided string.
func hashPath(data string) dataUsageHash {
if data != dataUsageRoot {
data = strings.Trim(data, hashPathCutSet)
}
return dataUsageHash(path.Clean(data))
}
//msgp:ignore dataUsageHashMap
type dataUsageHashMap map[string]struct{}
// DecodeMsg implements msgp.Decodable
func (z *dataUsageHashMap) DecodeMsg(dc *msgp.Reader) (err error) {
var zb0002 uint32
zb0002, err = dc.ReadArrayHeader()
if err != nil {
err = msgp.WrapError(err)
return
}
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
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if zb0002 == 0 {
*z = nil
return
}
*z = make(dataUsageHashMap, zb0002)
for i := uint32(0); i < zb0002; i++ {
{
var zb0003 string
zb0003, err = dc.ReadString()
if err != nil {
err = msgp.WrapError(err)
return
}
(*z)[zb0003] = struct{}{}
}
}
return
}
// EncodeMsg implements msgp.Encodable
func (z dataUsageHashMap) EncodeMsg(en *msgp.Writer) (err error) {
err = en.WriteArrayHeader(uint32(len(z)))
if err != nil {
err = msgp.WrapError(err)
return
}
for zb0004 := range z {
err = en.WriteString(zb0004)
if err != nil {
err = msgp.WrapError(err, zb0004)
return
}
}
return
}
// MarshalMsg implements msgp.Marshaler
func (z dataUsageHashMap) MarshalMsg(b []byte) (o []byte, err error) {
o = msgp.Require(b, z.Msgsize())
o = msgp.AppendArrayHeader(o, uint32(len(z)))
for zb0004 := range z {
o = msgp.AppendString(o, zb0004)
}
return
}
// UnmarshalMsg implements msgp.Unmarshaler
func (z *dataUsageHashMap) UnmarshalMsg(bts []byte) (o []byte, err error) {
var zb0002 uint32
zb0002, bts, err = msgp.ReadArrayHeaderBytes(bts)
if err != nil {
err = msgp.WrapError(err)
return
}
feat: add dynamic usage cache (#12229) A cache structure will be kept with a tree of usages. The cache is a tree structure where each keeps track of its children. An uncompacted branch contains a count of the files only directly at the branch level, and contains link to children branches or leaves. The leaves are "compacted" based on a number of properties. A compacted leaf contains the totals of all files beneath it. A leaf is only scanned once every dataUsageUpdateDirCycles, rarer if the bloom filter for the path is clean and no lifecycles are applied. Skipped leaves have their totals transferred from the previous cycle. A clean leaf will be included once every healFolderIncludeProb for partial heal scans. When selected there is a one in healObjectSelectProb that any object will be chosen for heal scan. Compaction happens when either: - The folder (and subfolders) contains less than dataScannerCompactLeastObject objects. - The folder itself contains more than dataScannerCompactAtFolders folders. - The folder only contains objects and no subfolders. - A bucket root will never be compacted. Furthermore, if a has more than dataScannerCompactAtChildren recursive children (uncompacted folders) the tree will be recursively scanned and the branches with the least number of objects will be compacted until the limit is reached. This ensures that any branch will never contain an unreasonable amount of other branches, and also that small branches with few objects don't take up unreasonable amounts of space. Whenever a branch is scanned, it is assumed that it will be un-compacted before it hits any of the above limits. This will make the branch rebalance itself when scanned if the distribution of objects has changed. TLDR; With current values: No bucket will ever have more than 10000 child nodes recursively. No single folder will have more than 2500 child nodes by itself. All subfolders are compacted if they have less than 500 objects in them recursively. We accumulate the (non-deletemarker) version count for paths as well, since we are changing the structure anyway.
2021-05-11 21:36:15 -04:00
if zb0002 == 0 {
*z = nil
return bts, nil
}
*z = make(dataUsageHashMap, zb0002)
for i := uint32(0); i < zb0002; i++ {
{
var zb0003 string
zb0003, bts, err = msgp.ReadStringBytes(bts)
if err != nil {
err = msgp.WrapError(err)
return
}
(*z)[zb0003] = struct{}{}
}
}
o = bts
return
}
// Msgsize returns an upper bound estimate of the number of bytes occupied by the serialized message
func (z dataUsageHashMap) Msgsize() (s int) {
s = msgp.ArrayHeaderSize
for zb0004 := range z {
s += msgp.StringPrefixSize + len(zb0004)
}
return
}
2022-07-05 17:45:49 -04:00
//msgp:encode ignore currentScannerCycle
//msgp:decode ignore currentScannerCycle
type currentScannerCycle struct {
current uint64
next uint64
started time.Time
cycleCompleted []time.Time
}
// clone returns a clone.
func (z currentScannerCycle) clone() currentScannerCycle {
z.cycleCompleted = append(make([]time.Time, 0, len(z.cycleCompleted)), z.cycleCompleted...)
return z
}