If more than 1M folders (objects or prefixes) are found at the top level in a bucket allow it to be compacted.
While very suboptimal structure we should limit memory usage at some point.
* Add periodic callhome functionality
Periodically (every 24hrs by default), fetch callhome information and
upload it to SUBNET.
New config keys under the `callhome` subsystem:
enable - Set to `on` for enabling callhome. Default `off`
frequency - Interval between callhome cycles. Default `24h`
* Improvements based on review comments
- Update `enableCallhome` safely
- Rename pctx to ctx
- Block during execution of callhome
- Store parsed proxy URL in global subnet config
- Store callhome URL(s) in constants
- Use existing global transport
- Pass auth token to subnetPostReq
- Use `config.EnableOn` instead of `"on"`
* Use atomic package instead of lock
* Use uber atomic package
* Use `Cancel` instead of `cancel`
Co-authored-by: Harshavardhana <harsha@minio.io>
Co-authored-by: Harshavardhana <harsha@minio.io>
Co-authored-by: Aditya Manthramurthy <donatello@users.noreply.github.com>
We need to make sure if we cannot read bucket metadata
for some reason, and bucket metadata is not missing and
returning corrupted information we should panic such
handlers to disallow I/O to protect the overall state
on the system.
In-case of such corruption we have a mechanism now
to force recreate the metadata on the bucket, using
`x-minio-force-create` header with `PUT /bucket` API
call.
Additionally fix the versioning config updated state
to be set properly for the site replication healing
to trigger correctly.
it seems in some places we have been wrongly using the
timer.Reset() function, nicely exposed by an example
shared by @donatello https://go.dev/play/p/qoF71_D1oXD
this PR fixes all the usage comprehensively
Spark/Hadoop workloads which use Hadoop MR
Committer v1/v2 algorithm upload objects to a
temporary prefix in a bucket. These objects are
'renamed' to a different prefix on Job commit.
Object storage admins are forced to configure
separate ILM policies to expire these objects
and their versions to reclaim space.
Our solution:
This can be avoided by simply marking objects
under these prefixes to be excluded from versioning,
as shown below. Consequently, these objects are
excluded from replication, and don't require ILM
policies to prune unnecessary versions.
- MinIO Extension to Bucket Version Configuration
```xml
<VersioningConfiguration xmlns="http://s3.amazonaws.com/doc/2006-03-01/">
<Status>Enabled</Status>
<ExcludeFolders>true</ExcludeFolders>
<ExcludedPrefixes>
<Prefix>app1-jobs/*/_temporary/</Prefix>
</ExcludedPrefixes>
<ExcludedPrefixes>
<Prefix>app2-jobs/*/__magic/</Prefix>
</ExcludedPrefixes>
<!-- .. up to 10 prefixes in all -->
</VersioningConfiguration>
```
Note: `ExcludeFolders` excludes all folders in a bucket
from versioning. This is required to prevent the parent
folders from accumulating delete markers, especially
those which are shared across spark workloads
spanning projects/teams.
- To enable version exclusion on a list of prefixes
```
mc version enable --excluded-prefixes "app1-jobs/*/_temporary/,app2-jobs/*/_magic," --exclude-prefix-marker myminio/test
```
Healing decisions would align with skipped folder counters. This can lead to files
never being selected for heal checks on "clean" paths.
Use different hashing methods and take objectHealProbDiv into account when
calculating the cycle.
Found by @vadmeste
some upgraded objects might not get listed due
to different quorum ratios across objects.
make sure to list all objects that satisfy the
maximum possible quorum.
This PR removes an unnecessary state that gets
passed around for DiskIDs, which is not necessary
since each disk exactly knows which pool and which
set it belongs to on a running system.
Currently cached DiskId's won't work properly
because it always ends up skipping offline disks
and never runs healing when disks are offline, as
it expects all the cached diskIDs to be present
always. This also sort of made things in-flexible
in terms perhaps a new diskID for `format.json`.
(however this is not a big issue)
This is an unnecessary requirement that healing
via scanner needs all drives to be online, instead
healing should trigger even when partial nodes
and drives are available this ensures that we
keep the SLA in-tact on the objects when disks
are offline for a prolonged period of time.
It is possible that GetLock() call remembers a previously
failed releaseAll() when there are networking issues, now
this state can have potential side effects.
This PR tries to avoid this side affect by making sure
to initialize NewNSLock() for each GetLock() attempts
made to avoid any prior state in the memory that can
interfere with the new lock grants.
A corner case can occur where the delete-marker was propagated
but the metadata could not be updated on the primary. Sending
a RemoveObject call with the Delete marker version would end
up permanently deleting the version on target. Instead, perform
a Stat on the delete-marker version on target and redo replication
only if the delete-marker is missing on target.
After the introduction of Refresh logic in locks, the data scanner can
quit when the data scanner lock is not able to get refreshed. In that
case, the context of the data scanner will get canceled and
runDataScanner() will quit. Another server would pick the scanning
routine but after some time, all nodes can just have all scanning
routine aborted, as described above.
This fix will just run the data scanner in a loop.
- Rename MaxNoncurrentVersions tag to NewerNoncurrentVersions
Note: We apply overlapping NewerNoncurrentVersions rules such that
we honor the highest among applicable limits. e.g if 2 overlapping rules
are configured with 2 and 3 noncurrent versions to be retained, we
will retain 3.
- Expire newer noncurrent versions after noncurrent days
- MinIO extension: allow noncurrent days to be zero, allowing expiry
of noncurrent version as soon as more than configured
NewerNoncurrentVersions are present.
- Allow NewerNoncurrentVersions rules on object-locked buckets
- No x-amz-expiration when NewerNoncurrentVersions configured
- ComputeAction should skip rules with NewerNoncurrentVersions > 0
- Add unit tests for lifecycle.ComputeAction
- Support lifecycle rules with MaxNoncurrentVersions
- Extend ExpectedExpiryTime to work with zero days
- Fix all-time comparisons to be relative to UTC
This unit allows users to limit the maximum number of noncurrent
versions of an object.
To enable this rule you need the following *ilm.json*
```
cat >> ilm.json <<EOF
{
"Rules": [
{
"ID": "test-max-noncurrent",
"Status": "Enabled",
"Filter": {
"Prefix": "user-uploads/"
},
"NoncurrentVersionExpiration": {
"MaxNoncurrentVersions": 5
}
}
]
}
EOF
mc ilm import myminio/mybucket < ilm.json
```
- remove some duplicated code
- reported a bug, separately fixed in #13664
- using strings.ReplaceAll() when needed
- using filepath.ToSlash() use when needed
- remove all non-Go style comments from the codebase
Co-authored-by: Aditya Manthramurthy <donatello@users.noreply.github.com>
also remove HealObjects() code from dataScanner running another
listing from the data-scanner is super in-efficient and in-fact
this code is redundant since we already attempt to heal all
dangling objects anyways.
* reduce extra getObjectInfo() calls during ILM transition
This PR also changes expiration logic to be non-blocking,
scanner is now free from additional costs incurred due
to slower object layer calls and hitting the drives.
* move verifying expiration inside locks
Faster healing as well as making healing more
responsive for faster scanner times.
also fixes a bug introduced in #13079, newly replaced
disks were not healing automatically.
- remove sourceCh usage from healing
we already have tasks and resp channel
- use read locks to lookup globalHealConfig
- fix healing resolver to pick candidates quickly
that need healing, without this resolver was
unexpectedly skipping.
Synchronize bucket cycles so it is much more
likely that the same prefixes will be picked up
for scanning.
Use the global bloom filter cycle for that.
Bump bloom filter versions to clear those.
- deletes should always Sweep() for tiering at the
end and does not need an extra getObjectInfo() call
- puts, copy and multipart writes should conditionally
do getObjectInfo() when tiering targets are configured
- introduce 'TransitionedObject' struct for ease of usage
and understanding.
- multiple-pools optimization deletes don't need to hold
read locks verifying objects across namespace and pools.
Remote caches were not returned correctly, so they would not get updated on save.
Furthermore make some tweaks for more reliable updates.
Invalidate bloom filter to ensure rescan.
auditLog should be attempted right before the
return of the function and not multiple times
per function, this ensures that we only trigger
it once per function call.
- Adds versioning support for S3 based remote tiers that have versioning
enabled. This ensures that when reading or deleting we specify the specific
version ID of the object. In case of deletion, this is important to ensure that
the object version is actually deleted instead of simply being marked for
deletion.
- Stores the remote object's version id in the tier-journal. Tier-journal file
version is not bumped up as serializing the new struct version is
compatible with old journals without the remote object version id.
- `storageRESTVersion` is bumped up as FileInfo struct now includes a
`TransitionRemoteVersionID` member.
- Azure and GCS support for this feature will be added subsequently.
Co-authored-by: Krishnan Parthasarathi <krisis@users.noreply.github.com>
Also adding an API to allow resyncing replication when
existing object replication is enabled and the remote target
is entirely lost. With the `mc replicate reset` command, the
objects that are eligible for replication as per the replication
config will be resynced to target if existing object replication
is enabled on the rule.
This is to ensure that there are no projects
that try to import `minio/minio/pkg` into
their own repo. Any such common packages should
go to `https://github.com/minio/pkg`
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.
upon errors to acquire lock context would still leak,
since the cancel would never be called. since the lock
is never acquired - proactively clear it before returning.
failed queue should be used for retried requests to
avoid cascading the failures into incoming queue, this
would allow for a more fair retry for failed replicas.
Additionally also avoid taking context in queue task
to avoid confusion, simplifies its usage.
* lock: Always cancel the returned Get(R)Lock context
There is a leak with cancel created inside the locking mechanism. The
cancel purpose was to cancel operations such erasure get/put that are
holding non-refreshable locks.
This PR will ensure the created context.Cancel is passed to the unlock
API so it will cleanup and avoid leaks.
* locks: Avoid returning nil cancel in local lockers
Since there is no Refresh mechanism in the local locking mechanism, we
do not generate a new context or cancel. Currently, a nil cancel
function is returned but this can cause a crash. Return a dummy function
instead.
With this change, MinIO's ILM supports transitioning objects to a remote tier.
This change includes support for Azure Blob Storage, AWS S3 compatible object
storage incl. MinIO and Google Cloud Storage as remote tier storage backends.
Some new additions include:
- Admin APIs remote tier configuration management
- Simple journal to track remote objects to be 'collected'
This is used by object API handlers which 'mutate' object versions by
overwriting/replacing content (Put/CopyObject) or removing the version
itself (e.g DeleteObjectVersion).
- Rework of previous ILM transition to fit the new model
In the new model, a storage class (a.k.a remote tier) is defined by the
'remote' object storage type (one of s3, azure, GCS), bucket name and a
prefix.
* Fixed bugs, review comments, and more unit-tests
- Leverage inline small object feature
- Migrate legacy objects to the latest object format before transitioning
- Fix restore to particular version if specified
- Extend SharedDataDirCount to handle transitioned and restored objects
- Restore-object should accept version-id for version-suspended bucket (#12091)
- Check if remote tier creds have sufficient permissions
- Bonus minor fixes to existing error messages
Co-authored-by: Poorna Krishnamoorthy <poorna@minio.io>
Co-authored-by: Krishna Srinivas <krishna@minio.io>
Signed-off-by: Harshavardhana <harsha@minio.io>
This is an optimization to save IOPS. The replication
failures will be re-queued once more to re-attempt
replication. If it still does not succeed, the replication
status is set as `FAILED` and will be caught up on
scanner cycle.
- collect real time replication metrics for prometheus.
- add pending_count, failed_count metric for total pending/failed replication operations.
- add API to get replication metrics
- add MRF worker to handle spill-over replication operations
- multiple issues found with replication
- fixes an issue when client sends a bucket
name with `/` at the end from SetRemoteTarget
API call make sure to trim the bucket name to
avoid any extra `/`.
- hold write locks in GetObjectNInfo during replication
to ensure that object version stack is not overwritten
while reading the content.
- add additional protection during WriteMetadata() to
ensure that we always write a valid FileInfo{} and avoid
ever writing empty FileInfo{} to the lowest layers.
Co-authored-by: Poorna Krishnamoorthy <poorna@minio.io>
Co-authored-by: Harshavardhana <harsha@minio.io>
It is inefficient to decide to heal an object before checking its
lifecycle for expiration or transition. This commit will just reverse
the order of action: evaluate lifecycle and heal only if asked and
lifecycle resulted a NoneAction.
This allows us to speed up or slow down sleeps
between multiple scanner cycles, helps in testing
as well as some deployments might want to run
scanner more frequently.
This change is also dynamic can be applied on
a running cluster, subsequent cycles pickup
the newly set value.
For large objects taking more than '3 minutes' response
times in a single PUT operation can timeout prematurely
as 'ResponseHeader' timeout hits for 3 minutes. Avoid
this by keeping the connection active during CreateFile
phase.
This commit adds a new package `etag` for dealing
with S3 ETags.
Even though ETag is often viewed as MD5 checksum of
an object, handling S3 ETags correctly is a surprisingly
complex task. While it is true that the ETag corresponds
to the MD5 for the most basic S3 API operations, there are
many exceptions in case of multipart uploads or encryption.
In worse, some S3 clients expect very specific behavior when
it comes to ETags. For example, some clients expect that the
ETag is a double-quoted string and fail otherwise.
Non-AWS compliant ETag handling has been a source of many bugs
in the past.
Therefore, this commit adds a dedicated `etag` package that provides
functionality for parsing, generating and converting S3 ETags.
Further, this commit removes the ETag computation from the `hash`
package. Instead, the `hash` package (i.e. `hash.Reader`) should
focus only on computing and verifying the content-sha256.
One core feature of this commit is to provide a mechanism to
communicate a computed ETag from a low-level `io.Reader` to
a high-level `io.Reader`.
This problem occurs when an S3 server receives a request and
has to compute the ETag of the content. However, the server
may also wrap the initial body with several other `io.Reader`,
e.g. when encrypting or compressing the content:
```
reader := Encrypt(Compress(ETag(content)))
```
In such a case, the ETag should be accessible by the high-level
`io.Reader`.
The `etag` provides a mechanism to wrap `io.Reader` implementations
such that the `ETag` can be accessed by a type-check.
This technique is applied to the PUT, COPY and Upload handlers.
currently crawler waits for an entire readdir call to
return until it processes usage, lifecycle, replication
and healing - instead we should pass the applicator all
the way down to avoid building any special stack for all
the contents in a single directory.
This allows for
- no need to remember the entire list of entries per directory
before applying the required functions
- no need to wait for entire readdir() call to finish before
applying the required functions
