canceled callers might linger around longer,
can potentially overwhelm the system. Instead
provider a caller context and canceled callers
don't hold on to them.
Bonus: we have no reason to cache errors, we should
never cache errors otherwise we can potentially have
quorum errors creeping in unexpectedly. We should
let the cache when invalidating hit the actual resources
instead.
Create new code paths for multiple subsystems in the code. This will
make maintaing this easier later.
Also introduce bugLogIf() for errors that should not happen in the first
place.
* Remove lock for cached operations.
* Rename "Relax" to `ReturnLastGood`.
* Add `CacheError` to allow caching values even on errors.
* Add NoWait that will return current value with async fetching if within 2xTTL.
* Make benchmark somewhat representative.
```
Before: BenchmarkCache-12 16408370 63.12 ns/op 0 B/op
After: BenchmarkCache-12 428282187 2.789 ns/op 0 B/op
```
* Remove `storageRESTClient.scanning`. Nonsensical - RPC clients will not have any idea about scanning.
* Always fetch remote diskinfo metrics and cache them. Seems most calls are requesting metrics.
* Do async fetching of usage caches.
AccountInfo is quite frequently called by the Console UI
login attempts, when many users are logging in it is important
that we provide them with better responsiveness.
- ListBuckets information is cached every second
- Bucket usage info is cached for up to 10 seconds
- Prefix usage (optional) info is cached for up to 10 secs
Failure to update after cache expiration, would still
allow login which would end up providing information
previously cached.
This allows for seamless responsiveness for the Console UI
logins, and overall responsiveness on a heavily loaded
system.
This allows scanner to avoid lengthy scans, skip
things appropriately and also not lose metrics in
any manner.
reduce longer deadlines for usage-cache loads/saves
to match the disk timeout which is 2minutes now per
IOP.
currently getReplicationConfig() failure incorrectly
returns error on unexpected buckets upon upgrade, we
should always calculate usage as much as possible.
prefixes at top level create such as
```
~ mc mb alias/bucket/prefix
```
The prefix/ incorrect appears as prefix__XL_DIR__/
in the accountInfo output, make sure to trim '__XL_DIR__'
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`
- 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>
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.
This change moves away from a unified constructor for plaintext and encrypted
usage. NewPutObjReader is simplified for the plain-text reader use. For
encrypted reader use, WithEncryption should be called on an initialized PutObjReader.
Plaintext:
func NewPutObjReader(rawReader *hash.Reader) *PutObjReader
The hash.Reader is used to provide payload size and md5sum to the downstream
consumers. This is different from the previous version in that there is no need
to pass nil values for unused parameters.
Encrypted:
func WithEncryption(encReader *hash.Reader,
key *crypto.ObjectKey) (*PutObjReader, error)
This method sets up encrypted reader along with the key to seal the md5sum
produced by the plain-text reader (already setup when NewPutObjReader was
called).
Usage:
```
pReader := NewPutObjReader(rawReader)
// ... other object handler code goes here
// Prepare the encrypted hashed reader
pReader, err = pReader.WithEncryption(encReader, objEncKey)
```
few places were still using legacy call GetObject()
which was mainly designed for client response writer,
use GetObjectNInfo() for internal calls instead.
with changes present to automatically throttle crawler
at runtime, there is no need to have an environment
value to disable crawling. crawling is a fundamental
piece for healing, lifecycle and many other features
there is no good reason anyone would need to disable
this on a production system.
* Apply suggestions from code review
Bonus fixes in quota enforcement to use the
new datastructure and use timedValue to cache
a value/reload automatically avoids one less
global variable.
No one really uses FS for large scale accounting
usage, neither we crawl in NAS gateway mode. It is
worthwhile to simply disable this feature as its
not useful for anyone.
Bonus disable bucket quota ops as well in, FS
and gateway mode
The `keepHTTPResponseAlive` would cause errors to be
returned with status OK.
- Add '32' as a filler byte until a response is ready
- '0' to indicate the response is ready to be consumed
- '1' to indicate response has an error which needs
to be returned to the caller
Clear out 'file not found' errors from dir walker, since it may be
in a folder that has been deleted since it was scanned.
data usage tracker and crawler seem to be logging
non-actionable information on console, which is not
useful and is fixed on its own in almost all deployments,
lets keep this logging to minimal.
By monitoring PUT/DELETE and heal operations it is possible
to track changed paths and keep a bloom filter for this data.
This can help prioritize paths to scan. The bloom filter can identify
paths that have not changed, and the few collisions will only result
in a marginal extra workload. This can be implemented on either a
bucket+(1 prefix level) with reasonable performance.
The bloom filter is set to have a false positive rate at 1% at 1M
entries. A bloom table of this size is about ~2500 bytes when serialized.
To not force a full scan of all paths that have changed cycle bloom
filters would need to be kept, so we guarantee that dirty paths have
been scanned within cycle runs. Until cycle bloom filters have been
collected all paths are considered dirty.
- acquire since leader lock for all background operations
- healing, crawling and applying lifecycle policies.
- simplify lifecyle to avoid network calls, which was a
bug in implementation - we should hold a leader and
do everything from there, we have access to entire
name space.
- make listing, walking not interfere by slowing itself
down like the crawler.
- effectively use global context everywhere to ensure
proper shutdown, in cache, lifecycle, healing
- don't read `format.json` for prometheus metrics in
StorageInfo() call.
canonicalize the ENVs such that we can bring these ENVs
as part of the config values, as a subsequent change.
- fix location of per bucket usage to `.minio.sys/buckets/<bucket_name>/usage-cache.bin`
- fix location of the overall usage in `json` at `.minio.sys/buckets/.usage.json`
(avoid conflicts with a bucket named `usage.json` )
- fix location of the overall usage in `msgp` at `.minio.sys/buckets/.usage.bin`
(avoid conflicts with a bucket named `usage.bin`
Change distributed locking to allow taking bulk locks
across objects, reduces usually 1000 calls to 1.
Also allows for situations where multiple clients sends
delete requests to objects with following names
```
{1,2,3,4,5}
```
```
{5,4,3,2,1}
```
will block and ensure that we do not fail the request
on each other.
Remove the random sleep. This is running in 4 goroutines,
so mostly doing nothing.
We use the getSize latency to estimate system load,
meaning when there is little load on the system and
we get the result fast we sleep a little.
If it took a long time we have high load and release
ourselves longer.
We are sleeping inside the mutex so this affects all
goroutines doing IO.
Adding mutex slows down the crawler to avoid large
spikes in CPU, also add millisecond interval jitter
in calculation of disk usage to slow down the spikes
further.
