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.
also additionally make sure errors during deserializer closes
the reader with right error type such that Write() end
actually see the final error, this avoids a waitGroup usage
and waiting.
If the periodic `case <-t.C:` save gets held up for a long time it will end up
synchronize all disk writes for saving the caches.
We add jitter to per set writes so they don't sync up and don't hold a
lock for the write, since it isn't needed anyway.
If an outage prevents writes for a long while we also add individual
waits for each disk in case there was a queue.
Furthermore limit the number of buffers kept to 2GiB, since this could get
huge in large clusters. This will not act as a hard limit but should be enough
for normal operation.
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)
```
If an erasure set had a drive replacement recently, we don't
need to attempt healing on another drive with in the same erasure
set - this would ensure we do not double heal the same content
and also prioritizes usage for such an erasure set to be calculated
sooner.
This ensures that all the prometheus monitoring and usage
trackers to avoid alerts configured, although we cannot
support v1 to v2 here - we can v2 to v3.
PR 038bcd9079 introduced
version '3', we need to make sure that we do not
print an unexpected error instead log a message to
indicate we will auto update the version.
Enforce bucket quotas when crawling has finished.
This ensures that we will not do quota enforcement on old data.
Additionally, delete less if we are closer to quota than we thought.
Bonus fixes in quota enforcement to use the
new datastructure and use timedValue to cache
a value/reload automatically avoids one less
global variable.
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.
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`
Andreas Auernhammer
Harshavardhana
Klaus Post
Krishnan Parthasarathi
Ritesh H Shukla