Trace data can be rather large and compresses fine.
Compress profile data in zip files:
```
277.895.314 before.profiles.zip
152.800.318 after.profiles.zip
```
globalSubscribers.NumSubscribers() is heavily used in S3 requests and it
uses mutex, use atomic.Load instead since it is faster
Co-authored-by: Anis Elleuch <anis@min.io>
always find the right set of online peers for remote listing,
this may have an effect on listing if the server is down - we
should do this to avoid always performing transient operations
on bucket->peerClient that is permanently or down for a long
period.
This refactor is done for few reasons below
- to avoid deadlocks in scenarios when number
of nodes are smaller < actual erasure stripe
count where in N participating local lockers
can lead to deadlocks across systems.
- avoids expiry routines to run 1000 of separate
network operations and routes per disk where
as each of them are still accessing one single
local entity.
- it is ideal to have since globalLockServer
per instance.
- In a 32node deployment however, each server
group is still concentrated towards the
same set of lockers that partipicate during
the write/read phase, unlike previous minio/dsync
implementation - this potentially avoids send
32 requests instead we will still send at max
requests of unique nodes participating in a
write/read phase.
- reduces overall chattiness on smaller setups.
Bonus fixes, we do not need reload format anymore
as the replaced drive is healed locally we only need
to ensure that drive heal reloads the drive properly.
We preserve the UUID of the original order, this means
that the replacement in `format.json` doesn't mean that
the drive needs to be reloaded into memory anymore.
fixes#10791
Design: https://gist.github.com/klauspost/025c09b48ed4a1293c917cecfabdf21c
Gist of improvements:
* Cross-server caching and listing will use the same data across servers and requests.
* Lists can be arbitrarily resumed at a constant speed.
* Metadata for all files scanned is stored for streaming retrieval.
* The existing bloom filters controlled by the crawler is used for validating caches.
* Concurrent requests for the same data (or parts of it) will not spawn additional walkers.
* Listing a subdirectory of an existing recursive cache will use the cache.
* All listing operations are fully streamable so the number of objects in a bucket no
longer dictates the amount of memory.
* Listings can be handled by any server within the cluster.
* Caches are cleaned up when out of date or superseded by a more recent one.
Bonus fixes
- logging improvements to ensure that we don't use
`go logger.LogIf` to avoid runtime.Caller missing
the function name. log where necessary.
- remove unused code at erasure sets
In almost all scenarios MinIO now is
mostly ready for all sub-systems
independently, safe-mode is not useful
anymore and do not serve its original
intended purpose.
allow server to be fully functional
even with config partially configured,
this is to cater for availability of actual
I/O v/s manually fixing the server.
In k8s like environments it will never make
sense to take pod into safe-mode state,
because there is no real access to perform
any remote operation on them.
- select lockers which are non-local and online to have
affinity towards remote servers for lock contention
- optimize lock retry interval to avoid sending too many
messages during lock contention, reduces average CPU
usage as well
- if bucket is not set, when deleteObject fails make sure
setPutObjHeaders() honors lifecycle only if bucket name
is set.
- fix top locks to list out always the oldest lockers always,
avoid getting bogged down into map's unordered nature.
- Add owner information for expiry, locking, unlocking a resource
- TopLocks returns now locks in quorum by default, provides
a way to capture stale locks as well with `?stale=true`
- Simplify the quorum handling for locks to avoid from storage
class, because there were challenges to make it consistent
across all situations.
- And other tiny simplifications to reset locks.
- Implement a new xl.json 2.0.0 format to support,
this moves the entire marshaling logic to POSIX
layer, top layer always consumes a common FileInfo
construct which simplifies the metadata reads.
- Implement list object versions
- Migrate to siphash from crchash for new deployments
for object placements.
Fixes#2111
size calculation in crawler was using the real size
of the object instead of its actual size i.e either
a decrypted or uncompressed size.
this is needed to make sure all other accounting
such as bucket quota and mcs UI to display the
correct values.
This PR adds a new configuration parameter which allows readiness
check to respond within 10secs, this can be reduced to a lower value
if necessary using
```
mc admin config set api ready_deadline=5s
```
or
```
export MINIO_API_READY_DEADLINE=5s
```
This PR is a continuation from #9586, now the
entire parsing logic is fully merged into
bucket metadata sub-system, simplify the
quota API further by reducing the remove
quota handler implementation.
this is a major overhaul by migrating off all
bucket metadata related configs into a single
object '.metadata.bin' this allows us for faster
bootups across 1000's of buckets and as well
as keeps the code simple enough for future
work and additions.
Additionally also fixes#9396, #9394
This PR is to ensure that we call the relevant object
layer APIs for necessary S3 API level functionalities
allowing gateway implementations to return proper
errors as NotImplemented{}
This allows for all our tests in mint to behave
appropriately and can be handled appropriately as
well.
We should allow quorum errors to be send upwards
such that caller can retry while reading bucket
encryption/policy configs when server is starting
up, this allows distributed setups to load the
configuration properly.
Current code didn't facilitate this and would have
never loaded the actual configs during rolling,
server restarts.
This PR allows setting a "hard" or "fifo" quota
restriction at the bucket level. Buckets that
have reached the FIFO quota configured, will
automatically be cleaned up in FIFO manner until
bucket usage drops to configured quota.
If a bucket is configured with a "hard" quota
ceiling, all further writes are disallowed.
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.
this commit avoids lots of tiny allocations, repeated
channel creates which are performed when filtering
the incoming events, unescaping a key just for matching.
also remove deprecated code which is not needed
anymore, avoids unexpected data structure transformations
from the map to slice.
Ritesh H Shukla