Callers of this function log the returned error and exit.
So let's just log the error with the given filepath and the call stack
inside the function itself and then exit. This simplifies the code
at callers' place while leaves the same level of debuggability in case of errors.
Callers of these functions log the returned error and then exit. The returned error already contains the path
to directory, which was failed to be created. So let's just log the error together with the call stack
inside these functions. This leaves the debuggability of the returned error at the same level
while allows simplifying the code at callers' side.
While at it, properly use MustMkdirFailIfExist instead of MustMkdirIfNotExist inside inmemoryPart.MustStoreToDisk().
It is expected that the inmemoryPart.MustStoreToDick() must fail if there is already a directory under the given path.
When WriteFileAndSync fails, then the caller eventually logs the error message
and exits. The error message returned by WriteFileAndSync already contains the path
to the file, which couldn't be created. This information alongside the call stack
is enough for debugging the issue. So just use log.Panicf("FATAL: ...") inside MustWriteAndSync().
This simplifies error handling at caller side a bit.
Previously the created part directory listing was fsynced implicitly
when storing metadata.json file in it.
Also remove superflouous fsync for part directory listing,
which was called at blockStreamWriter.MustClose().
After that the metadata.json file is created, so an additional fsync
for the directory contents is needed.
Improperly configured -bigMergeConcurrency command-line flag usually leads to uncontrolled
growth of unmerged parts, which, in turn, increases CPU usage and query durations.
So it is better deprecating this flag. In rare cases -smallMergeConcurrency command-line flag
can be used instead for controlling the concurrency of background merges.
- Use windows.FlushFileBuffers() instead of windows.Fsync() at streamTracker.adviseDontNeed()
for consistency with implementations for other architectures.
- Use filepath.Base() instead of filepath.Split(), since the dir part isn't used.
This simplifies the code a bit.
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/70
This is a follow-up for 43b24164ef
* lib/fs: adds memory map for windows
it should improve performance for file reading
* lib/storage: replace '/' with os specific separator
it must fix an errors for windows
* lib/fs: mention windows fsync support
* lib/filestream: adds fdatasync for windows writes
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/70
This commit changes background merge algorithm, so it becomes compatible with Windows file semantics.
The previous algorithm for background merge:
1. Merge source parts into a destination part inside tmp directory.
2. Create a file in txn directory with instructions on how to atomically
swap source parts with the destination part.
3. Perform instructions from the file.
4. Delete the file with instructions.
This algorithm guarantees that either source parts or destination part
is visible in the partition after unclean shutdown at any step above,
since the remaining files with instructions is replayed on the next restart,
after that the remaining contents of the tmp directory is deleted.
Unfortunately this algorithm doesn't work under Windows because
it disallows removing and moving files, which are in use.
So the new algorithm for background merge has been implemented:
1. Merge source parts into a destination part inside the partition directory itself.
E.g. now the partition directory may contain both complete and incomplete parts.
2. Atomically update the parts.json file with the new list of parts after the merge,
e.g. remove the source parts from the list and add the destination part to the list
before storing it to parts.json file.
3. Remove the source parts from disk when they are no longer used.
This algorithm guarantees that either source parts or destination part
is visible in the partition after unclean shutdown at any step above,
since incomplete partitions from step 1 or old source parts from step 3 are removed
on the next startup by inspecting parts.json file.
This algorithm should work under Windows, since it doesn't remove or move files in use.
This algorithm has also the following benefits:
- It should work better for NFS.
- It fits object storage semantics.
The new algorithm changes data storage format, so it is impossible to downgrade
to the previous versions of VictoriaMetrics after upgrading to this algorithm.
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3236
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3821
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/70
lib{mergset,storage}: prevent possible race condition with logging stats for merges
Previously partwrapper could be release by background process and reference for part may be invalid
during logging stats. It will lead to panic at vmstorage
https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3897
- Use flag.Duration instead of flagutil.Duration for -snapshotCreateTimeout,
since the flagutil.Duration is intended mostly for big durations, e.g. days, months and years,
while the -snapshotCreateTimeout is usually smaller than one hour.
- Add links to https://docs.victoriametrics.com/#how-to-work-with-snapshots in docs/CHANGELOG.md,
so readers could easily find the corresponding docs when reading the changelog.
- Properly remove all the created directories on unsuccessful attempt to create
snapshot in Storage.CreateSnapshot().
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3551
previously historical data backfilling may trigger force merge for previous month every hour
it consumes cpu, disk io and decrease cluster performance.
Following commit fixes it by applying deduplication for InMemoryParts
Assisted merges are intended to be performed by goroutines, which accept the incoming samples,
in order to limit the data ingestion rate.
The worker, which converts pending samples to parts, shouldn't be penalized by assisted merges,
since this may result in increased number of pending rows as seen at https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3647#issuecomment-1385039142
when the assisted merge takes too much time.
Blocked small merges may result into big number of small parts, which, in turn,
may result in increased CPU and memory usage during queries, since queries need to inspect
all the existing small parts.
The issue has been introduced in 8189770c50
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3337
The main purpose of this command-line flag is to increase the lifetime of low-end flash storage
with the limited number of write operations it can perform. Such flash storage is usually
installed on Raspberry PI or similar appliances.
For example, `-inmemoryDataFlushInterval=1h` reduces the frequency of disk write operations
to up to once per hour if the ingested one-hour worth of data fits the limit for in-memory data.
The in-memory data is searchable in the same way as the data stored on disk.
VictoriaMetrics automatically flushes the in-memory data to disk on graceful shutdown via SIGINT signal.
The in-memory data is lost on unclean shutdown (hardware power loss, OOM crash, SIGKILL).
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3337
The panic has been introduced in 68f3a02589
While at it, add padding to shard structs in order to avoid false sharing on mordern CPUs
This should improve scalability on systems with many CPU cores
The ioutil.{Read|Write}File is deprecated since Go1.16 -
see https://tip.golang.org/doc/go1.16#ioutil
VictoriaMetrics needs at least Go1.18, so it is safe to remove ioutil usage
from source code.
This is a follow-up for 02ca2342ab
* lib/storage: bump max merge concurrency for small parts to 15
The change is based on the feedback from users on github.
Thier examples show, that limit of 8 sometimes become a
bottleneck. Users report that without limit concurrency
can climb up to 15-20 merges at once.
Signed-off-by: hagen1778 <roman@victoriametrics.com>
* Update lib/storage/partition.go
Signed-off-by: hagen1778 <roman@victoriametrics.com>
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
* lib/storage: prevent excessive loops when storage is in RO
Returning nil error when storage is in RO mode results
into excessive loops and function calls which could
result into CPU exhaustion. Returning an err instead
will trigger delays in the for loop and save some resources.
Signed-off-by: hagen1778 <roman@victoriametrics.com>
* document the change
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
Workers count for merges affects the max part size during merges. Such behaviour
protects storage from running out of disk space for scenario when all workers
are merging parts with the max size.
This works very well for most cases. But for systems where high number of CPUs
is allocated for vmstorage components this could significantly impact the max
part size and result in more unmerged parts than expected.
While checking multiple production highly loaded setups it was discovered that
`max_over_time(vm_active_merges{type="storage/big}[1h]}"` rarely exceeds 2,
and `max_over_time(vm_active_merges{type="storage/small}[1h]}"` rarely exceeds 4.
The change in this commit limits the max value for concurrency accordingly.
Signed-off-by: hagen1778 <roman@victoriametrics.com>
Previously these caches could exceed limits set via `-memory.allowedPercent` and/or `-memory.allowedBytes`,
since limits were set independently per each data part. If the number of data parts was big, then limits could be exceeded,
which could result to out of memory errors.
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/2007
The vm_cache_size_max_bytes metric can be used for determining caches which reach their capacity via the following query:
vm_cache_size_bytes / vm_cache_size_max_bytes > 0.9
While this may increase CPU and disk IO usage needed for background merge,
this also recudes CPU usage during queries in production. This is because
such queries tend to read recently added data and it is better to have lower number
of parts for such data in order to reduce CPU usage.
This partially reverts ebf8da3730
Previously such parts could remain undeleted for long durations until they are merged with other parts.
This should help for `-retentionPeriod` values smaller than one month.
Previously the limit has been raised to GOMAXPROCS, but it has been appeared that this
increases query latencies since more CPUs are busy with merges.
While at it, substitute `*MergeConcurrencyLimitCh` channels with simple integer limits.
