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
* {app/vmstorage,app/vmselect}: add API to get list of existing tenants
* {app/vmstorage,app/vmselect}: add API to get list of existing tenants
* app/vmselect: fix error message
* {app/vmstorage,app/vmselect}: fix error messages
* app/vmselect: change log level for error handling
* wip
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
The searchTSIDs function was searching for metricIDs matching the the given tag filters
and then was locating the corresponding TSID entries for the found metricIDs.
The TSID entries aren't needed when searching for time series names (aka MetricName),
so this commit removes the uneeded TSID search from the implementation of /api/v1/series API.
This improves perfromance of /api/v1/series calls.
This commit also improves performance a bit for /api/v1/query and /api/v1/query_range calls,
since now these calls cache small metricIDs instead of big TSID entries
in the indexdb/tagFilters cache (now this cache is named indexdb/tagFiltersToMetricIDs)
without the need to compress the saved entries in order to save cache space.
This commit also removes concurrency limiter during searching for matching time series,
which was introduced in 8f16388428, since the concurrency
for all the read queries is already limited with -search.maxConcurrentRequests command-line flag.
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/648
These metrics allow alerting when the number of unique series approach the limit.
For example, the following query alerts when the number of series reaches 90% of the configured limit:
vm_hourly_series_limit_current_series / vm_hourly_series_limit_max_series > 0.9
Previously SearchMetricNames was returning unmarshaled metric names.
This wasn't great for vmstorage, which should spend additional CPU time
for marshaling the metric names before sending them to vmselect.
While at it, remove possible duplicate metric names, which could occur when
multiple samples for new time series are ingested via concurrent requests.
Also sort the metric names before returning them to the client.
This simplifies debugging of the returned metric names across repeated requests to /api/v1/series
This opens doors for implementing vmselect api server at vmselect level,
so top-level vmselect could query lower-level vmselect nodes in the same way
as it queries vmstorage nodes.
This will create the ability to create highly available querying architecture
when multiple independent VictoriaMetrics clusters with the same data
are located in distinct availability zones. In this case we can use top-level
vmselect instead of Promxy for simultaneous querying of all the clusters
in all the AZs.
querytracer has been added to the following storage.Storage methods:
- RegisterMetricNames
- DeleteMetrics
- SearchTagValueSuffixes
- SearchGraphitePaths
Previously the processVMSelectDeleteMetrics was calling separate functions from readSearchQuery().
It is better from readability and maintenance PoV to substitute it with readSearchQuery call.
The default size of `indexdb/tagFilters` now can be overridden via
`storage.cacheSizeIndexDBTagFilters` flag.
Please, be careful with changing default size since it may
lead to inefficient work of the vmstorage or OOM exceptions.
https://github.com/VictoriaMetrics/VictoriaMetrics/issues/2663
Signed-off-by: hagen1778 <roman@victoriametrics.com>
Co-authored-by: Nikolay <nik@victoriametrics.com>
* lib/{storage,flagutil} - Add option for snapshot autoremoval
- add prometheus-like duration as command flag
- add option to delete stale snapshots
- update duration.go flag to re-use own code
* wip
* lib/flagutil: re-use Duration.Set() call in NewDuration
* wip
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
* lib/{storage,regexpcache}: replaces regexpCacheMap with LRU cache
It should decrease memory usage for regexp caching
with storing cacheEntry by pointer - golang map should be able to effectivly shrink it's size
original issue with this case - unexpected map grows and storage OOM
Apply suggestions from code review
Co-authored-by: Roman Khavronenko <roman@victoriametrics.com>
Adds missing metrics for regexp cache and regexpPrefixes cache
* wip
* wip
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
* lib/index: reduce read/write load after indexDB rotation
IndexDB in VM is responsible for storing TSID - ID's used for identifying
time series. The index is stored on disk and used by both ingestion and read path.
IndexDB is stored separately to data parts and is global for all stored data.
It can't be deleted partially as VM deletes data parts. Instead, indexDB is
rotated once in `retention` interval.
The rotation procedure means that `current` indexDB becomes `previous`,
and new freshly created indexDB struct becomes `current`. So in any time,
VM holds indexDB for current and previous retention periods.
When time series is ingested or queried, VM checks if its TSID is present
in `current` indexDB. If it is missing, it checks the `previous` indexDB.
If TSID was found, it gets copied to the `current` indexDB. In this way
`current` indexDB stores only series which were active during the retention
period.
To improve indexDB lookups, VM uses a cache layer called `tsidCache`. Both
write and read path consult `tsidCache` and on miss the relad lookup happens.
When rotation happens, VM resets the `tsidCache`. This is needed for ingestion
path to trigger `current` indexDB re-population. Since index re-population
requires additional resources, every index rotation event may cause some extra
load on CPU and disk. While it may be unnoticeable for most of the cases,
for systems with very high number of unique series each rotation may lead
to performance degradation for some period of time.
This PR makes an attempt to smooth out resource usage after the rotation.
The changes are following:
1. `tsidCache` is no longer reset after the rotation;
2. Instead, each entry in `tsidCache` gains a notion of indexDB to which
they belong;
3. On ingestion path after the rotation we check if requested TSID was
found in `tsidCache`. Then we have 3 branches:
3.1 Fast path. It was found, and belongs to the `current` indexDB. Return TSID.
3.2 Slow path. It wasn't found, so we generate it from scratch,
add to `current` indexDB, add it to `tsidCache`.
3.3 Smooth path. It was found but does not belong to the `current` indexDB.
In this case, we add it to the `current` indexDB with some probability.
The probability is based on time passed since the last rotation with some threshold.
The more time has passed since rotation the higher is chance to re-populate `current` indexDB.
The default re-population interval in this PR is set to `1h`, during which entries from
`previous` index supposed to slowly re-populate `current` index.
The new metric `vm_timeseries_repopulated_total` was added to identify how many TSIDs
were moved from `previous` indexDB to the `current` indexDB. This metric supposed to
grow only during the first `1h` after the last rotation.
https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1401
Signed-off-by: hagen1778 <roman@victoriametrics.com>
* wip
* wip
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
Previously bytesutil.Resize() was copying the original byte slice contents to a newly allocated slice.
This wasted CPU cycles and memory bandwidth in some places, where the original slice contents wasn't needed
after slize resizing. Switch such places to bytesutil.ResizeNoCopy().
Rename the original bytesutil.Resize() function to bytesutil.ResizeWithCopy() for the sake of improved readability.
Additionally, allocate new slice with `make()` instead of `append()`. This guarantees that the capacity of the allocated slice
exactly matches the requested size. The `append()` could return a slice with bigger capacity as an optimization for further `append()` calls.
This could result in excess memory usage when the returned byte slice was cached (for instance, in lib/blockcache).
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/2007
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
* adds read-only mode for vmstorage
https://github.com/VictoriaMetrics/VictoriaMetrics/issues/269
* changes order a bit
* moves isFreeDiskLimitReached var to storage struct
renames functions to be consistent
change protoparser api - with optional storage limit check for given openned storage
* renames freeSpaceLimit to ReadOnly
* Rename -search.maxMetricsPointSearch to -search.maxSamplesPerQuery, so it is more consistent with the existing -search.maxSamplesPerSeries
* Move the -search.maxSamplesPerQuery from vmstorage to vmselect, so it could effectively limit the number of raw samples obtained from all the vmstorage nodes
* Document the -search.maxSamplesPerQuery in docs/CHANGELOG.md
This option can be useful when samples for the same time series are ingested with distinct order of labels.
For example, metric{k1="v1",k2="v2"} and metric{k2="v2",k1="v1"}.
