* It must reduce memory usage for misbehaving clients. Since
VictoriaMetrics stores sparse index inmemory.
* Reduce disk space usage for indexdb.
* Prevent possible indexDB items drops.
* It may trigger slow insert and new timeseries registration due to
default value for flag change
https://github.com/VictoriaMetrics/VictoriaMetrics/issues/6176
---------
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
Change the return values for these functions - now they return the unmarshaled result plus
the size of the unmarshaled result in bytes, so the caller could re-slice the src for further unmarshaling.
This improves performance of these functions in hot loops of VictoriaLogs a bit.
It is incorrect applying the limit on the number of values to search without applying filters,
since the returned subset of label values may miss the label values matching the given filters.
This is a follow-up for 66630c7960
This speeds up auto-suggestion for metric names in VMUI and Grafana, which use the following query in this case:
/api/v1/label/__name__/values?match[]={__name__=~"*.some_value.*"}
When the user types `some_value` in the query input field.
This should improve debuggability of unexpected deletion of directories inside partitions.
While at it, log the proper path to parts.json when the directory for big part is missing in the partition.
parts.json is located inside directory with small parts, and there is no parts.json file inside directory with big parts.
* lib/storage: add ability to use downsampling for the given series filter
Signed-off-by: Zakhar Bessarab <z.bessarab@victoriametrics.com>
* docs: add information about downsampling filters
Signed-off-by: Zakhar Bessarab <z.bessarab@victoriametrics.com>
* docs: fix MetricsQL filter
Signed-off-by: Zakhar Bessarab <z.bessarab@victoriametrics.com>
* lib/storage/downsampling: treat missing downsampling filter as a bug
Signed-off-by: Zakhar Bessarab <z.bessarab@victoriametrics.com>
* lib/storage/part_header: verify correctness of downsampling filters when opening partition
Signed-off-by: Zakhar Bessarab <z.bessarab@victoriametrics.com>
* lib/storage/downsampling: save only appliable rules in part metadata
Filter and save only rules which are appliable to partition based on MinTimestamp of stored data.
Signed-off-by: Zakhar Bessarab <z.bessarab@victoriametrics.com>
* lib/storage/downsampling: update log messages for final dedup
Properly specify a reason of re-running deduplication for partition.
Signed-off-by: Zakhar Bessarab <z.bessarab@victoriametrics.com>
* lib/storage: consistently use MaxTimestamp to determine deduplication/downsampling rules
Using MinTimestamp leads to applying downsampling to parts which are only partially covered by downsampling rule.
For example, partition covers range [1000-2000]. At t=2100 and rule offset 500 data with t=2100-500 => 1600 must be downsampled. The range check against MinTimestamp evaluates to true even though partition contains range which must not be downsampled - [1600:2000].
Signed-off-by: Zakhar Bessarab <z.bessarab@victoriametrics.com>
* Follow-up
- Apply the first matching downsampling period if multiple filters match the given time series.
This allows fine-tuning the downsampling config for the specific needs.
- Take into account downsampling filters during search queries.
- Reduce the difference between community and enterprise branches. This should simplify further maintenance of these branches.
- Properly parse series filters with colons inside them.
- Document the feature at docs/CHANGELOG.md.
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4960
---------
Signed-off-by: Zakhar Bessarab <z.bessarab@victoriametrics.com>
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
* lib/storage: adds metrics for downsampling
vm_downsampling_partitions_scheduled - shows the number of parts, that must be downsampled
vm_downsampling_partitions_scheduled_size_bytes - shows total size in bytes for parts, the must be donwsampled
These two metrics answer the questions - is downsampling running? how many parts scheduled for downsampling and how many of them currently downsampled? Storage space that it occupies.
https://github.com/VictoriaMetrics/VictoriaMetrics/issues/2612
* wip
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
Store the deadline when the metricID entries must be deleted from indexdb
if metricID->metricName entry isn't found after the deadline. This should
make the code more clear comparing the the previous version, where the timestamp
of the first metricID->metricName lookup miss was stored in missingMetricIDs.
Remove the misleading comment about the importance of the order for creating entries
in the inverted index when registering new time series. The order doesn't matter,
since any subset of the created entries can become visible for search
before any other subset after registering in indexdb.
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5948
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5959
* lib/storage/table: properly wait for force merges to be completed during shutdown
Properly keep track of running background merges and wait for merges completion when closing the table.
Previously, force merge was not in sync with overall storage shutdown which could lead to holding ptw ref.
Signed-off-by: Zakhar Bessarab <z.bessarab@victoriametrics.com>
* docs: add changelog entry
Signed-off-by: Zakhar Bessarab <z.bessarab@victoriametrics.com>
---------
Signed-off-by: Zakhar Bessarab <z.bessarab@victoriametrics.com>
This makes the code less fragile - it is harder to skip the convertToCompositeTagFilterss() call now.
While at it, call indexSearch.containsTimeRange() inside indexSearch.searchMetricIDsInternal()
in order to quickly terminate search of time series in the old indexdb for new time ranges.
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5055
This is a follow-up for 2d31fd7855
This should simplify code maintenance by gradually converting to atomic.* types instead of calling atomic.* functions
on int and bool types.
See ea9e2b19a5
The issue has been introduced in bace9a2501
The improper fix was in the d4c0615dcd ,
since it fixed the issue just by an accident, because Go comiler aligned the rawRowsShards field
by 4-byte boundary inside partition struct.
The proper fix is to use atomic.Int64 field - this guarantees that the access to this field
won't result in unaligned 64-bit atomic operation. See https://github.com/golang/go/issues/50860
and https://github.com/golang/go/issues/19057
Previously the (date, metricID) entries for dates older than the last 2 days were removed.
This could lead to slow check for the (date, metricID) entry in the indexdb during ingesting historical data (aka backfilling).
The issue has been introduced in 431aa16c8d
This commit returns back limits for these endpoints, which have been removed at 5d66ee88bd ,
since it has been appeared that missing limits result in high CPU usage, while the introduced concurrency limiter
results in failed lightweight requests to these endpoints because of timeout when heavyweight requests are executed.
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5055
Do not convert shard items to part when a shard becomes full. Instead, collect multiple
full shards and then convert them to a searchable part at once. This reduces
the number of searchable parts, which, in turn, should increase query performance,
since queries need to scan smaller number of parts.
Previously the interval between item addition and its conversion to searchable in-memory part
could vary significantly because of too coarse per-second precision. Switch from fasttime.UnixTimestamp()
to time.Now().UnixMilli() for millisecond precision. It is OK to use time.Now() for tracking
the time when buffered items must be converted to searchable in-memory parts, since time.Now()
calls aren't located in hot paths.
Increase the flush interval for converting buffered samples to searchable in-memory parts
from one second to two seconds. This should reduce the number of blocks, which are needed
to be processed during high-frequency alerting queries. This, in turn, should reduce CPU usage.
While at it, hardcode the maximum size of rawRows shard to 8Mb, since this size gives the optimal
data ingestion pefromance according to load tests. This reduces memory usage and CPU usage on systems
with big amounts of RAM under high data ingestion rate.
The pooled rawRowsBlock objects occupies big amounts of memory between flushes,
and the flushes are relatively rare. So it is better to don't use the pool
and to allocate rawRow blocks on demand. This should reduce the average
memory usage between flushes.
The buffer can be quite big under high ingestion rate (e.g. more than 100MB).
This leads to increased memory usage between buffer flushes.
So it is better to re-create the buffer on every flush in order to reduce memory usage
between buffer flushes.
Instead, log a sample of these long items once per 5 seconds into error log,
so users could notice and fix the issue with too long labels or too many labels.
Previously this panic could occur in production when ingesting samples with too long labels.
This allows removing importing unneeded command-line flags into binaries, which import lib/storage,
which, in turn, was importing lib/snapshot in order to use Time, Validate and NewName functions.
This is a follow-up for 83e55456e2
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/pull/5738
Entries for the previous dates is usually not used, so there is little sense in keeping them in memory.
This should reduce the size of storage/date_metricID cache, which can be monitored
via vm_cache_entries{type="storage/date_metricID"} metric.
This limit has little sense for these APIs, since:
- Thses APIs frequently result in scanning of all the time series on the given time range.
For example, if extra_filters={datacenter="some_dc"} .
- Users expect these APIs shouldn't hit the -search.maxUniqueTimeseries limit,
which is intended for limiting resource usage at /api/v1/query and /api/v1/query_range requests.
Also limit the concurrency for /api/v1/labels, /api/v1/label/.../values
and /api/v1/series requests in order to limit the maximum memory usage and CPU usage for these API.
This limit shouldn't affect typical use cases for these APIs:
- Grafana dashboard load when dashboard labels should be loaded
- Auto-suggestion list load when editing the query in Grafana or vmui
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5055
- Maintain a separate worker pool per each part type (in-memory, file, big and small).
Previously a shared pool was used for merging all the part types.
A single merge worker could merge parts with mixed types at once. For example,
it could merge simultaneously an in-memory part plus a big file part.
Such a merge could take hours for big file part. During the duration of this merge
the in-memory part was pinned in memory and couldn't be persisted to disk
under the configured -inmemoryDataFlushInterval .
Another common issue, which could happen when parts with mixed types are merged,
is uncontrolled growth of in-memory parts or small parts when all the merge workers
were busy with merging big files. Such growth could lead to significant performance
degradataion for queries, since every query needs to check ever growing list of parts.
This could also slow down the registration of new time series, since VictoriaMetrics
searches for the internal series_id in the indexdb for every new time series.
The third issue is graceful shutdown duration, which could be very long when a background
merge is running on in-memory parts plus big file parts. This merge couldn't be interrupted,
since it merges in-memory parts.
A separate pool of merge workers per every part type elegantly resolves both issues:
- In-memory parts are merged to file-based parts in a timely manner, since the maximum
size of in-memory parts is limited.
- Long-running merges for big parts do not block merges for in-memory parts and small parts.
- Graceful shutdown duration is now limited by the time needed for flushing in-memory parts to files.
Merging for file parts is instantly canceled on graceful shutdown now.
- Deprecate -smallMergeConcurrency command-line flag, since the new background merge algorithm
should automatically self-tune according to the number of available CPU cores.
- Deprecate -finalMergeDelay command-line flag, since it wasn't working correctly.
It is better to run forced merge when needed - https://docs.victoriametrics.com/#forced-merge
- Tune the number of shards for pending rows and items before the data goes to in-memory parts
and becomes visible for search. This improves the maximum data ingestion rate and the maximum rate
for registration of new time series. This should reduce the duration of data ingestion slowdown
in VictoriaMetrics cluster on e.g. re-routing events, when some of vmstorage nodes become temporarily
unavailable.
- Prevent from possible "sync: WaitGroup misuse" panic on graceful shutdown.
This is a follow-up for fa566c68a6 .
Thanks @misutoth to for the inspiration at https://github.com/VictoriaMetrics/VictoriaMetrics/pull/5212
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5190
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3790
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3551
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3337
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3425
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3647
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3641
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/648
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/291
This allows reducing the indexdb/tagFiltersToMetricIDs cache size by 8 on average.
The cache size can be checked via vm_cache_size_bytes{type="indexdb/tagFiltersToMetricIDs"} metric exposed at /metrics page.
Previously, it was not possible to determine which tenant sends metrics with excessive amount of labels of label values.
Signed-off-by: Zakhar Bessarab <z.bessarab@victoriametrics.com>
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
This should smooth CPU and RAM usage spikes related to these periodic tasks,
by reducing the probability that multiple concurrent periodic tasks are performed at the same time.
The dateMetricIDCache puts recently registered (date, metricID) entries into mutable cache protected by the mutex.
The dateMetricIDCache.Has() checks for the entry in the mutable cache when it isn't found in the immutable cache.
Access to the mutable cache is protected by the mutex. This means this access is slow on systems with many CPU cores.
The mutabe cache was merged into immutable cache every 10 seconds in order to avoid slow access to mutable cache.
This means that ingestion of new time series to VictoriaMetrics could result in significant slowdown for up to 10 seconds
because of bottleneck at the mutex.
Fix this by merging the mutable cache into immutable cache after len(cacheItems) / 2
cache hits under the mutex, e.g. when the entry is found in the mutable cache.
This should automatically adjust intervals between merges depending on the addition rate
for new time series (aka churn rate):
- The interval will be much smaller than 10 seconds under high churn rate.
This should reduce the mutex contention for mutable cache.
- The interval will be bigger than 10 seconds under low churn rate.
This should reduce the uneeded work on merging of mutable cache into immutable cache.
- Clarify the bugfix description at docs/CHANGELOG.md
- Simplify the code by accessing prefetchedMetricIDs struct under the lock
instead of using lockless access to immutable struct.
This shouldn't worsen code scalability too much on busy systems with many CPU cores,
since the code executed under the lock is quite small and fast.
This allows removing cloning of prefetchedMetricIDs struct every time
new metric names are pre-fetched. This should reduce load on Go GC,
since the cloning of uin64set.Set struct allocates many new objects.
Before, this cache was limited only by size.
Cache invalidation by time happens with jitter to prevent thundering herd problem.
Signed-off-by: hagen1778 <roman@victoriametrics.com>
* app/vmselect: limit the number of parallel workers by 32
The change should improve performance and memory usage during query processing
on machines with big number of CPU cores. The number of parallel workers for
query processing is controlled via `-search.maxWorkersPerQuery` command-line flag.
By default, the number of workers is limited by the number of available CPU cores,
but not more than 32. The limit can be increased via `-search.maxWorkersPerQuery`.
Signed-off-by: hagen1778 <roman@victoriametrics.com>
* wip
- The `-search.maxWorkersPerQuery` command-line flag doesn't limit resource usage,
so move it from the `resource usage limits` to `troubleshooting` chapter at docs/Single-server-VictoriaMetrics.md
- Make more clear the description for the `-search.maxWorkersPerQuery` command-line flag
- Add the description of `-search.maxWorkersPerQuery` to docs/Cluster-VictoriaMetrics.md
- Limit the maximum value, which can be passed to `-search.maxWorkersPerQuery`, to GOMAXPROCS,
because bigger values may worsen query performance and increase CPU usage
- Improve the the description of the change at docs/CHANGELOG.md. Mark it as FEATURE instead of BUGFIX,
since it is closer to a feature than to a bugfix.
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5087
---------
Signed-off-by: hagen1778 <roman@victoriametrics.com>
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
This should reduce tail latency during data ingestion.
This shouldn't slow down data ingestion in the worst case, since assisted merges are spread among
distinct addRows/addItems calls after this change.
* lib/storage/partition: add check to ensure parts exist on disk
If part exists in parts.json but is missing on disk there will be a misleading error similar to "unexpected number of substrings in the part name".
This change forces verification of part existence and throws a correct error in case it is missing on disk.
Such issue can be result of https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5005 or disk corruption.
Signed-off-by: Zakhar Bessarab <z.bessarab@victoriametrics.com>
* lib/storage/partition: use filepath.Join instead of string concatenation
Signed-off-by: Zakhar Bessarab <z.bessarab@victoriametrics.com>
* lib/storage/partition: add action points for error message
Signed-off-by: Zakhar Bessarab <z.bessarab@victoriametrics.com>
* all: add a check for missing part in lib/mergeset and lib/logstorage
---------
Signed-off-by: Zakhar Bessarab <z.bessarab@victoriametrics.com>
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
* Introduce flagutil.Duration
To avoid conversion bugs
* Fix tests
* Clarify documentation re. month=31 days
* Add fasttime.UnixTime() to obtain time.Time
The goal is to refactor out the last usage of `.Msecs`.
* Use fasttime for time.Now()
* wip
- Remove fasttime.UnixTime(), since it doesn't improve code readability and maintainability
- Run `make docs-sync` for syncing changes from README.md to docs/ folder
- Make lib/flagutil.Duration.Msec private
- Rename msecsPerMonth const to msecsPer31Days in order to be consistent with retention31Days
---------
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
* lib/storage: pre-create timeseries before indexDB rotation
during an hour before indexDB rotation start creating records at the next indexDB
it must improve performance during switch for the next indexDB and remove ingestion issues.
Since there is no need for creation new index records for timeseries already ingested into current indexDB
https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4563
* lib/storage: further work on indexdb rotation optimization
- Document the change at docs/CHAGNELOG.md
- Move back various caches from indexDB to Storage. This makes the change less intrusive.
The dateMetricIDCache now takes into account indexDB generation, so it stores (date, metricID)
entries for both the current and the next indexDB.
- Consolidate the code responsible for idbNext pre-filling into prefillNextIndexDB() function.
This improves code readability and maintainability a bit.
- Rewrite and simplify the code responsible for calculating the next retention timestamp.
Add various tests for corner cases of this code.
- Remove indexdb pre-filling from RegisterMetricNames() function, since this function is rarely called.
It is OK to add indexdb entries on demand in this function. This simplifies the code.
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/1401
* docs/CHANGELOG.md: refer to https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4563
---------
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
This eliminates the need in .(*T) casting for results obtained from Load()
Leave atomic.Value for map, since atomic.Pointer[map[...]...] makes double pointer to map,
because map is already a pointer type.
