After changes at commit 787b9cd. Minimal timestamps for extDB check was performed without context of the index search prefix.
It worked fine for Single node version, but for cluster version a different prefix was used for
metricID search requests. It may lead to incomplete results, if minimal missing timestamp was cached
for the tenant with different ingestion patterns.
Minimal reproducible case is:
- metrics were ingested for tenants 0 and 1
- at some point in time metrics ingestion for tenant 1 stopped
- index records have the following timestamps layout:
tenant 0: 1,2,3,4,5,6
tenant 1: 1,2,3,4
- after indexDB rotation, containsTimeRange lookups may produce
incorrect results:
time range request for tenant 1 - 5:6 caches 5 as min timestamp
request for the same or smaller time range for tenant 0 now returns
empty results.
Second case:
- requests for the tenant without metrics always updates atomic value with incorrect minimal time range for other tenants.
This commit replaces single atomic with map of search prefix keys. It should have slight performance overhead,
but work consistently for cluster version. minMissingTimestamp is cached by prefix search key, which included tenantID.
Since it will be only populated at runtime, it doesn't hold unused tenants for queries.
Related issue:
https://github.com/VictoriaMetrics/VictoriaMetrics/issues/7417
It is possible for in-memory part to be empty if ingested samples are
removed by retention filters. In this case, data will not be discarded
due to retention before creating in memory part. After in-memory parts
merge samples will be removed resulting in creating completely empty
part at destination.
This commit checks for resulting part and skips it, if it's empty.
---------
Signed-off-by: Zakhar Bessarab <z.bessarab@victoriametrics.com>
Related issue:
https://github.com/VictoriaMetrics/VictoriaMetrics/issues/7182
- add a separate index cache for searches which might read through large
amounts of random entries. Primary use-case for this is retention and
downsampling filters, when applying filters background merge needs to
fetch large amount of random entries which pollutes an index cache.
Using different caches allows to reduce effect on memory usage and cache
efficiency of the main cache while still having high cache hit rate. A
separate cache size is 5% of allowed memory.
- reduce size of indexdb/dataBlocks cache in order to free memory for
new sparse cache. Reduced size by 5% and moved this to a separate cache.
- add a separate metricName search which does not cache metric names -
this is needed in order to allow disabling metric name caching when
applying downsampling/retention filters. Applying filters during
background merge accesses random entries, this fills up cache and does
not provide an actual improvement due to random access nature.
Merge performance and memory usage stats before and after the change:
- before
![image](https://github.com/user-attachments/assets/485fffbb-c225-47ae-b5c5-bc8a7c57b36e)
- after
![image](https://github.com/user-attachments/assets/f4ba3440-7c1c-4ec1-bc54-4d2ab431eef5)
---------
Signed-off-by: Zakhar Bessarab <z.bessarab@victoriametrics.com>
This commit fixes the TestStorageRotateIndexDB flaky test reported at:
#6977. Sample test failure: https://pastebin.com/bTSs8HP1
The test fails because one goroutine adds items to the indexDB table
while another goroutine is closing that table. This may happen if
indexDB rotation happens twice during one Storage.add() operation:
- Storage.add() takes the current indexDB and adds index recods to it
- First index db rotation makes the current index DB a previous one
(still ok at this point)
- Second index db rotation removes the indexDB that was current two
rotations earlier. It does this by setting the mustDrop flag to true and
decrementing the ref counter. The ref counter reaches zero which cases
the underlying indexdb table to release its resources gracefully.
Graceful release assumes that the table is not written anymore. But
Storage.add() still adds items to it.
The solution is to increment the indexDB ref counters while it is used
inside add().
The unit test has been changed a little so that the test fails reliably.
The idea is to make add() function invocation to last much longer,
therefore the test inserts not just one record at a time but thouthands
of them.
To see the test fail, just replace the idbsLocked() func with:
```go
unc (s *Storage) idbsLocked2() (*indexDB, *indexDB, func()) {
return s.idbCurr.Load(), s.idbNext.Load(), func() {}
}
```
---------
Signed-off-by: Artem Fetishev <rtm@victoriametrics.com>
### Describe Your Changes
Add support for
https://github.com/VictoriaMetrics/VictoriaMetrics/issues/6930
Calculate `-search.maxUniqueTimeseries` by
`-search.maxConcurrentRequests` and remaining memory if it's **not set**
or **less equal than 0**.
The remaining memory is affected by `-memory.allowedPercent`,
`-memory.allowedBytes` and cgroup memory limit.
### Checklist
The following checks are **mandatory**:
- [x] My change adheres [VictoriaMetrics contributing
guidelines](https://docs.victoriametrics.com/contributing/).
---------
Signed-off-by: hagen1778 <roman@victoriametrics.com>
Co-authored-by: Roman Khavronenko <roman@victoriametrics.com>
(cherry picked from commit 85f60237e2)
Signed-off-by: hagen1778 <roman@victoriametrics.com>
`vm_rows_ignored_total` metric is a metric for users to signalize about
ingestion issues, such as bad timestamp or parsing error.
In commit
a5424e95b3
this metric started to increment each time vmstorage gets NaN. But NaN
is a valid value for Prometheus data model and for Prometheus metrics
exposition format. Exporters from Prometheus ecosystem could expose NaNs
as values for metrics and these values will be delivered to vmstorage
and increment the metric.
Since there is nothing user can do with this, in opposite to parsing
errors or bad timestamps, there is not much sense in incrementing this
metric. So this commit rolls-back `reason="nan_value"` increments.
### Describe Your Changes
Please provide a brief description of the changes you made. Be as
specific as possible to help others understand the purpose and impact of
your modifications.
### Checklist
The following checks are **mandatory**:
- [ ] My change adheres [VictoriaMetrics contributing
guidelines](https://docs.victoriametrics.com/contributing/).
Signed-off-by: hagen1778 <roman@victoriametrics.com>
### Describe Your Changes
Introduce the `-search.maxDeleteSeries` flag that limits the number of
time series that can be deleted with a single
`/api/v1/admin/tsdb/delete_series` call.
Currently, any number can be deleted and if the number is big (millions)
then the operation may result in unaccounted CPU and memory usage spikes
which in some cases may result in OOM kill (see #7027). The flag limits
the number to 30k by default and the users may override it if needed at
the vmstorage start time.
---------
Signed-off-by: Artem Fetishev <rtm@victoriametrics.com>
Co-authored-by: Nikolay <nik@victoriametrics.com>
### Describe Your Changes
Currently it the metricID list is empty it won't be mashalled and as the
result won't be put into the tagFiltersToMetricIDsCache which causes the
cache misses for the corresponding tagFilters. In some setups this
causes severe search speed detradation (see #7009).
The empty metric IDs was covered before but then was accidentally
removed in 6c21439.
This PR restores the coverage of this case.
A new unit test can be used as a proof that empty metricID lists are not
added to the cache (just remove the fix in index_db.go and run the test
to see the result)
Also a benchmark has been added to see the implications of the
compression.
```
user@laptop:~/p/github.com/rtm0/VictoriaMetrics/01/src$ go test ./lib/storage/ -run=NONE -bench BenchmarkMarshalUnmarshalMetricIDs --loggerLevel=ERROR
goos: linux
goarch: amd64
pkg: github.com/VictoriaMetrics/VictoriaMetrics/lib/storage
cpu: 13th Gen Intel(R) Core(TM) i7-1355U
BenchmarkMarshalUnmarshalMetricIDs/numMetricIDs-0-12 3237240 363.5 ns/op 0 compression-rate
BenchmarkMarshalUnmarshalMetricIDs/numMetricIDs-1-12 2831049 451.8 ns/op 0.4706 compression-rate
BenchmarkMarshalUnmarshalMetricIDs/numMetricIDs-10-12 1152764 1009 ns/op 1.667 compression-rate
BenchmarkMarshalUnmarshalMetricIDs/numMetricIDs-100-12 297055 3998 ns/op 5.755 compression-rate
BenchmarkMarshalUnmarshalMetricIDs/numMetricIDs-1000-12 31172 34566 ns/op 8.484 compression-rate
BenchmarkMarshalUnmarshalMetricIDs/numMetricIDs-10000-12 4900 289659 ns/op 9.416 compression-rate
BenchmarkMarshalUnmarshalMetricIDs/numMetricIDs-100000-12 447 2341173 ns/op 9.456 compression-rate
BenchmarkMarshalUnmarshalMetricIDs/numMetricIDs-1000000-12 42 24926928 ns/op 9.468 compression-rate
BenchmarkMarshalUnmarshalMetricIDs/numMetricIDs-10000000-12 5 204098872 ns/op 9.467 compression-rate
PASS
ok github.com/VictoriaMetrics/VictoriaMetrics/lib/storage 15.018s
```
### Checklist
The following checks are **mandatory**:
- [x] My change adheres [VictoriaMetrics contributing
guidelines](https://docs.victoriametrics.com/contributing/).
---------
Signed-off-by: Artem Fetishev <wwctrsrx@gmail.com>
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
The indexSearch.containsTimeRange() function is called for the current indexDB and the previous indexDB
every time when searching for metricIDs by label filters. This function consumes a lot of additional CPU time
for cases when queries with lightweight label filters are sent to VictoriaMetrics at high rate (e.g. thousands of RPS),
like in the issue https://github.com/VictoriaMetrics/VictoriaMetrics/issues/7009 .
Optimize indexSearch.containsTimeRange() function in the following ways:
- Unconditionally return true if this function is called for the current indexDB, since there are very high
chances that the current indexDB contains the data with timestamps in the requested time range.
- Cache the minimum timestamp, which is missing in the indexed data for the previous indexDB.
This is safe to do, since the previous indexDB is readonly.
This optimization eliminates potentially slow lookup in the previous indexDB for typical
use cases when the requested time range is close to the current time.
Previously indexDB.doExtDB() was returning boolean value, which was indicating whether f callback was called.
There is no need in returning this boolean value, since the f callback can determine on itself whether it was called.
This simplifies the code a bit.
While at it, document indexDB.doExtDB().
Make function name and comments more clear.
d8f8822fa5
Signed-off-by: hagen1778 <roman@victoriametrics.com>
Co-authored-by: Nikolay <nik@victoriametrics.com>
* Previously, only metricID->metricName missing index records were
tracked with deadline But it was possible a case for missing
metricID->TSID index records. IndexDB metrics fix exposed misleading
metric for such missing records.
* This commit adds check for metricID->TSID missing index records. And
delete missing metricID entry if it hit 60 second deadline.
Related issue
https://github.com/VictoriaMetrics/VictoriaMetrics/issues/6931
Signed-off-by: f41gh7 <nik@victoriametrics.com>
### Describe Your Changes
Add storage metrics that count records that failed to insert:
- `RowsReceivedTotal`: the number of records that have been received by
the storage from the clients
- `RowsAddedTotal`: the number of records that have actually been
persisted. This value must be equal to `RowsReceivedTotal` if all the
records have been valid ones. But it will be smaller otherwise. The
values of the metrics below should provide the insight of why some
records hasn't been added
- `NaNValueRows`: the number of records whose value was `NaN`
- `StaleNaNValueRows`: the number of records whose value was `Stale NaN`
- `InvalidRawMetricNames`: the number of records whose raw metric name
has failed to unmarshal.
The following metrics existed before this PR and are listed here for
completeness:
- `TooSmallTimestampRows`: the number of records whose timestamp is
negative or is older than retention period
- `TooBigTimestampRows`: the number of records whose timestamp is too
far in the future.
- `HourlySeriesLimitRowsDropped`: the number of records that have not
been added because the hourly series limit has been exceeded.
- `DailySeriesLimitRowsDropped`: the number of records that have not
been added because the daily series limit has been exceeded.
---
Signed-off-by: Artem Fetishev <wwctrsrx@gmail.com>
This patch reverts 1fd3385
After discussing it we've come to conclusion that this is a valid
behavior which can be avoided by deleting the time series only once the
corresponding stale NaNs have been received.
On the other hand, the fix leads to lost stale NaNs in some rare but
valid use cases. For example:
- In a cluster configuration the samples for a given time series are
normally sent to the same vmstorage replica. However, wminsert may
reroute the samples to another replica because the original one is down
or is overloaded. In this case the stale NaN may end up on a replica
that has no data for that time series, but we still want to record that
sample.
Thus, reverting that fix.
---
related issue https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5069
Signed-off-by: Artem Fetishev <wwctrsrx@gmail.com>
follow up
4ecc370acb
### Describe Your Changes
Please provide a brief description of the changes you made. Be as
specific as possible to help others understand the purpose and impact of
your modifications.
### Checklist
The following checks are **mandatory**:
- [ ] My change adheres [VictoriaMetrics contributing
guidelines](https://docs.victoriametrics.com/contributing/).
### Describe Your Changes
This is a follow-up PR: Unit tests introduced in #6872 can now use
RowsAddedTotal counter whose scope was fixed in #6841.
### Checklist
The following checks are **mandatory**:
- [x] My change adheres [VictoriaMetrics contributing
guidelines](https://docs.victoriametrics.com/contributing/).
Signed-off-by: Artem Fetishev <wwctrsrx@gmail.com>
Co-authored-by: Nikolay <nik@victoriametrics.com>
Previously, some extIndexDB metrics were not registered. It resulted
into missing metrics, if metric value was added to the extIndexDB. It's
a usual case for search requests at both indexes.
Current commit updates all metrics from extIndexDB according to the
current IndexDB. It must fix such cases
Related issue:
https://github.com/VictoriaMetrics/VictoriaMetrics/issues/6868
### Describe Your Changes
Please provide a brief description of the changes you made. Be as
specific as possible to help others understand the purpose and impact of
your modifications.
### Checklist
The following checks are **mandatory**:
- [ ] My change adheres [VictoriaMetrics contributing
guidelines](https://docs.victoriametrics.com/contributing/).
`TL;DR` This PR improves the metric IDs search in IndexDB:
- Avoid seaching for metric IDs twice when `maxMetrics` limit is
exceeded
- Use correct error type for indicating that the `maxMetrics` limit is
exceded
- Simplify the logic of deciding between per-day and global index search
A unit test has been added to ensure that this refactoring does not
break anything.
---
Function calls before the fix:
```
idb.searchMetricIDs
|__ is.searchMetricIDs
|__ is.searchMetricIDsInternal
|__ is.updateMetricIDsForTagFilters
|__ is.tryUpdatingMetricIDsForDateRange
| |
|__ is.getMetricIDsForDateAndFilters
```
- `searchMetricIDsInternal` searches metric IDs for each filter set. It
maintains a metric ID set variable which is updated every time the
`updateMetricIDsForTagFilters` function is called. After each successful
call, the function checks the length of the updated metric ID set and if
it is greater than `maxMetrics`, the function returns `too many
timeseries` error.
- `updateMetricIDsForTagFilters` uses either per-day or global index to
search metric IDs for the given filter set. The decision of which index
to use is made is made within the `tryUpdatingMetricIDsForDateRange`
function and if it returns `fallback to global search` error then the
function uses global index by calling `getMetricIDsForDateAndFilters`
with zero date.
- `tryUpdatingMetricIDsForDateRange` first checks if the given time
range is larger than 40 days and if so returns `fallback to global
search` error. Otherwise it proceeds to searching for metric IDs within
that time range by calling `getMetricIDsForDateAndFilters` for each
date.
- `getMetricIDsForDateAndFilters` searches for metric IDs for the given
date and returns `fallback to global search` error if the number of
found metric IDs is greater than `maxMetrics`.
Problems with this solution:
1. The `fallback to global search` error returned by
`getMetricIDsForDateAndFilters` in case when maxMetrics is exceeded is
misleading.
2. If `tryUpdatingMetricIDsForDateRange` proceeds to date range search
and returns `fallback to global search` error (because
`getMetricIDsForDateAndFilters` returns it) then this will trigger
global search in `updateMetricIDsForTagFilters`. However the global
search uses the same maxMetrics value which means this search is
destined to fail too. I.e. the same search is performed twice and fails
twice.
3. `too many timeseries` error is already handled in
`searchMetricIDsInternal` and therefore handing this error in
`updateMetricIDsForTagFilters` is redundant
4. updateMetricIDsForTagFilters is a better place to make a decision on
whether to use per-day or global index.
Solution:
1. Use a dedicated error for `too many timeseries` case
2. Handle `too many timeseries` error in `searchMetricIDsInternal` only
3. Move the per-day or global search decision from
`tryUpdatingMetricIDsForDateRange` to `updateMetricIDsForTagFilters` and
remove `fallback to global search` error.
---------
Signed-off-by: Artem Fetishev <wwctrsrx@gmail.com>
Co-authored-by: Nikolay <nik@victoriametrics.com>
Once the timeseries is in tsidCache, new entries won't be created in
per-day index because the RegisterMetricNames() code does consider
different dates for the same timeseries. So this case has been added.
The same bug exists for AddRows() but it is not manifested because the
index entries are finally created in updatePerDateData().
RegisterMetricNames also updated to increase the newTimeseriesCreated
counter because it actually creates new time series in index.
A unit tests has been added that check all possible data patterns
(different metric names and dates) and code branches in both
RegisterMetricNames and AddRows. The total number of new unit tests is
around 100 which increaded the running time of storage tests by 50%.
---------
Signed-off-by: Artem Fetishev <wwctrsrx@gmail.com>
Co-authored-by: Roman Khavronenko <hagen1778@gmail.com>
### Describe Your Changes
Reduced the scope of rowsAddedTotal variable from global to Storage.
This metric clearly belongs to a given Storage object as it counts the
number of records added by a given Storage instance.
Reducing the scope improves the incapsulation and allows to reset this
variable during the unit tests (i.e. every time a new Storage object is
created by a test, that object gets a new variable).
Signed-off-by: Artem Fetishev <wwctrsrx@gmail.com>
This reverts commit e280d90e9a.
Reason for revert: the updated code doesn't improve the performance of table.MustAddRows for the typical case
when rows contain timestamps belonging to ptws[0].
The performance may be improved in theory for the case when all the rows belong to partiton other than ptws[0],
but this partition is automatically moved to ptws[0] by the code at lines
6aad1d43e9/lib/storage/table.go (L287-L298) ,
so the next time the typical case will work.
Also the updated code makes the code harder to follow, since it introduces an additional level of indirection
with non-trivial semantics inside table.MustAddRows - the partition.TimeRangeInPartition() function.
This function needs to be inspected and understood when reading the code at table.MustAddRows().
This function depends on minTsInRows and maxTsInRows vars, which are defined and initialized
many lines above the partition.TimeRangeInPartition() call. This complicates reading and understanding
the code even more.
The previous code was using clearer loop over rows with the clear call to partition.HasTimestamp()
for every timestamp in the row. The partition.HasTimestamp() call is used in the table.MustAddRows()
function multiple times. This makes the use of partition.HasTimestamp() call more consistent,
easier to understand and easier to maintain comparing to the mix of partition.HasTimestamp() and partition.TimeRangeInPartition()
calls.
Aslo, there is no need in documenting some hardcore software engineering refactoring at docs/CHANGLELOG.md,
since the docs/CHANGELOG.md is intended for VictoriaMetrics users, who may not know software engineering.
The docs/CHANGELOG.md must document user-visible changes, and the docs must be concise and clear for VictoriaMetrics users.
See https://docs.victoriametrics.com/contributing/#pull-request-checklist for more details.
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/pull/6629
### Describe Your Changes
The original logic is not only highly complex but also poorly readable,
so it can be modified to increase readability and reduce time
complexity.
---------
Co-authored-by: Zhu Jiekun <jiekun@victoriametrics.com>
### Describe Your Changes
`Storage.AddRows()` returns an error only in one case: when
`Storage.updatePerDateData()` fails to unmarshal a `metricNameRaw`. But
the same error is treated as a warning when it happens inside
`Storage.add()` or returned by `Storage.prefillNextIndexDB()`.
This commit fixes this inconsistency by treating the error returned by
`Storage.updatePerDateData()` as a warning as well. As a result
`Storage.add()` does not need a return value anymore and so doesn't
`Storage.AddRows()`.
Additionally, this commit adds a unit test that checks all cases that
result in a row not being added to the storage.
---------
Signed-off-by: Artem Fetishev <wwctrsrx@gmail.com>
Co-authored-by: Nikolay <nik@victoriametrics.com>
Pending rows and items unconditionally remain in memory for up to pending{Items,Rows}FlushInterval,
so there is no any sense in setting dataFlushInterval (the interval for guaranteed flush of in-memory data to disk)
to values smaller than pending{Items,Rows}FlushInterval, since this doesn't affect the interval
for flushing pending rows and items from memory to disk.
This is a follow-up for 4c80b17027
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/pull/6221
'any' type is supported starting from Go1.18. Let's consistently use it
instead of 'interface{}' type across the code base, since `any` is easier to read than 'interface{}'.
### Describe Your Changes
Fix Date metricid cache consistency under concurrent use.
When one goroutine calls Has() and does not find the cache entry in the
immutable map it will acquire a lock and check the mutable map. And it
is possible that before that lock is acquired, the entry is moved from
the mutable map to the immutable map by another goroutine causing a
cache miss.
The fix is to check the immutable map again once the lock is acquired.
### Checklist
The following checks are **mandatory**:
- [x ] My change adheres [VictoriaMetrics contributing
guidelines](https://docs.victoriametrics.com/contributing/).
---------
Signed-off-by: Artem Fetishev <wwctrsrx@gmail.com>
Co-authored-by: Nikolay <nik@victoriametrics.com>
* 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