Previously the following query could miss rows matching !bar if these rows do not contain foo:
foo OR !bar
This is because of incorrect detection of common tokens for OR filters - all the unsupported filters
were skipped (including the NOT filter (aka `!`)), while in this case zero common tokens must be returned.
While at it, move repetiteve code in TestFilterAnd and TestFilterOr into f function.
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/6554
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/pull/6556
This is needed for avoiding confusion between the `|` operator at `math` pipe and `|` pipe delimiter.
For example, the following query was parsed unexpectedly:
* | math foo / bar | fields x
as
* | math foo / (bar | fields) as x
Substituting `|` with `or` inside `math` pipe fixes this ambiguity.
### 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>
Previously per-token hashes for per-block bloom filters were re-calculated on every scanned block.
This could be slow when the number of tokens is big or when the number of blocks to scan is big.
Pre-calculate hashes for bloom filters and then use them for searching in bloom filters.
This improves performance by 2.5x for in(...) filters with many values to search inside `in()`.
Previous bugfix at 49f63b2 only partially fixed pagination host validation error.
Before this fix it was:
```
unexpected nextLink host \"management.azure.com\", expecting \"https://management.azure.com\"
```
Now we only check the `Host` without schema.
However, when Azure respond `nextLink` in `Host:Port` format, the
`nextLink` check will fail:
```
unexpected nextLink host \"management.azure.com:443\", expecting \"management.azure.com\"
```
This pull request further relaxes the checks by only checking the
`Hostname`.
---
related issue: https://github.com/VictoriaMetrics/VictoriaMetrics/issues/6912
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/).
Previously (f1:foo OR f2:bar) was incorrectly returning `foo` token for `f1` and `bar` token for `f2`.
These tokens were used for checking against bloom filter for every data block, so the data block,
which didn't contain simultaneously `foo` token for `f1` field and `bar` token for `f2` field, was skipped.
This was incorrect, since such a block may contain logs matching the original OR filter.
The fix is to return common tokens from `OR`-delimted filters only if these tokens exist at EVERY such filter
for the given field name. If some `OR`-delimited filter misses the given field name, then `OR`-delimited filters
do not contain common tokens, which could be used for checking against bloom filter.
While at it, add more tests covering various edge cases for filters delimited by AND and OR.
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/6554
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/pull/6556
Commit adds the following changes:
* Adds support of OpenTelemetry logs for Victoria Logs with protobuf encoded messages
* json encoding is not supported for the following reasons:
- It brings a lot of fragile code, which works inefficiently.
- json encoding is impossible to use with language SDK.
* splits metrics and logs structures at lib/protoparser/opentelemetry/pb package.
* adds docs with examples for opentelemetry logs.
---
Related issue: https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4839
Co-authored-by: AndrewChubatiuk <andrew.chubatiuk@gmail.com>
Co-authored-by: f41gh7 <nik@victoriametrics.com>
fix#6554
andfilter shouldn't return orfilter field which result in bloomfilter
return false.
---------
Co-authored-by: hagen1778 <roman@victoriametrics.com>
### 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>
### Describe Your Changes
fsync() ensures that the data is written to disk. In production this is
needed for data durability. However, during the development, when the
unit tests are run, this level of durability is not needed. Therefore
fsync() can be disabled which will makes test runs two times faster.
The disabling is done by setting the `DISABLE_FSYNC_FOR_TESTING`
environment variable. The valid values for this variable are the same as
the values of the arg of `go doc strconv.ParseBool`:
```
1, t, T, TRUE, true, True, 0, f, F, FALSE, false, False.
```
Any other value means `false`.
The variable is set for all test build targets. Compare running times:
Build Target | DISABLE_FSYNC_FOR_TESTING=0 | DISABLE_FSYNC_FOR_TESTING=1
----------------- | ------------------------------------------------ |
-------------------------------------------------
make test | 1m5s | 0m22s
make test-race | 3m1s | 1m42s
make test-pure | 1m7s | 0m20s
make test-full | 1m21s | 0m32s
make test-full-386 | 1m42s | 0m36s
When running tests for a given package, fsync can be disabled as
follows:
```shell
DISABLE_FSYNC_FOR_TESTING=1 go test ./lib/storage
```
Disabling fsync() is intended for testing purposes only and the name of
the variables reflects that.
What could also have been done but haven't:
- lib/filestream/filestream.go: `Writer.MustFlush()` also uses f.Sync()
but nothing has been done to it, because the Writer.MustFlush() is not
used anywhere in the VM codebase. A side question: what is the general
policy for the unused code?
- lib/filestream/filestream.go: Writer.Write() calls `adviceDontNeed()`
which calls unix.Fdatasync(). Disabling it could potentially improve
running time, but running tests with this code disabled has shown
otherwise.
### 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>
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>
In the previous commit 8958cecad6
the default ports (80/443) were removed for both the `scrapeURL` and
`instance` label values for those targets without a port in
`__address__`. Different values in the `instance` label generate new
time series.
This commit reverts the changes made to the `instance` label. Now,
for those targets:
- `scrapeURL` will remain unchanged.
- The `instance` label value will include the default port.
https://github.com/VictoriaMetrics/VictoriaMetrics/issues/6792
* Adds custom dial func for HTTP-Connect and socks5 proxy tunnels.
Standard golang http.transport exposes GetProxyConnectHeader function,
but it doesn't allow to use separate tls config for proxy.
It also not possible to enforce HTTP-Connect with standard http lib.
* For http scrape targets, by default http.Transport.Proxy function must
be used. Since it has special case with full uri forward.
* Adds proxy.URL json methods that allow to properly copy internal
fields, like User/Password.
It should fix bug with proxy_url. When credentials specified at URL was
ignored.
* Adds tests for scrape client proxy requests
related issue https://github.com/VictoriaMetrics/VictoriaMetrics/issues/6771
* It was necessary to add default ports for fasthttp client. After migration to the std.httpclient it's no longer needed.
* An additional configuration is required at proxy servers with implicitly set 80/443 ports to the host header (such as HA proxy.
It's expected that after upgrade __address_ label may change. But it should be rare case. 80/443 ports are not widely used at monitoring ecosystem. And it shouldn't have much impact.
Related issue https://github.com/VictoriaMetrics/VictoriaMetrics/issues/6792
Co-authored-by: Nikolay <nik@victoriametrics.com>
…eep_metric_names` options in stream aggregation config together
With aggregated data and raw data under the same metric, results would
be confusing.
---------
Signed-off-by: hagen1778 <roman@victoriametrics.com>
Co-authored-by: hagen1778 <roman@victoriametrics.com>
### Describe Your Changes
This helps to improve reliability of performing backups in environments
with unreliable connection and tolerate temporary errors at S3 provider
side.
See: https://github.com/VictoriaMetrics/VictoriaMetrics/issues/6732
Default retry timeout is up to 3 minutes to make this consistent with
the same configuration for GCS:
a05317f61f/lib/backup/gcsremote/gcs.go (L70-L76)
### Checklist
The following checks are **mandatory**:
- [x] My change adheres [VictoriaMetrics contributing
guidelines](https://docs.victoriametrics.com/contributing/).
---------
Signed-off-by: Zakhar Bessarab <z.bessarab@victoriametrics.com>
Before, buffer growth was always x2 of its size, which could lead to
excessive memory usage when processing big amount of data.
For example, scraping a target with hundreds of MBs in response could
result into hih memory spikes in vmagent because buffer has to double
its size to fit the response. See
https://github.com/VictoriaMetrics/VictoriaMetrics/issues/6759
The change smoothes out the growth rate, trading higher allocation rate
for lower mem usage at certain conditions.
---------
Signed-off-by: hagen1778 <roman@victoriametrics.com>
The resetState arg was used only for the BenchmarkAggregatorsFlushInternalSerial benchmark.
This benchmark was testing aggregate state flush performance by keeping the same state across flushes.
The benhmark didn't reflect the performance and scalability of stream aggregation in production,
while it led to non-trivial code changes related to resetState arg handling.
So let's drop the benchmark together with all the code related to resetState handling,
in order to simplify the code at lib/streamaggr a bit.
Thanks to @AndrewChubatiuk for the original idea at https://github.com/VictoriaMetrics/VictoriaMetrics/pull/6314
Prevsiously every aggregation output was using its own timestamp for the output aggregated samples
in a single aggregation interval. This could result in unexpected inconsitent timesetamps for the output
aggregated samples.
This commit consistently uses the same timestamp across all the output aggregated samples.
This commit makes sure that the duration between subsequent timestamps strictly equals
the configured aggregation interval.
Thanks to @AndrewChubatiuk for the original idea at https://github.com/VictoriaMetrics/VictoriaMetrics/pull/6314
This commit should help https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4580
By introducing this feature, users will have the ability to customize
the sampleLimit parameter on a per-target basis, providing more
flexibility and control over the job execution behavior.
### Describe Your Changes
This is useful for clients which validate InfluxDB is available before
data ingestion can be started.
See: https://github.com/VictoriaMetrics/VictoriaMetrics/issues/6653
### Checklist
The following checks are **mandatory**:
- [x] My change adheres [VictoriaMetrics contributing
guidelines](https://docs.victoriametrics.com/contributing/).
---------
Signed-off-by: Zakhar Bessarab <z.bessarab@victoriametrics.com>
Signed-off-by: hagen1778 <roman@victoriametrics.com>
Co-authored-by: hagen1778 <roman@victoriametrics.com>
Validate files specified via `-tlsKeyFile` and `-tlsCertFile` cmd-line flags on the process start-up. Previously, validation happened on the first connection accepted by HTTP server.
https://github.com/VictoriaMetrics/VictoriaMetrics/issues/6608
---------
Co-authored-by: hagen1778 <roman@victoriametrics.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>
- Mention that credentials can be configured via env variables at both vmbackup and vmrestore docs.
- Make clear that the AZURE_STORAGE_DOMAIN env var is optional at https://docs.victoriametrics.com/vmbackup/#providing-credentials-via-env-variables
- Use string literals as is for env variable names instead of indirecting them via string constants.
This makes easier to read and understand the code. These environment variable names aren't going to change
in the future, so there is no sense in hiding them under string constants with some other names.
- Refer to https://docs.victoriametrics.com/vmbackup/#providing-credentials-via-env-variables in error messages
when auth creds are improperly configured. This should simplify figuring out how to fix the error.
- Simplify the code a bit at FS.newClient(), so it is easier to follow it now.
While at it, remove the check when superflouos environment variables are set, since it is too fragile
and it looks like it doesn't help properly configuring vmbackup / vmrestore.
- Remove envLookuper indirection - just use 'func(name string) (string, bool)' type inline.
This simplifies code reading and understanding.
- Split TestFSInit() into TestFSInit_Failure() and TestFSInit_Success(). This simplifies the test code,
so it should be easier to maintain in the future.
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/pull/6518
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5984
The %q formatter may result in incorrectly formatted JSON string if the original string
contains special chars such as \x1b . They must be encoded as \u001b , otherwise the resulting JSON string
cannot be parsed by JSON parsers.
This is a follow-up for c0caa69939
See https://github.com/VictoriaMetrics/victorialogs-datasource/issues/24
- Clarify the description of -graphite.sanitizeMetricName command-line flag at README.md
- Do not sanitize tag values - only metric names and tag names must be sanitized,
since they are treated specially by Grafana. Grafana doesn't apply any restrictions on tag values.
- Properly replace more than two consecutive dots with a single dot.
- Disallow unicode letters in metric names and tag names, since neither Prometheus nor Grafana
do not support them.
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/pull/6489
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/6077
### 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>
- Obtain IAM token via GCE-like API instead of Amazon EC2 IMDSv2 API,
since it looks like IMDBSv2 API isn't supported by Yandex Cloud
according to https://yandex.cloud/en/docs/security/standard/authentication#aws-token :
> So far, Yandex Cloud does not support version 2, so it is strongly recommended
> to technically disable getting a service account token via the Amazon EC2 metadata service.
- Try obtaining IAM token via GCE-like API at first and then fall back to the deprecated Amazon EC2 IMDBSv1.
This should prevent from auth errors for instances with disabled GCE-like auth API.
This addresses @ITD27M01 concern at https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5513#issuecomment-1867794884
- Make more clear the description of the change at docs/CHANGELOG.md , add reference to the related issue.
P.S. This change wasn't tested in prod because I have no access to Yandex Cloud.
It is recommended to test this change by @ITD27M01 and @vmazgo , who filed
the issue https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5513
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/pull/6524
- Rename GetStatDialFunc to NewStatDialFunc, since it returns new function with every call
- NewStatDialFunc isn't related to http in any way, so it must be moved from lib/httputils to lib/netutil
- Simplify the implementation of NewStatDialFunc by removing sync.Map from there.
- Use netutil.NewStatDialFunc at app/vmauth and lib/promscrape/discoveryutils
- Use gauge instead of counter type for *_conns metric
This is a follow-up for d7b5062917
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/pull/6299
- Move the remaining code responsible for stream aggregation initialization from remotewrite.go to streamaggr.go .
This improves code maintainability a bit.
- Properly shut down streamaggr.Aggregators initialized inside remotewrite.CheckStreamAggrConfigs().
This prevents from potential resource leaks.
- Use separate functions for initializing and reloading of global stream aggregation and per-remoteWrite.url stream aggregation.
This makes the code easier to read and maintain. This also fixes INFO and ERROR logs emitted by these functions.
- Add an ability to specify `name` option in every stream aggregation config. This option is used as `name` label
in metrics exposed by stream aggregation at /metrics page. This simplifies investigation of the exposed metrics.
- Add `path` label additionally to `name`, `url` and `position` labels at metrics exposed by streaming aggregation.
This label should simplify investigation of the exposed metrics.
- Remove `match` and `group` labels from metrics exposed by streaming aggregation, since they have little practical applicability:
it is hard to use these labels in query filters and aggregation functions.
- Rename the metric `vm_streamaggr_flushed_samples_total` to less misleading `vm_streamaggr_output_samples_total` .
This metric shows the number of samples generated by the corresponding streaming aggregation rule.
This metric has been added in the commit 861852f262 .
See https://github.com/VictoriaMetrics/VictoriaMetrics/pull/6462
- Remove the metric `vm_streamaggr_stale_samples_total`, since it is unclear how it can be used in practice.
This metric has been added in the commit 861852f262 .
See https://github.com/VictoriaMetrics/VictoriaMetrics/pull/6462
- Remove Alias and aggrID fields from streamaggr.Options struct, since these fields aren't related to optional params,
which could modify the behaviour of the constructed streaming aggregator.
Convert the Alias field to regular argument passed to LoadFromFile() function, since this argument is mandatory.
- Pass Options arg to LoadFromFile() function by reference, since this structure is quite big.
This also allows passing nil instead of Options when default options are enough.
- Add `name`, `path`, `url` and `position` labels to `vm_streamaggr_dedup_state_size_bytes` and `vm_streamaggr_dedup_state_items_count` metrics,
so they have consistent set of labels comparing to the rest of streaming aggregation metrics.
- Convert aggregator.aggrStates field type from `map[string]aggrState` to `[]aggrOutput`, where `aggrOutput` contains the corresponding
`aggrState` plus all the related metrics (currently only `vm_streamaggr_output_samples_total` metric is exposed with the corresponding
`output` label per each configured output function). This simplifies and speeds up the code responsible for updating per-output
metrics. This is a follow-up for the commit 2eb1bc4f81 .
See https://github.com/VictoriaMetrics/VictoriaMetrics/pull/6604
- Added missing urls to docs ( https://docs.victoriametrics.com/stream-aggregation/ ) in error messages. These urls help users
figuring out why VictoriaMetrics or vmagent generates the corresponding error messages. The urls were removed for unknown reason
in the commit 2eb1bc4f81 .
- Fix incorrect update for `vm_streamaggr_output_samples_total` metric in flushCtx.appendSeriesWithExtraLabel() function.
While at it, reduce memory usage by limiting the maximum number of samples per flush to 10K.
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5467
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/pull/6268
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
- Consistently enumerate stream aggregation outputs in alphabetical order across the source code and docs.
This should simplify future maintenance of the corresponding code and docs.
- Fix the link to `rate_sum()` at `see also` section of `rate_avg()` docs.
- Make more clear the docs for `rate_sum()` and `rate_avg()` outputs.
- Encapsulate output metric suffix inside rateAggrState. This eliminates possible bugs related
to incorrect suffix passing to newRateAggrState().
- Rename rateAggrState.total field to less misleading rateAggrState.increase name, since it calculates
counter increase in the current aggregation window.
- Set rateLastValueState.prevTimestamp on the first sample in time series instead of the second sample.
This makes more clear the code logic.
- Move the code for removing outdated entries at rateAggrState into removeOldEntries() function.
This make the code logic inside rateAggrState.flushState() more clear.
- Do not write output sample with zero value if there are no input series, which could be used
for calculating the rate, e.g. if only a single sample is registered for every input series.
- Do not take into account input series with a single registered sample when calculating rate_avg(),
since this leads to incorrect results.
- Move {rate,total}AggrState.flushState() function to the end of rate.go and total.go files, so they look more similar.
This shuld simplify future mantenance.
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/pull/6243
- Drop samples and return true from remotewrite.TryPush() at fast path when all the remote storage
systems are configured with the disabled on-disk queue, every in-memory queue is full
and -remoteWrite.dropSamplesOnOverload is set to true. This case is quite common,
so it should be optimized. Previously additional CPU time was spent on per-remoteWriteCtx
relabeling and other processing in this case.
- Properly count the number of dropped samples inside remoteWriteCtx.pushInternalTrackDropped().
Previously dropped samples were counted only if -remoteWrite.dropSamplesOnOverload flag is set.
In reality, the samples are dropped when they couldn't be sent to the queue because in-memory queue is full
and on-disk queue is disabled.
The remoteWriteCtx.pushInternalTrackDropped() function is called by streaming aggregation for pushing
the aggregated data to the remote storage. Streaming aggregation cannot wait until the remote storage
processes pending data, so it drops aggregated samples in this case.
- Clarify the description for -remoteWrite.disableOnDiskQueue command-line flag at -help output,
so it is clear that this flag can be set individually per each -remoteWrite.url.
- Make the -remoteWrite.dropSamplesOnOverload flag global. If some of the remote storage systems
are configured with the disabled on-disk queue, then there is no sense in keeping samples
on some of these systems, while dropping samples on the remaining systems, since this
will result in global stall on the remote storage system with the disabled on-disk queue
and with the -remoteWrite.dropSamplesOnOverload=false flag. vmagent will always return false
from remotewrite.TryPush() in this case. This will result in infinite duplicate samples
written to the remaining remote storage systems. That's why the -remoteWrite.dropSamplesOnOverload
is forcibly set to true if more than one -remoteWrite.disableOnDiskQueue flag is set.
This allows proceeding with newly scraped / pushed samples by sending them to the remaining
remote storage systems, while dropping them on overloaded systems with the -remoteWrite.disableOnDiskQueue flag set.
- Verify that the remoteWriteCtx.TryPush() returns true in the TestRemoteWriteContext_TryPush_ImmutableTimeseries test.
- Mention in vmagent docs that the -remoteWrite.disableOnDiskQueue command-line flag can be set individually per each -remoteWrite.url.
See https://docs.victoriametrics.com/vmagent/#disabling-on-disk-persistence
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/pull/6248
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/pull/6065
This makes test code more clear and reduces the number of code lines by 500.
This also simplifies debugging tests. See https://itnext.io/f-tests-as-a-replacement-for-table-driven-tests-in-go-8814a8b19e9e
While at it, consistently use t.Fatal* instead of t.Error* across tests, since t.Error*
requires more boilerplate code, which can result in additional bugs inside tests.
While t.Error* allows writing logging errors for the same, this doesn't simplify fixing
broken tests most of the time.
This is a follow-up for a9525da8a4
We use `vm_streamaggr_flushed_samples_total` to show the number of
produced samples by aggregation rule, previously it was overcounted, and
doesn't account for `output_relabel_configs`.
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/pull/6462
---------
Signed-off-by: hagen1778 <roman@victoriametrics.com>
Co-authored-by: hagen1778 <roman@victoriametrics.com>
### Describe Your Changes
These changes support using Azure Managed Identity for the `vmbackup`
utility. It adds two new environment variables:
* `AZURE_USE_DEFAULT_CREDENTIAL`: Instructs the `vmbackup` utility to
build a connection using the [Azure Default
Credential](https://pkg.go.dev/github.com/Azure/azure-sdk-for-go/sdk/azidentity@v1.5.2#NewDefaultAzureCredential)
mode. This causes the Azure SDK to check for a variety of environment
variables to try and make a connection. By default, it tries to use
managed identity if that is set up.
This will close
https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5984
### Checklist
The following checks are **mandatory**:
- [x] My change adheres [VictoriaMetrics contributing
guidelines](https://docs.victoriametrics.com/contributing/).
### Testing
However you normally test the `vmbackup` utility using Azure Blob should
continue to work without any changes. The set up for that is environment
specific and not listed out here.
Once regression testing has been done you can set up [Azure Managed
Identity](https://learn.microsoft.com/en-us/entra/identity/managed-identities-azure-resources/overview)
so your resource (AKS, VM, etc), can use that credential method. Once it
is set up, update your environment variables according to the updated
documentation.
I added unit tests to the `FS.Init` function, then made my changes, then
updated the unit tests to capture the new branches.
I tested this in our environment, but with SAS token auth and managed
identity and it works as expected.
---------
Signed-off-by: Zakhar Bessarab <z.bessarab@victoriametrics.com>
Co-authored-by: Justin Rush <jarush@epic.com>
Co-authored-by: Zakhar Bessarab <z.bessarab@victoriametrics.com>
Co-authored-by: hagen1778 <roman@victoriametrics.com>
'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{}'.
This makes easier to read and debug these tests. This also reduces test lines count by 15% from 3K to 2.5K
See https://itnext.io/f-tests-as-a-replacement-for-table-driven-tests-in-go-8814a8b19e9e
While at it, consistently use t.Fatal* instead of t.Error*, since t.Error* usually leads
to more complicated and fragile tests, while it doesn't bring any practical benefits over t.Fatal*.
Reason for revert:
There are many statsd servers exist:
- https://github.com/statsd/statsd - classical statsd server
- https://docs.datadoghq.com/developers/dogstatsd/ - statsd server from DataDog built into DatDog Agent ( https://docs.datadoghq.com/agent/ )
- https://github.com/avito-tech/bioyino - high-performance statsd server
- https://github.com/atlassian/gostatsd - statsd server in Go
- https://github.com/prometheus/statsd_exporter - statsd server, which exposes the aggregated data as Prometheus metrics
These servers can be used for efficient aggregating of statsd data and sending it to VictoriaMetrics
according to https://docs.victoriametrics.com/#how-to-send-data-from-graphite-compatible-agents-such-as-statsd (
the https://github.com/prometheus/statsd_exporter can be scraped as usual Prometheus target
according to https://docs.victoriametrics.com/#how-to-scrape-prometheus-exporters-such-as-node-exporter ).
Adding support for statsd data ingestion protocol into VictoriaMetrics makes sense only if it provides
significant advantages over the existing statsd servers, while has no significant drawbacks comparing
to existing statsd servers.
The main advantage of statsd server built into VictoriaMetrics and vmagent - getting rid of additional statsd server.
The main drawback is non-trivial and inconvenient streaming aggregation configs, which must be used for the ingested statsd metrics (
see https://docs.victoriametrics.com/stream-aggregation/ ). These configs are incompatible with the configs for standalone statsd servers.
So you need to manually translate configs of the used statsd server to stream aggregation configs when migrating
from standalone statsd server to statsd server built into VictoriaMetrics (or vmagent).
Another important drawback is that it is very easy to shoot yourself in the foot when using built-in statsd server
with the -statsd.disableAggregationEnforcement command-line flag or with improperly configured streaming aggregation.
In this case the ingested statsd metrics will be stored to VictoriaMetrics as is without any aggregation.
This may result in high CPU usage during data ingestion, high disk space usage for storing all the unaggregated
statsd metrics and high CPU usage during querying, since all the unaggregated metrics must be read, unpacked and processed
during querying.
P.S. Built-in statsd server can be added to VictoriaMetrics and vmagent after figuring out more ergonomic
specialized configuration for aggregating of statsd metrics. The main requirements for this configuration:
- easy to write, read and update (ideally it should work out of the box for most cases without additional configuration)
- hard to misconfigure (e.g. hard to shoot yourself in the foot)
It would be great if this configuration will be compatible with the configuration of the most widely used statsd server.
In the mean time it is recommended continue using external statsd server.
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/pull/6265
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/pull/5053
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5052
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/206
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/4600
This reverts commit 5a3abfa041.
Reason for revert: exemplars aren't in wide use because they have numerous issues which prevent their adoption (see below).
Adding support for examplars into VictoriaMetrics introduces non-trivial code changes. These code changes need to be supported forever
once the release of VictoriaMetrics with exemplar support is published. That's why I don't think this is a good feature despite
that the source code of the reverted commit has an excellent quality. See https://docs.victoriametrics.com/goals/ .
Issues with Prometheus exemplars:
- Prometheus still has only experimental support for exemplars after more than three years since they were introduced.
It stores exemplars in memory, so they are lost after Prometheus restart. This doesn't look like production-ready feature.
See 0a2f3b3794/content/docs/instrumenting/exposition_formats.md (L153-L159)
and https://prometheus.io/docs/prometheus/latest/feature_flags/#exemplars-storage
- It is very non-trivial to expose exemplars alongside metrics in your application, since the official Prometheus SDKs
for metrics' exposition ( https://prometheus.io/docs/instrumenting/clientlibs/ ) either have very hard-to-use API
for exposing histograms or do not have this API at all. For example, try figuring out how to expose exemplars
via https://pkg.go.dev/github.com/prometheus/client_golang@v1.19.1/prometheus .
- It looks like exemplars are supported for Histogram metric types only -
see https://pkg.go.dev/github.com/prometheus/client_golang@v1.19.1/prometheus#Timer.ObserveDurationWithExemplar .
Exemplars aren't supported for Counter, Gauge and Summary metric types.
- Grafana has very poor support for Prometheus exemplars. It looks like it supports exemplars only when the query
contains histogram_quantile() function. It queries exemplars via special Prometheus API -
https://prometheus.io/docs/prometheus/latest/querying/api/#querying-exemplars - (which is still marked as experimental, btw.)
and then displays all the returned exemplars on the graph as special dots. The issue is that this doesn't work
in production in most cases when the histogram_quantile() is calculated over thousands of histogram buckets
exposed by big number of application instances. Every histogram bucket may expose an exemplar on every timestamp shown on the graph.
This makes the graph unusable, since it is litterally filled with thousands of exemplar dots.
Neither Prometheus API nor Grafana doesn't provide the ability to filter out unneeded exemplars.
- Exemplars are usually connected to traces. While traces are good for some
I doubt exemplars will become production-ready in the near future because of the issues outlined above.
Alternative to exemplars:
Exemplars are marketed as a silver bullet for the correlation between metrics, traces and logs -
just click the exemplar dot on some graph in Grafana and instantly see the corresponding trace or log entry!
This doesn't work as expected in production as shown above. Are there better solutions, which work in production?
Yes - just use time-based and label-based correlation between metrics, traces and logs. Assign the same `job`
and `instance` labels to metrics, logs and traces, so you can quickly find the needed trace or log entry
by these labes on the time range with the anomaly on metrics' graph.
- Export streamaggr.LoadFromData() function, so it could be used in tests outside the lib/streamaggr package.
This allows removing a hack with creation of temporary files at TestRemoteWriteContext_TryPush_ImmutableTimeseries.
- Move common code for mustParsePromMetrics() function into lib/prompbmarshal package,
so it could be used in tests for building []prompbmarshal.TimeSeries from string.
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/6205
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/pull/6206
- Clarify docs for `Ignore aggregation intervals on start` feature.
- Make more clear the code dealing with ignoreFirstIntervals at aggregator.runFlusher() functions.
It is better from readability and maintainability PoV using distinct a.flush() calls
for distinct cases instead of merging them into a single a.flush() call.
- Take into account the first incomplete interval when tracking the number of skipped aggregation intervals,
since this behaviour is easier to understand by the end users.
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/pull/6137
### Describe Your Changes
Added flag to sanitize graphite metrics
fixes#6077
### Checklist
The following checks are **mandatory**:
- [ ] My change adheres [VictoriaMetrics contributing
guidelines](https://docs.victoriametrics.com/contributing/).
---------
Signed-off-by: hagen1778 <roman@victoriametrics.com>
Co-authored-by: hagen1778 <roman@victoriametrics.com>
### Describe Your Changes
- added stale metrics counters for input and output samples
- added labels for aggregator metrics =>
`name="{rwctx}:{aggrId}:{aggrSuffix}"`
- rwctx - global or number starting from 1
- aggrid - aggregator id starting from 1
- aggrSuffix - <interval>_(by|without)_label1_label2_labeln
e.g: `name="global:1:1m_without_instance_pod"`
### Checklist
The following checks are **mandatory**:
- [ ] My change adheres [VictoriaMetrics contributing
guidelines](https://docs.victoriametrics.com/contributing/).
---------
Signed-off-by: hagen1778 <roman@victoriametrics.com>
Co-authored-by: hagen1778 <roman@victoriametrics.com>
The set of log fields in the found logs may differ from the set of log fields present in the log stream.
So compare only the log fields in the found logs when searching for the matching log entry in the log stream.
While at it, return _stream field in the delimiter log entry, since this field is used by VictoriaLogs Web UI
for grouping logs by log streams.
### 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>
The TryParseTimestampRFC3339Nano() must properly parse RFC3339 timestamps with timezone offsets.
While at it, make tryParseTimestampISO8601 function private in order to prevent
from improper usage of this function from outside the lib/logstorage package.
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/6508
Reason for revert: this commit doesn't resolve real security issues,
while it complicates the resulting code in subtle ways (aka security circus).
Comparison of two strings (passwords, auth keys) takes a few nanoseconds.
This comparison is performed in non-trivial http handler, which takes thousands
of nanoseconds, and the request handler timing is non-deterministic because of Go runtime,
Go GC and other concurrently executed goroutines. The request handler timing is even
more non-deterministic when the application is executed in shared environments
such as Kubernetes, where many other applications may run on the same host and use
shared resources of this host (CPU, RAM bandwidth, network bandwidth).
Additionally, it is expected that the passwords and auth keys are passed via TLS-encrypted connections.
Establishing TLS connections takes additional non-trivial time (millions of nanoseconds),
which depends on many factors such as network latency, network congestion, etc.
This makes impossible to conduct timing attack on passwords and auth keys in VictoriaMetrics components.
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/pull/6423/files
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/issues/6392
### Describe Your Changes
Fixed a small typo in a comment about the mutex inside the FastQueue
struct
### Checklist
The following checks are **mandatory**:
- [x] My change adheres [VictoriaMetrics contributing
guidelines](https://docs.victoriametrics.com/contributing/).
### Describe Your Changes
Trimming content which is loaded from an external pass leads to obscure
issues in case user-defined input contained trimmed chars. For example.
user-defined password "foo\n" will become "foo" while user will expect
it to contain a new line.
---
For example, a user defines a password which ends with `\n`. This often
happens when user Kubernetes secrets and manually encodes value as
base64-encoded string.
In this case vmauth configuration might look like:
```
users:
- url_prefix:
- http://vminsert:8480/insert/0/prometheus/api/v1/write
name: foo
username: foo
password: "foobar\n"
```
vmagent configuration for this setup will use the following flags:
```
-remoteWrite.url=http://vmauth:8427/
-remoteWrite.basicAuth.passwordFile=/tmp/vmagent-password
-remoteWrite.basicAuth.username="foo"
```
Where `/tmp/vmagent-password` is a file with `foobar\n` password.
Before this change such configuration will result in `401 Unauthorized`
response received by vmagent since after file content will become
`foobar`.
---
An example with Kubernetes operator which uses a secret to reference the
same password in multiple configurations.
<details>
<summary>See full manifests</summary>
`Secret`:
```
apiVersion: v1
data:
name: Zm9v # foo
password: Zm9vYmFy # foobar\n
username: Zm9v= # foo
kind: Secret
metadata:
name: vmuser
```
`VMUser`:
```
apiVersion: operator.victoriametrics.com/v1beta1
kind: VMUser
metadata:
name: vmagents
spec:
generatePassword: false
name: vmagents
targetRefs:
- crd:
kind: VMAgent
name: some-other-agent
namespace: example
username: foo
# note - the secret above is referenced to provide password
passwordRef:
name: vmagent
key: password
```
`VMAgent`:
```
apiVersion: operator.victoriametrics.com/v1beta1
kind: VMAgent
metadata:
name: example
spec:
selectAllByDefault: true
scrapeInterval: 5s
replicaCount: 1
remoteWrite:
- url: "http://vmauth-vmauth-example:8427/api/v1/write"
# note - the secret above is referenced as well
basicAuth:
username:
name: vmagent
key: username
password:
name: vmagent
key: password
```
</details>
Since both config target exactly the same `Secret` object it is expected
to work, but apparently the result will be `401 Unauthrized` error.
### Checklist
The following checks are **mandatory**:
- [x] My change adheres [VictoriaMetrics contributing
guidelines](https://docs.victoriametrics.com/contributing/).
---------
Signed-off-by: Zakhar Bessarab <z.bessarab@victoriametrics.com>
Signed-off-by: hagen1778 <roman@victoriametrics.com>
Co-authored-by: hagen1778 <roman@victoriametrics.com>
Check for ranged vector arguments in aggregate expressions when
`-search.disableImplicitConversion` or `-search.logImplicitConversion`
are enabled.
For example, `sum(up[5m])` will fail to execute if these flags are set.
### 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
* check if `lastValue` was seen at least twice with different
timestamps. Otherwise, the difference between last timestamp and
previous timestamp could be `0` and will result into `NaN` calculation
* check if there items left in lastValue map after staleness cleanup.
Otherwise, `rate_avg` could have produce `NaN` result.
### 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>
Previously byte slices up to 2^20 bytes (e.g. 1Mb) were cached because of a typo in the commit c14dafce43 .
This could result in increased memory usage when vmagent scrapes many regular targets, which expose
relatively small number of metrics (e.g. up to a few thousand per target) and a few large targets such as kube-state-metrics,
which expose more than 10 thousand metrics. This is common case for Kubernetes monitoring.
While at it, remove pools for very small byte slices, since they are rarely used during scraping.
- Make it in a separate goroutine, so it doesn't slow down regular intern() calls.
- Do not lock internStringMap.mutableLock during the cleanup routine, since now
it is called from a single goroutine and reads only the readonly part of the internStringMap.
This should prevent from locking regular intern() calls for new strings during cleanups.
- Add jitter to the cleanup interval in order to prevent from synchornous increase in resource usage
during cleanups.
- Run the cleanup twice per -internStringCacheExpireDuration . This should save 30% CPU time spent
on cleanup comparing to the previous code, which was running the cleanup 3 times per -internStringCacheExpireDuration .
This change fixes the following panic:
```
2024-06-04T11:16:52.899Z warn app/vmauth/auth_config.go:353 cannot discover backend SRV records for http://srv+localhost:8080: lookup localhost on 10.100.10.4:53: server misbehaving; use it literally
panic: runtime error: integer divide by zero
goroutine 9 [running]:
github.com/VictoriaMetrics/VictoriaMetrics/lib/httpserver.handlerWrapper.func1()
/Users/lhhdz/wd/projects/go/VictoriaMetrics/lib/httpserver/httpserver.go:291 +0x58
panic({0x103115100?, 0x10338d700?})
/Users/lhhdz/go/pkg/mod/golang.org/toolchain@v0.0.1-go1.22.3.darwin-arm64/src/runtime/panic.go:770 +0x124
main.getLeastLoadedBackendURL({0x0?, 0x22?, 0x1400014757b?}, 0x1400013c120?)
/Users/lhhdz/wd/projects/go/VictoriaMetrics/app/vmauth/auth_config.go:473 +0x210
main.(*URLPrefix).getBackendURL(0x140000aa080)
/Users/lhhdz/wd/projects/go/VictoriaMetrics/app/vmauth/auth_config.go:312 +0xb8
```
---------
Co-authored-by: Haley Wang <haley@victoriametrics.com>
This should reduce GC overhead when tens of millions of strings are interned (for example, during stream deduplication
of millions of active time series).
These functions are called every time `/metrics` page is scraped, so it would be great
if they could be sped up for the cases when dedupAggr tracks tens of millions of active time series.
- Use bytesutil.InternString() instead of strings.Clone() for inputKey and outputKey in aggregatorpushSamples().
This should reduce string allocation rate, since strings can be re-used between aggrState flushes.
- Reduce memory allocations at dedupAggrShard by storing dedupAggrSample by value in the active series map.
- Remove duplicate call to bytesutil.InternBytes() at Deduplicator, since it is already called inside dedupAggr.pushSamples().
- Add missing string interning at rateAggrState.pushSamples().
Updates https://github.com/VictoriaMetrics/VictoriaMetrics/pull/6402
The main change is getting rid of interning of sample key. It was
discovered that for cases with many unique time series aggregated by
vmagent interned keys could grow up to hundreds of millions of objects.
This has negative impact on the following aspects:
1. It slows down garbage collection cycles, as GC has to scan all inuse
objects periodically. The higher is the number of inuse objects, the
longer it takes/the more CPU it takes.
2. It slows down the hot path of samples aggregation where each key
needs to be looked up in the map first.
The change makes code more fragile, but suppose to provide performance
optimization for heavy-loaded vmagents with stream aggregation enabled.
---------
Signed-off-by: hagen1778 <roman@victoriametrics.com>
Co-authored-by: Aliaksandr Valialkin <valyala@victoriametrics.com>
### Describe Your Changes
Added streamaggr metrics to:
- `vm_streamaggr_samples_lag_seconds` - samples lag
- `vm_streamaggr_ignored_samples_total{reason="nan"}` - ignored NaN
samples
- `vm_streamaggr_ignored_samples_total{reason="too_old"}` - ignored old
samples
### Describe Your Changes
Fix for issue #6396: according to rmdir manpage, ENOTEMPTY and EEXIST
should be treated equally
https://github.com/VictoriaMetrics/VictoriaMetrics/issues/6396
### Checklist
The following checks are **mandatory**:
- [x ] My change adheres [VictoriaMetrics contributing
guidelines](https://docs.victoriametrics.com/contributing/).
---------
Co-authored-by: Ludovic Pollet <ludovic.pollet@exfo.com>
Co-authored-by: hagen1778 <roman@victoriametrics.com>
It allows to create alert for possible item drops at indexdb. It may
happen, if ingested metric size exceeds max indexdb item size.
---------
Signed-off-by: hagen1778 <roman@victoriametrics.com>
Co-authored-by: Zakhar Bessarab <z.bessarab@victoriametrics.com>
Co-authored-by: hagen1778 <roman@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>
