This is part of https://github.com/prometheus/prometheus/pull/5882 that can be done to simplify things.
All todos I added will be fixed in follow up PRs.
* querier.Querier, querier.Appender, querier.SeriesSet, and querier.Series interfaces merged
with storage interface.go. All imports that.
* querier.SeriesIterator replaced by chunkenc.Iterator
* Added chunkenc.Iterator.Seek method and tests for xor implementation (?)
* Since we properly handle SelectParams for Select methods I adjusted min max
based on that. This should help in terms of performance for queries with functions like offset.
* added Seek to deletedIterator and test.
* storage/tsdb was removed as it was only a unnecessary glue with incompatible structs.
No logic was changed, only different source of abstractions, so no need for benchmarks.
Signed-off-by: Bartlomiej Plotka <bwplotka@gmail.com>
* Make lookbackDelta a option of QueryEngine
Signed-off-by: Julien Pivotto <roidelapluie@inuits.eu>
* julius' suggestion
Signed-off-by: Julien Pivotto <roidelapluie@inuits.eu>
* remove trivial getter
Signed-off-by: Julien Pivotto <roidelapluie@inuits.eu>
* Assume lookback delta is always > 0
Signed-off-by: Julien Pivotto <roidelapluie@inuits.eu>
* add debug log
Signed-off-by: Julien Pivotto <roidelapluie@inuits.eu>
* don't expose loopback delta
Signed-off-by: Julien Pivotto <roidelapluie@inuits.eu>
* Specify that lookack delta is also used in federation
Signed-off-by: Julien Pivotto <roidelapluie@inuits.eu>
* Fix federation test
While we have added some logic to the promql engine to keep it backwards
compatible and have a 5 minute loopback by default, the web/ package is
likely to really be internal to Prometheus and we should not add the
same kind of heuritstics here.
Signed-off-by: Julien Pivotto <roidelapluie@inuits.eu>
* loopback delta: Fix debug log
Signed-off-by: Julien Pivotto <roidelapluie@inuits.eu>
Since we use ActiveQueryTracker to check for concurrency in
d992c36b3a it does not make sense to keep
the MaxConcurrent value as an option of the PromQL engine.
This pull request removes it from the PromQL engine options, sets the
max concurrent metric to -1 if there is no active query tracker, and use
the value of the active query tracker otherwise.
It removes dead code and also will inform people who import the promql
package that we made that change, as it breaks the EngineOpts struct.
Signed-off-by: Julien Pivotto <roidelapluie@inuits.eu>
The windows clock is sometime off by 25ms, and as precise as 15ms.
Let's give it more time to avoid flaky tests.
Fix#6672
Signed-off-by: Julien Pivotto <roidelapluie@inuits.eu>
* Move check for empty VectorSelector to typeChecking
* Move check for twice set metric name to typeChecking
* Make child of MatrixSelector a general Node
* rename checkType to checkAST
* Rename fail to addParseErr
* Remove trailing whitespace
Signed-off-by: Tobias Guggenmos <tguggenm@redhat.com>
Fixes#6649.
The crash is fixed here, was caused because some AST sanity checks were performed on the syntax tree while assembling it. In case of previous parsing errors this could lead to undefined behaviour.
The fix is to move the checks to the typechecking phase, which runs only when a syntax tree was assembled without there being parsing errors.
There are other places, where similiar checks are performed while assembling the syntax tree. It might be a good idea to move those to the typechecking phase, too. Should I do this in the same or a separate PR?
Signed-off-by: Tobias Guggenmos <tguggenm@redhat.com>
* PromQL: Use a sync.Pool for the generated parser structure
The generated PromQL parser allocates a struct about 4kb in size on every run.
This puts a high load on the garbage collector.
To reduce that load, a sync.Pool is used to recycle these structures.
On small queries this makes parsing 2-3 times faster.
Signed-off-by: Tobias Guggenmos <tguggenm@redhat.com>
During the PromQL parser rewrite there was some logic put in place that allowed switching between the non generated and the generated parser. Since the parser is now fully generated this is not needed anymore.
Signed-off-by: Tobias Guggenmos <tguggenm@redhat.com>
* Cleanup PromQL functions
The engine ensures, for Matrix functions, that functions are called with exactly one series at the time.
Therefore a lot of code can be inlined and we can directly assume the first element of the arguments exists and contains all the samples needed.
Signed-off-by: Julien Pivotto <roidelapluie@inuits.eu>
The parser benchmarks called the `ParseMetric` function instead of the `ParseExpr` function, which resulted in parsing failing every time.
This means only the case of PromQL parser failure was benchmarked.
Signed-off-by: Tobias Guggenmos <tguggenm@redhat.com>
* Add parser method to produce errors messages about unexpected items
* PromQL: use parser.unexpected in generated parser
Signed-off-by: Tobias Guggenmos <tguggenm@redhat.com>
* Add grammar for label_sets
* Parse label Sets using the generated parser
* Allow trailing commas for label sets and selectors
* Add test to trigger all possible error messages for label matchers
Signed-off-by: Tobias Guggenmos <tguggenm@redhat.com>
The most common format (used by go, gcc and clang) for compiler error positions seems to be
`filename:line:char:` or `line:char:` if the filename is unknown.
This PR adapts the PromQL parser to use this convention.
Signed-off-by: Tobias Guggenmos <tguggenm@redhat.com>
This PR exports the list of supported PromQL functions and their signatures.
The reason for that is that the PromQL language server likes to use that list.
Signed-off-by: Tobias Guggenmos <tguggenm@redhat.com>
* promql: Allow injecting fake tokens into the generated parser
Yacc grammars do not support having multiple start symbols.
To work around that restriction, it is possible to inject fake tokens into the lexer stream,
as described here https://www.gnu.org/software/bison/manual/html_node/Multiple-start_002dsymbols.html .
This is part of the parser rewrite effort described in #6256.
Signed-off-by: Tobias Guggenmos <tguggenm@redhat.com>
For yacc generated parsers there is the convention to capitalize the names of item types provided by the lexer, which makes it easy to distinct lexer tokens (capitalized) from nonterminal symbols (not capitalized) in language grammars.
This convention is also followed by the (non generated) go compiler (see https://golang.org/pkg/go/token/#Token).
Part of the parser rewrite described in #6256.
Signed-off-by: Tobias Guggenmos <tguggenm@redhat.com>
This is the first step towards a generated lexer as described in #6256.
It adds methods to the parser struct, that make it implement the yyLexer interface required by a yacc generated parser, as described here: https://godoc.org/golang.org/x/tools/cmd/goyacc .
The yyLexer interface is implemented by the parser struct instead of the lexer struct for the following reasons:
* Both parsers have a lookahead that the lexer does not know about. This solution makes it possible to synchronize these lookaheads when switching parsers.
* The routines to handle parser errors are not accessible to the lexer.
Signed-off-by: Tobias Guggenmos <tguggenm@redhat.com>
* promql: Clean up parser struct
The parser struct used two have two somewhat misused fields:
peekCount int
token [3]item
By reading the code carefully one notices, that peekCount always has the value 0 or 1 and that only the first element of token is ever accessed.
To make this clearer, this commit replaces the token array with a single variable and the peekCount int with a boolean.
Signed-off-by: Tobias Guggenmos <tguggenm@redhat.com>
Before this commit, the PromQL parser ran in two goroutines:
* The lexer goroutine that splits the input into tokens and sent them over a channel to
* the parser goroutine which produces the abstract syntax tree
The Problem with this approach is that the parser spends more time on goroutine creation
and syncronisation than on actual parsing.
This commit removes that concurrency and replaces the channel by a slice based buffer.
Benchmarks show that this makes the up to 7 times faster than before.
Signed-off-by: Tobias Guggenmos <tguggenm@redhat.com>
* Include tsdb tool in builds (#6085) (#6089)
Add the tsdb tool to promu so that it's included in the release
tarballs.
Signed-off-by: Ben Kochie <superq@gmail.com>
* web/ui: fix for CVE-2019-10215 (#6098)
Signed-off-by: Simon Pasquier <spasquie@redhat.com>
* cut 2.13 release (#6099)
Signed-off-by: Krasi Georgiev <8903888+krasi-georgiev@users.noreply.github.com>
* Fix panic in ARM builds of Prometheus (#6110)
An extra sync.Pool was added during a refactor which caused some 64 bit,
atomically accessed variables to no longer be 64 bit aligned. By moving
all atomically accessed variables to the beginning of the struct they
are guaranteed to be 64 bit aligned.
Signed-off-by: Chris Marchbanks <csmarchbanks@gmail.com>
* promql: fix potential panic in the query logger (#6094)
Signed-off-by: Simon Pasquier <spasquie@redhat.com>
* Cut release 2.13.1 (#6145)
Signed-off-by: Krasi Georgiev <8903888+krasi-georgiev@users.noreply.github.com>
* promql: Move tests to testutil
Signed-off-by: Alex Dzyoba <alex@dzyoba.com>
* promql: Match error type via errors.As in tests
Signed-off-by: Alex Dzyoba <alex@dzyoba.com>
* promql: Remove unused `expectedList` func from lex_test.go
Signed-off-by: Alex Dzyoba <alex@dzyoba.com>
* Added query logging for prometheus.
Options added:
1) active.queries.filepath: Filename where queries will be recorded
2) active.queries.filesize: Size of the file where queries will be recorded.
Functionality added:
All active queries are now logged in a file. If prometheus crashes unexpectedly, these queries are also printed out on stdout in the rerun.
Queries are written concurrently to an mmaped file, and removed once they are done. Their positions in the file are reused. They are written in json format. However, due to dynamic nature of application, the json has an extra comma after the last query, and is missing an ending ']'. There may also null bytes in the tail of file.
Signed-off-by: Advait Bhatwadekar <advait123@ymail.com>
With the next release of client_golang, Summaries will not have
objectives by default. To not lose the objectives we have right now,
explicitly state the current default objectives.
Signed-off-by: beorn7 <beorn@grafana.com>
For my benchmarks on aggregation this reduces allocations by ~5% (~10%
time improvement):
```
benchmark old ns/op new ns/op delta
BenchmarkEvaluations/benchdata/aggregators.test/promxy-4 727692 649626 -10.73%
benchmark old allocs new allocs delta
BenchmarkEvaluations/benchdata/aggregators.test/promxy-4 2566 2434 -5.14%
benchmark old bytes new bytes delta
BenchmarkEvaluations/benchdata/aggregators.test/promxy-4 162760 148854 -8.54%
```
Signed-off-by: Thomas Jackson <jacksontj.89@gmail.com>
The documentation for Context states that this is just as good:
// If Done is not yet closed, Err returns nil.
// If Done is closed, Err returns a non-nil error
Signed-off-by: Bryan Boreham <bryan@weave.works>
i) Uses the more idiomatic Wrap and Wrapf methods for creating nested errors.
ii) Fixes some incorrect usages of fmt.Errorf where the error messages don't have any formatting directives.
iii) Does away with the use of fmt package for errors in favour of pkg/errors
Signed-off-by: tariqibrahim <tariq181290@gmail.com>
* Expose lexer item types
We have generally agreed to expose AST types / values that are necessary
to make sense of the AST outside of the promql package. Currently the
`UnaryExpr`, `BinaryExpr`, and `AggregateExpr` AST nodes store the lexer
item type to indicate the operator type, but since the individual item
types aren't exposed, an external user of the package cannot determine
the operator type. So this PR exposes them.
Although not all item types are required to make sense of the AST (some
are really only used in the lexer), I decided to expose them all here to
be somewhat more consistent. Another option would be to not use lexer
item types at all in AST nodes.
The concrete motivation is my work on the PromQL->Flux transpiler, but
this ought to be useful for other cases as well.
Signed-off-by: Julius Volz <julius.volz@gmail.com>
* Fix item type names in tests
Signed-off-by: Julius Volz <julius.volz@gmail.com>
See,
$ codespell -S './vendor/*,./.git*,./web/ui/static/vendor*' --ignore-words-list="uint,dur,ue,iff,te,wan"
Signed-off-by: Mario Trangoni <mjtrangoni@gmail.com>
Although it is spelling mistakes, it might make an affects
while reading.
Co-Authored-By: Kim Bao Long longkb@vn.fujitsu.com
Signed-off-by: Nguyen Hai Truong <truongnh@vn.fujitsu.com>
This makes things generally more resilient, and will
help with OpenMetrics transitions (and inconsistencies).
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* *: use latest release of staticcheck
It also fixes a couple of things in the code flagged by the additional
checks.
Signed-off-by: Simon Pasquier <spasquie@redhat.com>
* Use official release of staticcheck
Also run 'go list' before staticcheck to avoid failures when downloading packages.
Signed-off-by: Simon Pasquier <spasquie@redhat.com>
When there was an error in the parser, the
lexer goroutine was left running.
Also make runtime panic test actually test things.
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
Since it is used in a type assertion, having it as an alias to the
error interface is the same as saying 'error', i.e. it succeeds for
all types of error. Change to a struct which is a concrete type and
the type assertion will only succeed if the type is identical.
Signed-off-by: Bryan Boreham <bjboreham@gmail.com>
* use Welford/Knuth method to compute standard deviation and variance, avoids float precision issues
* use better method for calculating avg and avg_over_time
Signed-off-by: Dan Cech <dcech@grafana.com>
There are many more (mostly finalizers like Close/Stop/etc.), but most of
the others seemed like one couldn't do much about them anyway.
Signed-off-by: Julius Volz <julius.volz@gmail.com>
* Allow for BufferedSeriesIterator instances to be created without an underlying iterator, to simplify their usage.
Signed-off-by: Alin Sinpalean <alin.sinpalean@gmail.com>
* Add Start/End to SelectParams
* Make remote read use the new selectParams for start/end
This commit will continue sending the start/end time of the remote read
query as the overarching promql time and the specific range of data that
the query is intersted in receiving a response to is now part of the
ReadHints (upstream discussion in #4226).
* Remove unused vendored code
The genproto.sh script was updated, but the code wasn't regenerated.
This simply removes the vendored deps that are no longer part of the
codegen output.
Signed-off-by: Thomas Jackson <jacksontj.89@gmail.com>
Right now promql won't time out a request if populating the iterators
takes a long time.
Signed-off-by: Thomas Jackson <jacksontj.89@gmail.com>
Fixes#4289
This changes the Walk/Inspect API inside the promql package to bubble
up errors. This is done by having the inspector return an error (instead
of a bool) and then bubbling that up in the Walk. This way if any error
is encountered in the Walk() the walk will stop and return the error.
This avoids issues where errors from the Querier where being ignored
(causing incorrect promql evaluation).
Signed-off-by: Thomas Jackson <jacksontj.89@gmail.com>
Fixes#4136
* Move range logic to 'eval'
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Make aggregegate range aware
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* PromQL is statically typed, so don't eval to find the type.
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Extend rangewrapper to multiple exprs
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Start making function evaluation ranged
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Make instant queries a special case of range queries
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Eliminate evalString
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Evaluate range vector functions one series at a time
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Make unary operators range aware
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Make binops range aware
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Pass time to range-aware functions.
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Make simple _over_time functions range aware
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Reduce allocs when working with matrix selectors
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Add basic benchmark for range evaluation
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Reuse objects for function arguments
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Do dropmetricname and allocating output vector only once.
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Add range-aware support for range vector functions with params
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Optimise holt_winters, cut cpu and allocs by ~25%
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Make rate&friends range aware
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Make more functions range aware. Document calling convention.
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Make date functions range aware
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Make simple math functions range aware
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Convert more functions to be range aware
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Make more functions range aware
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Specialcase timestamp() with vector selector arg for range awareness
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Remove transition code for functions
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Remove the rest of the engine transition code
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Remove more obselete code
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Remove the last uses of the eval* functions
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Remove engine finalizers to prevent corruption
The finalizers set by matrixSelector were being called
just before the value they were retruning to the pool
was then being provided to the caller. Thus a concurrent query
could corrupt the data that the user has just been returned.
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Add new benchmark suite for range functinos
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Migrate existing benchmarks to new system
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Expand promql benchmarks
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Simply test by removing unused range code
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* When testing instant queries, check range queries too.
To protect against subsequent steps in a range query being
affected by the previous steps, add a test that evaluates
an instant query that we know works again as a range query
with the tiimestamp we care about not being the first step.
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Reuse ring for matrix iters. Put query results back in pool.
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Reuse buffer when iterating over matrix selectors
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Unary minus should remove metric name
Cut down benchmarks for faster runs.
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Reduce repetition in benchmark test cases
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Work series by series when doing normal vectorSelectors
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Optimise benchmark setup, cuts time by 60%
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Have rangeWrapper use an evalNodeHelper to cache across steps
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Use evalNodeHelper with functions
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Cache dropMetricName within a node evaluation.
This saves both the calculations and allocs done by dropMetricName
across steps.
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Reuse input vectors in rangewrapper
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Reuse the point slices in the matrixes input/output by rangeWrapper
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Make benchmark setup faster using AddFast
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Simplify benchmark code.
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Add caching in VectorBinop
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Use xor to have one-level resultMetric hash key
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Add more benchmarks
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Call Query.Close in apiv1
This allows point slices allocated for the response data
to be reused by later queries, saving allocations.
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Optimise histogram_quantile
It's now 5-10% faster with 97% less garbage generated for 1k steps
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Make the input collection in rangeVector linear rather than quadratic
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Optimise label_replace, for 1k steps 15x fewer allocs and 3x faster
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Optimise label_join, 1.8x faster and 11x less memory for 1k steps
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Expand benchmarks, cleanup comments, simplify numSteps logic.
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Address Fabian's comments
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Comments from Alin.
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Address jrv's comments
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Remove dead code
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Address Simon's comments.
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Rename populateIterators, pre-init some sizes
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Handle case where function has non-matrix args first
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Split rangeWrapper out to rangeEval function, improve comments
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Cleanup and make things more consistent
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Make EvalNodeHelper public
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Fabian's comments.
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* promql: Rewrote tests with testutil for functions_test
Signed-off-by: Elif T. Kuş <elifkus@gmail.com>
* pkg/relabel: Rewrote tests with testutil for relabel_test
Signed-off-by: Elif T. Kuş <elifkus@gmail.com>
* discovery/consul: Rewrote tests with testutil for consul_test
Signed-off-by: Elif T. Kuş <elifkus@gmail.com>
* scrape: Rewrote tests with testutil for manager_test
Signed-off-by: Elif T. Kuş <elifkus@gmail.com>
This attempts to close#3973.
Handles cases where the length of the input vector to an aggregate topk
/ bottomk function is less than the K paramater. The change updates
Prometheus to allocate a result vector the same length as the input
vector in these cases.
Previously Prometheus would out-of-memory panic for large K values. This
change makes that unlikely unless the size of the input vector is
equally large.
Signed-off-by: David King <dave@davbo.org>
* parser test cleanup
- Test against the exported package functions instead of the private functions.
* Improves readability of TestParseSeries
- Moves package function closer to parser function
This adds a parameter to the storage selection interface which allows
query engine(s) to pass information about the operations surrounding a
data selection.
This can for example be used by remote storage backends to infer the
correct downsampling aggregates that need to be provided.
* TotalFoo suggested a comprehensive timing, but TotalEvalTime was part
of the Exec timings, together with Queue timings
* The other option was to rename ExecTotalTime to TotalExecTime, but
there was already ExecQueueTime, suggesting Exec to be some sort of
group
API consumers should be able to get insight into the query run times.
The UI currently measures total roundtrip times. This PR allows for more
fine grained metrics to be exposed.
* adds new timer for total execution time (queue + eval)
* expose new timer, queue timer, and eval timer in stats field of the
range query response:
```json
{
"status": "success",
"data": {
"resultType": "matrix",
"result": [],
"stats": {
"execQueueTimeNs": 4683,
"execTotalTimeNs": 2086587,
"totalEvalTimeNs": 2077851
}
}
}
```
* stats field is optional, only set when query parameter `stats` is not
empty
Try it via
```sh
curl 'http://localhost:9090/api/v1/query_range?query=up&start=1486480279&end=1486483879&step=14000&stats=true'
```
Review feedback
* moved query stats json generation to query_stats.go
* use seconds for all query timers
* expose all timers available
* Changed ExecTotalTime string representation from Exec queue total time to Exec total time
This means that if there is no stale marker, only the usual staleness
delta (5m) applies.
It has occured to me that there is an oddity in the heurestic. It works
fine as long as you have 2 points within the last 5m, but breaks down
when the time window advances to the point where you have just 1 point.
Consider you had points at t=0 and t=10. With the heurestic it goes stale
at t=51, up until t=300. However from t=301 until t=310 we only
see the t=10 point and the series comes back to life. That is not
desirable.
I don't see a way to keep this form of heurestic working given this
issue, so thus I'm removing it.
* Re-add contexts to storage.Storage.Querier()
These are needed when replacing the storage by a multi-tenant
implementation where the tenant is stored in the context.
The 1.x query interfaces already had contexts, but they got lost in 2.x.
* Convert promql.Engine to use native contexts
With the squaring of the timestamp, we run into the
limitations of the 53bit mantissa for a 64bit float.
By subtracting away a timestamp of one of the samples (which is how the
intercept is used) we avoid this issue in practice as it's unlikely
that it is used over a very long time range.
Fixes#2674
* Fix error where we look into the future.
So currently we are adding values that are in the future for an older
timestamp. For example, if we have [(1, 1), (150, 2)] we will end up
showing [(1, 1), (2,2)].
Further it is not advisable to call .At() after Next() returns false.
Signed-off-by: Goutham Veeramachaneni <cs14btech11014@iith.ac.in>
* Retuen early if done
Signed-off-by: Goutham Veeramachaneni <cs14btech11014@iith.ac.in>
* Handle Seek() where we reach the end of iterator
Signed-off-by: Goutham Veeramachaneni <cs14btech11014@iith.ac.in>
* Simplify code
Signed-off-by: Goutham Veeramachaneni <cs14btech11014@iith.ac.in>
To cover the cases where stale markers may not be available,
we need to infer the interval and mark series stale based on that.
As we're lacking stale markers this is less accurate, however
it should be good enough for these cases.
We need 4 intervals as if say we had data at t=0 and t=10,
coming via federation. The next data point should be at t=20 however it
could take up to t=30 for it actually to be ingested, t=40 for it to be
scraped via federation and t=50 for it to be ingested.
We then add 10% on to that for slack, as we do elsewhere.
For instant vectors, if "stale" is the newest sample
ignore the timeseries.
For range vectors, filter out "stale" samples.
Make it possible to inject "stale" samples in promql tests.
Query and query_range should return the timestamp
at which an evaluation is performed, not the timestamp
of the data. This is as that's what query range asked
for, and we need to keep query consistent with that.
Query for a matrix remains unchanged, returning the literal
matrix.
Make the timestamp of instant vectors be the timestamp of the sample
rather than the evaluation. We were not using this anywhere, so this is
safe.
Add a function to return the timestamp of samples in an instant vector.
Fixes#1557
* Use request.Context() instead of a global map of contexts.
* Add some basic opentracing instrumentation on the query path.
* Remove tracehandler endpoint.
* Force buckets in a histogram to be monotonic for quantile estimation
The assumption that bucket counts increase monotonically with increasing
upperBound may be violated during:
* Recording rule evaluation of histogram_quantile, especially when rate()
has been applied to the underlying bucket timeseries.
* Evaluation of histogram_quantile computed over federated bucket
timeseries, especially when rate() has been applied
This is because scraped data is not made available to RR evalution or
federation atomically, so some buckets are computed with data from the N
most recent scrapes, but the other buckets are missing the most recent
observations.
Monotonicity is usually guaranteed because if a bucket with upper bound
u1 has count c1, then any bucket with a higher upper bound u > u1 must
have counted all c1 observations and perhaps more, so that c >= c1.
Randomly interspersed partial sampling breaks that guarantee, and rate()
exacerbates it. Specifically, suppose bucket le=1000 has a count of 10 from
4 samples but the bucket with le=2000 has a count of 7, from 3 samples. The
monotonicity is broken. It is exacerbated by rate() because under normal
operation, cumulative counting of buckets will cause the bucket counts to
diverge such that small differences from missing samples are not a problem.
rate() removes this divergence.)
bucketQuantile depends on that monotonicity to do a binary search for the
bucket with the qth percentile count, so breaking the monotonicity
guarantee causes bucketQuantile() to return undefined (nonsense) results.
As a somewhat hacky solution until the Prometheus project is ready to
accept the changes required to make scrapes atomic, we calculate the
"envelope" of the histogram buckets, essentially removing any decreases
in the count between successive buckets.
* Fix up comment docs for ensureMonotonic
* ensureMonotonic: Use switch statement
Use switch statement rather than if/else for better readability.
Process the most frequent cases first.
* Add max concurrent and current queries engine metrics
This commit adds two metrics to the promql/engine: the
number of max concurrent queries, as configured by the flag, and
the number of current queries being served+blocked in the engine.
This extracts Querier as an instantiateable and closeable object
rather than just defining extending methods of the storage interface.
This improves composability and allows abstracting query transactions,
which can be useful for transaction-level caches, consistent data views,
and encapsulating teardown.
This is based on https://github.com/prometheus/prometheus/pull/1997.
This adds contexts to the relevant Storage methods and already passes
PromQL's new per-query context into the storage's query methods.
The immediate motivation supporting multi-tenancy in Frankenstein, but
this could also be used by Prometheus's normal local storage to support
cancellations and timeouts at some point.
For Weaveworks' Frankenstein, we need to support multitenancy. In
Frankenstein, we initially solved this without modifying the promql
package at all: we constructed a new promql.Engine for every
query and injected a storage implementation into that engine which would
be primed to only collect data for a given user.
This is problematic to upstream, however. Prometheus assumes that there
is only one engine: the query concurrency gate is part of the engine,
and the engine contains one central cancellable context to shut down all
queries. Also, creating a new engine for every query seems like overkill.
Thus, we want to be able to pass per-query contexts into a single engine.
This change gets rid of the promql.Engine's built-in base context and
allows passing in a per-query context instead. Central cancellation of
all queries is still possible by deriving all passed-in contexts from
one central one, but this is now the responsibility of the caller. The
central query context is now created in main() and passed into the
relevant components (web handler / API, rule manager).
In a next step, the per-query context would have to be passed to the
storage implementation, so that the storage can implement multi-tenancy
or other features based on the contextual information.
The current separation between lexer and parser is a bit fuzzy when it
comes to operators, aggregators and other keywords. The lexer already
tries to determine the type of a token, even though that type might
change depending on the context.
This led to the problematic behavior that no tokens known to the lexer
could be used as label names, including operators (and, by, ...),
aggregators (count, quantile, ...) or other keywords (for, offset, ...).
This change additionally checks whether an identifier is one of these
types. We might want to check whether the specific item identification
should be moved from the lexer to the parser.
As described in #1898 'go test -race' detects a race in lexer code. This
pacth fixes it and also add '-race' option to test target to prevent
regression.
This was only relevant so far for the benchmark suite as it would
recycle Expr for repetitions. However, the append is unnecessary as
each node is only inspected once when populating iterators, and
population must always start from scratch.
This also introduces error checking during benchmarks and fixes the so
far undetected test errors during benchmarking.
Also, remove a style nit (two golint warnings less…).
See discussion in
https://groups.google.com/forum/#!topic/prometheus-developers/bkuGbVlvQ9g
The main idea is that the user of a storage shouldn't have to deal with
fingerprints anymore, and should not need to do an individual preload
call for each metric. The storage interface needs to be made more
high-level to not expose these details.
This also makes it easier to reuse the same storage interface for remote
storages later, as fewer roundtrips are required and the fingerprint
concept doesn't work well across the network.
NOTE: this deliberately gets rid of a small optimization in the old
query Analyzer, where we dedupe instants and ranges for the same series.
This should have a minor impact, as most queries do not have multiple
selectors loading the same series (and at the same offset).
tl;dr: This is not a fundamental solution to the indexing problem
(like tindex is) but it at least avoids utilizing the intersection
problem to the greatest possible amount.
In more detail:
Imagine the following query:
nicely:aggregating:rule{job="foo",env="prod"}
While it uses a nicely aggregating recording rule (which might have a
very low cardinality), Prometheus still intersects the low number of
fingerprints for `{__name__="nicely:aggregating:rule"}` with the many
thousands of fingerprints matching `{job="foo"}` and with the millions
of fingerprints matching `{env="prod"}`. This totally innocuous query
is dead slow if the Prometheus server has a lot of time series with
the `{env="prod"}` label. Ironically, if you make the query more
complicated, it becomes blazingly fast:
nicely:aggregating:rule{job=~"foo",env=~"prod"}
Why so? Because Prometheus only intersects with non-Equal matchers if
there are no Equal matchers. That's good in this case because it
retrieves the few fingerprints for
`{__name__="nicely:aggregating:rule"}` and then starts right ahead to
retrieve the metric for those FPs and checking individually if they
match the other matchers.
This change is generalizing the idea of when to stop intersecting FPs
and go into "retrieve metrics and check them individually against
remaining matchers" mode:
- First, sort all matchers by "expected cardinality". Matchers
matching the empty string are always worst (and never used for
intersections). Equal matchers are in general consider best, but by
using some crude heuristics, we declare some better than others
(instance labels or anything that looks like a recording rule).
- Then go through the matchers until we hit a threshold of remaining
FPs in the intersection. This threshold is higher if we are already
in the non-Equal matcher area as intersection is even more expensive
here.
- Once the threshold has been reached (or we have run out of matchers
that do not match the empty string), start with "retrieve metrics
and check them individually against remaining matchers".
A beefy server at SoundCloud was spending 67% of its CPU time in index
lookups (fingerprintsForLabelPairs), serving mostly a dashboard that
is exclusively built with recording rules. With this change, it spends
only 35% in fingerprintsForLabelPairs. The CPU usage dropped from 26
cores to 18 cores. The median latency for query_range dropped from 14s
to 50ms(!). As expected, higher percentile latency didn't improve that
much because the new approach is _occasionally_ running into the worst
case while the old one was _systematically_ doing so. The 99th
percentile latency is now about as high as the median before (14s)
while it was almost twice as high before (26s).
