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).
When converting `AlertStmt` to a string, the alert rule labels were
printed as `ANNOTATIONS` instead of the annotations themselves.
Fix and add a test to catch future regressions.
This offers new semantics in allowing on() for matching
two single-element vectors with no known common labels.
Previosuly this was often done using on(dummy).
This also allows making it explict that you meant
to do an aggregation without labels via by().
Fixes#1597.
PromQL only requires a much narrower interface than local.Storage in
order to run queries. Narrower interfaces are easier to replace and
test, too.
We could also change the web interface to use local.Querier, except that
we'll probably use appending functions from there in the future.
Currently the printer doesn't print the annotations of an `*AlertStmt`
declaration. I've added a test case as well, which fails for the current
master.
Since rule evaluations work via String(), this fixes evaluation of
rules containing GROUP_x modifiers without labels. This change is the
minimal bugfix (so that we can release a fixed version without
risk). It does not intend to implement any additional features (like
allowing `GROUP_LEFT()` or `ON()` or even `ON` - see discussion in
https://github.com/prometheus/prometheus/issues/1597 ).
If the label doesn't exist on the one side, it's not copied.
All labels on the many inside are included, this is a breaking change
but likely low impact.
The labels listed in the group_ modifier will be copied from the one
side to the many side. It will be valid to specify no labels.
This is intended to replace the existing ON/GROUP_* support.,
Brian Brazil