This fixes the problem where samples become temporarily unavailable for
queries while they are being flushed to disk. Although the entire
flushing code could use some major refactoring, I'm explicitly trying to
do the minimal change to fix the problem since there's a whole new
storage implementation in the pipeline.
Change-Id: I0f5393a30b88654c73567456aeaea62f8b3756d9
This optimizes the runtime and memory allocation behavior for label matchers
other than type "Equal". Instead of creating a new set for every union of
fingerprints, this simply adds new fingerprints to the existing set to achieve
the same effect.
The current behavior made a production Prometheus unresponsive when running a
NotEqual match against the "instance" label (a label with high value
cardinality).
BEFORE:
BenchmarkGetFingerprintsForNotEqualMatcher 10 170430297 ns/op 39229944 B/op 40709 allocs/op
AFTER:
BenchmarkGetFingerprintsForNotEqualMatcher 5000 706260 ns/op 217717 B/op 1116 allocs/op
Change-Id: Ifd78e81e7dfbf5d7249e50ad1903a5d9c42c347a
This fixes https://github.com/prometheus/prometheus/issues/390
The cause for the deadlock was a lock semantic in Go that wasn't
obvious to me when introducing this bug:
http://golang.org/pkg/sync/#RWMutex.Lock
Key phrase: "To ensure that the lock eventually becomes available, a
blocked Lock call excludes new readers from acquiring the lock."
In the memory series storage, we have one function
(GetFingerprintsForLabelMatchers) acquiring an RLock(), which calls
another function also acquiring the same RLock()
(GetLabelValuesForLabelName). That normally doesn't deadlock, unless a
Lock() call from another goroutine happens right in between the two
RLock() calls, blocking both the Lock() and the second RLock() call from
ever completing.
GoRoutine 1 GoRoutine 2
======================================
RLock()
... Lock() [DEADLOCK]
RLock() [DEADLOCK] Unlock()
RUnlock()
RUnlock()
Testing deadlocks is tricky, but the regression test I added does
reliably detect the deadlock in the original code on my machine within a
normal concurrent reader/writer run duration of 250ms.
Change-Id: Ib34c2bb8df1a80af44550cc2bf5007055cdef413
This was initially motivated by wanting to distribute the rule checker
tool under `tools/rule_checker`. However, this was not possible without
also distributing the LevelDB dynamic libraries because the tool
transitively depended on Levigo:
rule checker -> query layer -> tiered storage layer -> leveldb
This change separates external storage interfaces from the
implementation (tiered storage, leveldb storage, memory storage) by
putting them into separate packages:
- storage/metric: public, implementation-agnostic interfaces
- storage/metric/tiered: tiered storage implementation, including memory
and LevelDB storage.
I initially also considered splitting up the implementation into
separate packages for tiered storage, memory storage, and LevelDB
storage, but these are currently so intertwined that it would be another
major project in itself.
The query layers and most other parts of Prometheus now have notion of
the storage implementation anymore and just use whatever implementation
they get passed in via interfaces.
The rule_checker is now a static binary :)
Change-Id: I793bbf631a8648ca31790e7e772ecf9c2b92f7a0
2014-04-16 13:30:19 +02:00
Renamed from storage/metric/memory_test.go (Browse further)
