The one central sample ingestion channel has caused a variety of
trouble. This commit removes it. Targets and rule evaluation call an
Append method directly now. To incorporate multiple storage backends
(like OpenTSDB), storage.Tee forks the Append into two different
appenders.
Note that the tsdb queue manager had its own queue anyway. It was a
queue after a queue... Much queue, so overhead...
Targets have their own little buffer (implemented as a channel) to
avoid stalling during an http scrape. But a new scrape will only be
started once the old one is fully ingested.
The contraption of three pipelined ingesters was removed. A Target is
an ingester itself now. Despite more logic in Target, things should be
less confusing now.
Also, remove lint and vet warnings in ast.go.
A number of mostly minor things:
- Rename chunk type -> chunk encoding.
- After all, do not carry around the chunk encoding to all parts of
the system, but just have one place where the encoding for new
chunks is set based on the flag. The new approach has caveats as
well, but the polution of so many method signatures is worse.
- Use the default chunk encoding for new chunks of existing
series. (Previously, only new _series_ would get chunks with the
default encoding.)
- Use an enum for chunk encoding. (But keep the version number for the
flag, for reasons discussed previously.)
- Add encoding() to the chunk interface (so that a chunk knows its own
encoding - no need to have that in a different top-level function).
- Got rid of newFollowUpChunk (which would keep the existing encoding
for all chunks of a time series). Now only use newChunk(), which
will create a chunk encoding according to the flag.
- Simplified transcodeAndAdd.
- Reordered methods of deltaEncodedChunk and doubleDeltaEncoded chunk
to match the order in the chunk interface.
- Only transcode if the chunk is not yet half full. If more than half
full, add a new chunk instead.
This is done by bucketing chunks by fingerprint. If the persisting to
disk falls behind, more and more chunks are in the queue. As soon as
there are "double hits", we will now persist both chunks in one go,
doubling the disk throughput (assuming it is limited by disk
seeks). Should even more pile up so that we end wit "triple hits", we
will persist those first, and so on.
Even if we have millions of time series, this will still help,
assuming not all of them are growing with the same speed. Series that
get many samples and/or are not very compressable will accumulate
chunks faster, and they will soon get double- or triple-writes.
To improve the chance of double writes,
-storage.local.persistence-queue-capacity could be set to a higher
value. However, that will slow down shutdown a lot (as the queue has
to be worked through). So we leave it to the user to set it to a
really high value. A more fundamental solution would be to checkpoint
not only head chunks, but also chunks still in the persist queue. That
would be quite complicated for a rather limited use-case (running many
time series with high ingestion rate on slow spinning disks).
- Increase samplesQueueCapacity.
- Improve docstring for the above.
- Accept a short waiting period for the ingest channel to become
ready. This should depend on the http timeout, but 100ms is probably
good enough to cushion bursts bigger than samplesQueueCapacity,
while it is unlikely that anybody ever will set an HTTP timeout
similarly short.
Also, set a much higher default value.
Chunk persist requests can be quite spiky. If you collect a large
number of time series that are very similar, they will tend to finish
up a chunk at about the same time. There is no reason we need to back
up scraping just because of that. The rationale of the new default
value is "1/8 of the chunks in memory".
- Move CONTRIBUTORS.md to the more common AUTHORS.
- Added the required NOTICE file.
- Changed "Prometheus Team" to "The Prometheus Authors".
- Reverted the erroneous changes to the Apache License.
Essentially:
- Remove unused code.
- Make it 'go vet' clean. The only remaining warnings are in generated code.
- Make it 'golint' clean. The only remaining warnings are in gerenated code.
- Smoothed out same minor things.
Change-Id: I3fe5c1fbead27b0e7a9c247fee2f5a45bc2d42c6
And I swear I'll never use 'rebase' to 'clean something up' ever agin,
even if Julius tells me to do so...
Change-Id: Ifeabab20445279bf693c95f062da769b60fe195f
Fix the behavior if preload for non-existent series is requested.
Instead of returning an error (which triggers a panic further up),
simply count those incidents. They can happen regularly, we just want
to know if they happen too frequently because that would mean the
indexing is behind or broken.
Change-Id: I4b2d1b93c4146eeea897d188063cb9574a270f8b
Checkpointing interval is now a command line flag.
Along the way, several things were refactored.
- Restructure the way the storage is started and stopped..
- Number of series in checkpoint is now a uint64, not a varint.
(Breaks old checkpoints, needs wipe!)
- More consistent naming and order of methods.
Change-Id: I883d9170c9a608ee716bb0ab3d0ded8ca03760d9
Also, fix problems in shutdown.
Starting serving and shutdown still has to be cleaned up properly.
It's a mess.
Change-Id: I51061db12064e434066446e6fceac32741c4f84c
Move rulemanager to it's own package to break cicrular dependency.
Make NewTestTieredStorage available to tests, remove duplication.
Change-Id: I33b321245a44aa727bfc3614a7c9ae5005b34e03
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
The closing of Prometheus now using a sync.Once wrapper to prevent
any accidental multiple invocations of it, which could trigger
corruption or a race condition. The shutdown process is made more
verbose through logging.
A not-enabled by default web handler has been provided to trigger a
remote shutdown if requested for debugging purposes.
Change-Id: If4fee75196bbff1fb1e4a4ef7e1cfa53fef88f2e
The idiomatic pattern for signalling a one-time message to multiple
consumers from a single producer is as follows:
```
c := make(chan struct{})
w := new(sync.WaitGroup) // Boilerplate to ensure synchronization.
for i := 0; i < 1000; i++ {
w.Add(1)
go func() {
defer w.Done()
for {
select {
case _, ok := <- c:
if !ok {
return
}
default:
// Do something here.
}
}
}()
}
close(c) // Signal the one-to-many single-use message.
w.Wait()
```
Change-Id: I755f73ba4c70a923afd342a4dea63365bdf2144b
Idiomatic semaphore usage in Go, unless it is wrapping a concrete type,
should use anonymous empty structs (``struct{}``). This has several
features that are worthwhile:
1. It conveys that the object in the channel is likely used for
resource limiting / semaphore use. This is by idiom.
2. Due to magic under the hood, empty structs have a width of zero,
meaning they consume little space. It is presumed that slices,
channels, and other values of them can be represented specially
with alternative optimizations. Dmitry Vyukov has done
investigations into improvements that can be made to the channel
design and Go and concludes that there are already nice short
circuiting behaviors at work with this type.
This is the first change of several that apply this type of change to
suitable places.
In this one change, we fix a bug in the previous revision, whereby a
semaphore can be acquired for curation and never released back for
subsequent work: http://goo.gl/70Y2qK. Compare that versus the
compaction definition above.
On top of that, the use of the semaphore in the mode better supports
system shutdown idioms through the closing of channels.
Change-Id: Idb4fca310f26b73c9ec690bbdd4136180d14c32d
Prometheus needs long-term storage. Since we don't have enough resources
to build our own timeseries storage from scratch ontop of Riak,
Cassandra or a similar distributed datastore at the moment, we're
planning on using OpenTSDB as long-term storage for Prometheus. It's
data model is roughly compatible with that of Prometheus, with some
caveats.
As a first step, this adds write-only replication from Prometheus to
OpenTSDB, with the following things worth noting:
1)
I tried to keep the integration lightweight, meaning that anything
related to OpenTSDB is isolated to its own package and only main knows
about it (essentially it tees all samples to both the existing storage
and TSDB). It's not touching the existing TieredStorage at all to avoid
more complexity in that area. This might change in the future,
especially if we decide to implement a read path for OpenTSDB through
Prometheus as well.
2)
Backpressure while sending to OpenTSDB is handled by simply dropping
samples on the floor when the in-memory queue of samples destined for
OpenTSDB runs full. Prometheus also only attempts to send samples once,
rather than implementing a complex retry algorithm. Thus, replication to
OpenTSDB is best-effort for now. If needed, this may be extended in the
future.
3)
Samples are sent in batches of limited size to OpenTSDB. The optimal
batch size, timeout parameters, etc. may need to be adjusted in the
future.
4)
OpenTSDB has different rules for legal characters in tag (label) values.
While Prometheus allows any characters in label values, OpenTSDB limits
them to a to z, A to Z, 0 to 9, -, _, . and /. Currently any illegal
characters in Prometheus label values are simply replaced by an
underscore. Especially when integrating OpenTSDB with the read path in
Prometheus, we'll need to reconsider this: either we'll need to
introduce the same limitations for Prometheus labels or escape/encode
illegal characters in OpenTSDB in such a way that they are fully
decodable again when reading through Prometheus, so that corresponding
timeseries in both systems match in their labelsets.
Change-Id: I8394c9c55dbac3946a0fa497f566d5e6e2d600b5
