Formalize ZeroSamplePair as return value for non-existing samples.
Change LastSamplePairForFingerprint to return a SamplePair (and not a
pointer to it), which saves allocations in a potentially extremely
frequent call.
This will fix issue #1035 and will also help to make issue #1264 less
bad.
The fundamental problem in the current code:
In the preload phase, we quite accurately determine which chunks will
be used for the query being executed. However, in the subsequent step
of creating series iterators, the created iterators are referencing
_all_ in-memory chunks in their series, even the un-pinned ones. In
iterator creation, we copy a pointer to each in-memory chunk of a
series into the iterator. While this creates a certain amount of
allocation churn, the worst thing about it is that copying the chunk
pointer out of the chunkDesc requires a mutex acquisition. (Remember
that the iterator will also reference un-pinned chunks, so we need to
acquire the mutex to protect against concurrent eviction.) The worst
case happens if a series doesn't even contain any relevant samples for
the query time range. We notice that during preloading but then we
will still create a series iterator for it. But even for series that
do contain relevant samples, the overhead is quite bad for instant
queries that retrieve a single sample from each series, but still go
through all the effort of series iterator creation. All of that is
particularly bad if a series has many in-memory chunks.
This commit addresses the problem from two sides:
First, it merges preloading and iterator creation into one step,
i.e. the preload call returns an iterator for exactly the preloaded
chunks.
Second, the required mutex acquisition in chunkDesc has been greatly
reduced. That was enabled by a side effect of the first step, which is
that the iterator is only referencing pinned chunks, so there is no
risk of concurrent eviction anymore, and chunks can be accessed
without mutex acquisition.
To simplify the code changes for the above, the long-planned change of
ValueAtTime to ValueAtOrBefore time was performed at the same
time. (It should have been done first, but it kind of accidentally
happened while I was in the middle of writing the series iterator
changes. Sorry for that.) So far, we actively filtered the up to two
values that were returned by ValueAtTime, i.e. we invested work to
retrieve up to two values, and then we invested more work to throw one
of them away.
The SeriesIterator.BoundaryValues method can be removed once #1401 is
fixed. But I really didn't want to load even more changes into this
PR.
Benchmarks:
The BenchmarkFuzz.* benchmarks run 83% faster (i.e. about six times
faster) and allocate 95% fewer bytes. The reason for that is that the
benchmark reads one sample after another from the time series and
creates a new series iterator for each sample read.
To find out how much these improvements matter in practice, I have
mirrored a beefy Prometheus server at SoundCloud that suffers from
both issues #1035 and #1264. To reach steady state that would be
comparable, the server needs to run for 15d. So far, it has run for
1d. The test server currently has only half as many memory time series
and 60% of the memory chunks the main server has. The 90th percentile
rule evaluation cycle time is ~11s on the main server and only ~3s on
the test server. However, these numbers might get much closer over
time.
In addition to performance improvements, this commit removes about 150
LOC.
Fixes https://github.com/prometheus/prometheus/issues/481
While doing so, clean up and fix a few other things:
- Fix `go vet` warnings (@fabxc to blame ;).
- Fix a racey problem with unarchiving: Whenever we unarchive a
series, we essentially want to do something with it. However, until
we have done something with it, it appears like a series that is
ready to be archived or even purged. So e.g. it would be ignored
during checkpointing. With this fix, we always load the chunkDescs
upon unarchiving. This is wasteful if we only want to add a new
sample to an archived time series, but the (presumably more common)
case where we access an archived time series in a query doesn't
become more expensive.
- The change above streamlined the getOrCreateSeries ond
newMemorySeries flow. Also, the modTime is now always set correctly.
- Fix the leveldb-backed implementation of KeyValueStore.Delete. It
had the wrong behavior of still returning true, nil if a
non-existing key has been passed in.
See https://github.com/prometheus/prometheus/issues/887, which will at
least be partially fixed by this.
From the spec https://golang.org/ref/spec#Conversions:
"In all non-constant conversions involving floating-point or complex
values, if the result type cannot represent the value the conversion
succeeds but the result value is implementation-dependent."
This ended up setting the converted values to 0 on Debian's Go 1.4.2
compiler, at least on 32-bit Debians.
Also, clean up some things in the code (especially introduction of the
chunkLenWithHeader constant to avoid the same expression all over the place).
Benchmark results:
BEFORE
BenchmarkLoadChunksSequentially 5000 283580 ns/op 152143 B/op 312 allocs/op
BenchmarkLoadChunksRandomly 20000 82936 ns/op 39310 B/op 99 allocs/op
BenchmarkLoadChunkDescs 10000 110833 ns/op 15092 B/op 345 allocs/op
AFTER
BenchmarkLoadChunksSequentially 10000 146785 ns/op 152285 B/op 315 allocs/op
BenchmarkLoadChunksRandomly 20000 67598 ns/op 39438 B/op 103 allocs/op
BenchmarkLoadChunkDescs 20000 99631 ns/op 12636 B/op 192 allocs/op
Note that everything is obviously loaded from the page cache (as the
benchmark runs thousands of times with very small series files). In a
real-world scenario, I expect a larger impact, as the disk operations
will more often actually hit the disk. To load ~50 sequential chunks,
this reduces the iops from 100 seeks and 100 reads to 1 seek and 1
read.
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.
