The initial impetus for this was that it made unmarshalling sample
values much faster.
Other relevant benchmark changes in ns/op:
Benchmark old new speedup
==================================================================
BenchmarkMarshal 179170 127996 1.4x
BenchmarkUnmarshal 404984 132186 3.1x
BenchmarkMemoryGetValueAtTime 57801 50050 1.2x
BenchmarkMemoryGetBoundaryValues 64496 53194 1.2x
BenchmarkMemoryGetRangeValues 66585 54065 1.2x
BenchmarkStreamAdd 45.0 75.3 0.6x
BenchmarkAppendSample1 1157 1587 0.7x
BenchmarkAppendSample10 4090 4284 0.95x
BenchmarkAppendSample100 45660 44066 1.0x
BenchmarkAppendSample1000 579084 582380 1.0x
BenchmarkMemoryAppendRepeatingValues 22796594 22005502 1.0x
Overall, this gives us good speedups in the areas where they matter
most: decoding values from disk and accessing the memory storage (which
is also used for views).
Some of the smaller append examples take minimally longer, but the cost
seems to get amortized over larger appends, so I'm not worried about
these. Also, we're currently not bottlenecked on the write path and have
plenty of other optimizations available in that area if it becomes
necessary.
Memory allocations during appends don't change measurably at all.
Change-Id: I7dc7394edea09506976765551f35b138518db9e8
This doesn't add complex discriminator logic yet, but adds a single
version byte to the beginning of each samples chunk. If we ever need to
change the disk format again, this will make it easy to do so without
having to wipe the entire database.
Change-Id: I60c39274256f790bc2da83167a1effaa174588fe
- Mostly docstring fixed/additions.
(Please review these carefully, since most of them were missing, I
had to guess them from an outsider's perspective. (Which on the
other hand proves how desperately required many of these docstrings
are.))
- Removed all uses of new(...) to meet our own style guide (draft).
- Fixed all other 'go vet' and 'golint' issues (except those that are
not fixable (i.e. caused by bugs in or by design of 'go vet' and
'golint')).
- Some trivial refactorings, like reorder functions, minor renames, ...
- Some slightly less trivial refactoring, mostly to reduce code
duplication by embedding types instead of writing many explicit
forwarders.
- Cleaned up the interface structure a bit. (Most significant probably
the removal of the View-like methods from MetricPersistenc. Now they
are only in View and not duplicated anymore.)
- Removed dead code. (Probably not all of it, but it's a first
step...)
- Fixed a leftover in storage/metric/end_to_end_test.go (that made
some parts of the code never execute (incidentally, those parts
were broken (and I fixed them, too))).
Change-Id: Ibcac069940d118a88f783314f5b4595dce6641d5
So far we've been using Go's native time.Time for anything related to sample
timestamps. Since the range of time.Time is much bigger than what we need, this
has created two problems:
- there could be time.Time values which were out of the range/precision of the
time type that we persist to disk, therefore causing incorrectly ordered keys.
One bug caused by this was:
https://github.com/prometheus/prometheus/issues/367
It would be good to use a timestamp type that's more closely aligned with
what the underlying storage supports.
- sizeof(time.Time) is 192, while Prometheus should be ok with a single 64-bit
Unix timestamp (possibly even a 32-bit one). Since we store samples in large
numbers, this seriously affects memory usage. Furthermore, copying/working
with the data will be faster if it's smaller.
*MEMORY USAGE RESULTS*
Initial memory usage comparisons for a running Prometheus with 1 timeseries and
100,000 samples show roughly a 13% decrease in total (VIRT) memory usage. In my
tests, this advantage for some reason decreased a bit the more samples the
timeseries had (to 5-7% for millions of samples). This I can't fully explain,
but perhaps garbage collection issues were involved.
*WHEN TO USE THE NEW TIMESTAMP TYPE*
The new clientmodel.Timestamp type should be used whenever time
calculations are either directly or indirectly related to sample
timestamps.
For example:
- the timestamp of a sample itself
- all kinds of watermarks
- anything that may become or is compared to a sample timestamp (like the timestamp
passed into Target.Scrape()).
When to still use time.Time:
- for measuring durations/times not related to sample timestamps, like duration
telemetry exporting, timers that indicate how frequently to execute some
action, etc.
*NOTE ON OPERATOR OPTIMIZATION TESTS*
We don't use operator optimization code anymore, but it still lives in
the code as dead code. It still has tests, but I couldn't get all of them to
pass with the new timestamp format. I commented out the failing cases for now,
but we should probably remove the dead code soon. I just didn't want to do that
in the same change as this.
Change-Id: I821787414b0debe85c9fffaeb57abd453727af0f
