This rewrite had may backs and forths. In my git repository, it
consists of 35 commits which I cannot group or merge into reasonable
review buckets. Gerrit breaks fundamental git semantics, so I have to
squash the 35 commits into one for the review.
I'll push this not with refs/for/master, but with refs/for/next so
that we can transition after submission in a controlled fashion.
For the review, I recommend to start with looking at godoc and in
particular the many examples. After that, continue with a line-by-line
detailed review. (The big picture is hopefully as expected after
wrapping up the discussion earlier.)
Change-Id: Ib38cc46493a5139ca29d84020650929d94cac850
- Full support for UNTYPED type.
- Receptive support for timestamp_ms (i.e. the processor can process
it, but the client library cannot yet create it - which is kind of
intended as timestamps are meant for other things like federation,
which will need separate support anyway).
Change-Id: I5913164a80089943d49ad58bf86e465a843ab82b
This also adds a check that forbids any user-supplied metrics to start
with the reserved label name prefix "__".
Change-Id: I2fe94c740b685ad05c4c670613cf2af7b9e1c1c0
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.
Change-Id: I253a467388774280c10400fda122369ff77c1730
This commit finally unlocks the ability for the Prometheus client
users of the Summary metric type to automatically get total counts
and sums partitioned by labels. It exposes them through two
synthetic variables, if the underlying data is present.
The following is the base case:
foo_samples{quantile=0.5} = <?>
foo_samples{quantile=0.99} = <?>
The following results with this change:
foo_samples{quantile=0.5} = <?>
foo_samples{quantile=0.99} = <?>
foo_samples_sum = <?>
foo_samples_count = <?>
Change-Id: I75b5ea0d8c851da8c0c82ed9c8ac0890e4238f87
This commit introduces an incomplete processor that decodes varint
record length-delimited streams of io.prometheus.client.MetricFamily
Protocol Buffer messages. The Go client presently does not support
generation of said messages, but this will unblock a number of Java
changes.
This commit introduces all relevant server-side artifacts such that the
Result streams can be used by external parties for one-off tools and
such. This will ultimately better enable us to support additional
wireformats with much more ease.
Julius Volz