Commit Graph

5 Commits

Author SHA1 Message Date
Bjoern Rabenstein d7f8eb1083 Change "Prometheus Team" to "The Prometheus Authors". 2015-02-02 15:14:36 +01:00
Julius Volz 4a842c5da0 Better sample value string formatting.
This forces a float format without exponent that uses the minimum number
of digits necessary to display a given sample value.
2015-01-25 23:52:46 +01:00
Julius Volz 87a585def8 Adjust various things required for the new storage backend.
- Change Fingerprints to be simple uint64s.
- Deal sensibly with missing metric names.
- Enable finer-grained time resolution.

Merge this concurrently with the merge of the new storage backend into
prometheus/prometheus.

Change-Id: Idd82f137aa0c4286df422c53ce3c62e0de285360
2014-11-24 19:56:40 +01:00
Bjoern Rabenstein 9da2fbcce3 Eliminate a number of style-guide violations.
Change-Id: Iedcd611e5c7ad24c84c004d8d6c551d1734e443c
2014-04-25 21:18:04 +02:00
Julius Volz 3ffd7c4a6c Add custom Timestamp type for sample times.
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
2013-10-31 17:12:03 +01:00