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https://github.com/HdrHistogram/hdrhistogram-go

Last synced: about 4 hours ago

Repository metadata:

A pure Go implementation of Gil Tene's HDR Histogram.


Owner metadata:


Committers metadata

Last synced: about 7 hours ago

Total Commits: 69
Total Committers: 11
Avg Commits per committer: 6.273
Development Distribution Score (DDS): 0.623

Commits in past year: 0
Committers in past year: 0
Avg Commits per committer in past year: 0.0
Development Distribution Score (DDS) in past year: 0.0

Name Email Commits
filipecosta90 f****0@g****m 26
Coda Hale c****e@g****m 23
Adrian Cockcroft a****t@g****m 5
Tyler Treat t****1@g****m 5
Alec a****n@c****m 3
Carl Jackson c****l@a****m 2
Coda Hale c****a@s****m 1
Jason Toffaletti t****i@g****m 1
Jeff Jolma j****a@g****m 1
Sean Chittenden s****n@c****g 1
Tobias Schottdorf t****f@g****m 1

Issue and Pull Request metadata

Last synced: 1 day ago


Package metadata

go: github.com/HdrHistogram/hdrhistogram-go

Package hdrhistogram provides an implementation of Gil Tene's HDR Histogram data structure. The HDR Histogram allows for fast and accurate analysis of the extreme ranges of data with non-normal distributions, like latency. Histograms are encoded using the HdrHistogram V2 format which is based on an adapted ZigZag LEB128 encoding where: consecutive zero counters are encoded as a negative number representing the count of consecutive zeros non zero counter values are encoded as a positive number A typical histogram (2 digits precision 1 usec to 1 day range) can be encoded in less than the typical MTU size of 1500 bytes. The log format encodes into a single file, multiple histograms with optional shared meta data.

  • Homepage: https://github.com/HdrHistogram/hdrhistogram-go
  • Documentation: https://pkg.go.dev/github.com/HdrHistogram/hdrhistogram-go#section-documentation
  • Licenses: MIT
  • Latest release: v1.1.2 (published about 3 years ago)
  • Last Synced: 2024-11-09T00:04:32.806Z (1 day ago)
  • Versions: 6
  • Dependent Packages: 2,488
  • Dependent Repositories: 7,087
  • Docker Downloads: 3,318,799,140
  • Rankings:
    • Dependent packages count: 0.074%
    • Docker downloads count: 0.075%
    • Dependent repos count: 0.09%
    • Average: 1.259%
    • Stargazers count: 2.868%
    • Forks count: 3.191%
go: github.com/hdrhistogram/hdrhistogram-go

Package hdrhistogram provides an implementation of Gil Tene's HDR Histogram data structure. The HDR Histogram allows for fast and accurate analysis of the extreme ranges of data with non-normal distributions, like latency.

  • Homepage: https://github.com/hdrhistogram/hdrhistogram-go
  • Documentation: https://pkg.go.dev/github.com/hdrhistogram/hdrhistogram-go#section-documentation
  • Licenses: MIT
  • Latest release: v1.1.2 (published about 3 years ago)
  • Last Synced: 2024-11-09T00:04:37.385Z (1 day ago)
  • Versions: 6
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Docker Downloads: 2,145,519
  • Rankings:
    • Stargazers count: 1.736%
    • Forks count: 1.912%
    • Average: 4.998%
    • Dependent packages count: 6.999%
    • Dependent repos count: 9.346%
go: github.com/hdrHistogram/hdrhistogram-go

Package hdrhistogram provides an implementation of Gil Tene's HDR Histogram data structure. The HDR Histogram allows for fast and accurate analysis of the extreme ranges of data with non-normal distributions, like latency.

  • Homepage: https://github.com/hdrHistogram/hdrhistogram-go
  • Documentation: https://pkg.go.dev/github.com/hdrHistogram/hdrhistogram-go#section-documentation
  • Licenses: MIT
  • Latest release: v1.1.2 (published about 3 years ago)
  • Last Synced: 2024-11-09T00:04:55.360Z (1 day ago)
  • Versions: 6
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Rankings:
    • Dependent packages count: 6.999%
    • Average: 8.173%
    • Dependent repos count: 9.346%