[erlang-questions] [ANN] HDR Histogram 0.2.3 High Dynamic Range Histogram library for Erlang/OTP

Darach Ennis darach@REDACTED
Fri Feb 27 13:37:56 CET 2015


Hi folk,

A high dynamic range histogram is one that supports recording and analyzing
sampled data points across a configurable range with configurable precision
within that range. The precision is expressed as a number of significant
figures in the recording.

This HDR histogram implementation is designed for recording histograms of
value measurements in latency sensitive environments. Although the native
recording times can be as low as single digit nanoseconds there is added
overhead in this wrapper/binding due to both the frontend overhead of
converting from native C to the NIF interface, and the erlang overhead
incurred calling into the NIFs. C'est la vie, I suppose.

A distinct advantage of this histogram implementation is constant space and
recording (time) overhead with an ability to recycle and reset instances
whilst reclaiming already allocated space for reuse thereby reducing
allocation cost and garbage collection overhead in the BEAM where repeated
or continuous usage is likely. For example, a gen_server recording metrics
continuously and resetting and logging histogram dumps on a periodic or
other windowed basis.

Since announced at 0.1.0:

* Moved to the HDR Histogram organization and is now part of that project
* Histograms can now be easily iterated by record, linearly,
logarithmically and by percentile
* Histograms can now be serialized to and deserialized from zlib compressed
or raw binary
* Automated continuous integration tests via travis covering R16B02 .. R17.3
* Gitter service. This is a chat room where you'll find expertise on HDR
Histogram in various flavors (Java, C, C#, Erlang ...) from authors,
contributors and users.
* Thanks. Heinz Gies of Project FIFO for contributing a patch. Mark Allen
of Basho for feedback that improved docs and will influence the next
version 0.3.

Where:
  https://github.com/HdrHistogram/hdr_histogram_erl

Enjoy!
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