https://github.com/ztellman/narrator

This is a reimplementation of an approach I've discussed in several talks 
[1] [2], with an eye towards performance, memory efficiency, and 
flexibility w.r.t. how the event stream is represented.  The readme does a 
good job of explaining how it works, but there have been a number of new 
event processing libraries recently (core.async, EEP, etc.), so I'll spend 
some time here describing how this differs.

First, this library is focused on aggregations over event streams, not 
arbitrary transformations.  It is designed such that these aggregations can 
be automatically parallelized, and use non-thread-safe data structures 
(such as those in the excellent stream-lib [3]) without having to worry 
about coordination.  As such, within this narrower application it has a 
richer set of operators, and should be a fair bit faster (millions of 
messages/sec/core).

Second, this has support for time-series analysis of ordered streams, 
either historical or in real time.  The input for either type of analysis 
can be normal sequences, core.async channels, or Lamina channels. At 
Factual we use this for aggregations across many of our real-time systems, 
and I also use it for both ad hoc queries and daily rollups of logs and 
other historical data.

On a personal note, I think this is one of the most interesting and useful 
libraries I've written.  I'm really looking forward to seeing how people 
use it, and encourage feedback on how to make it better.

Zach

[1] http://www.infoq.com/presentations/analyze-running-system
[2] http://vimeo.com/45132054#!
[3] https://github.com/addthis/stream-lib

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