Project

rredis

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RReDis - a round robin database backed by redis
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 Dependencies

Development

~> 3.0
~> 3.10

Runtime

>= 0
 Project Readme

RReDis

https://github.com/dsander/RReDis

RReDis is a round robin database backed by redis. It uses the brand new lua scripting feature of redis 2.6.

Getting started

Install the gem

gem install rredis

Store some metrics

require 'rredis'
rrd = RReDis.new

# We start two hours in the past
start = (Time.now-(3600*2)).to_i

# We pretend to update the data every 10 seconds for two hours
(2*3600/10).times do |step|
  rrd.store "example", start+step*10, rand(100)
end

Fetch data from RReDis

require 'rredis'
rrd = RReDis.new

# Get the data from 5 minutes ago until now
puts rrd.get('example', Time.now-300, Time.now).inspect
# Get the data from one hour ago until 55 minutes ago
puts rrd.get('example', Time.now-3600, Time.now-3300, 'min').inspect
# Get the data from two hours ago until 90 minutes ago
puts rrd.get('example', Time.now-7200, Time.now-5400, 'max').inspect

The get function takes three or four arguments:

  • The metric to query
  • Starting time stamp for the timespan to return
  • Ending time stamp for the timespan to return
  • Optional aggregation method

The array returned contains two arrays, the first one with unix timestamps of the measurements, the second one the (aggregated) values.

Configuration

Per default RReDis is configured to store one measurement every 10 seconds for one day (called native resolution from here on), and then aggregate the measurements for the following timespans:

  • 1 week at 1 minute resolution
  • 1 month at 15 minute resolution
  • 1 year at 1 hour resolution

RReDis also stores the average, minima and maxima of aggregated measurements.

Configuration format

RReDis default configuration:

{:steps=>10, :rows=>17280, 
 :aggregations=>["average", "min", "max"], 
 :rra => [ {:steps=>60, :rows=>10080, :xff=>0.5},
           {:steps=>900, :rows=>2976, :xff=>0.5},
           {:steps=>3600, :rows=>8760, :xff=>0.5}]}

:steps interval in seconds in which to store measurements

:rows amount of measurements to store, the timespan in seconds of the native resolution equals to :steps*:rows

:aggregations array of aggregations to use for this measurement, currently available: average, min, max, sum

:rra array of archives to store historical data

For every :rra:

:steps interval in seconds in which to aggregate the measurements of the next higher resolution

:rows amount of aggregations to store, the timespan in seconds of the archive equals to :steps*:rows

:xff the xfiles factor - determines if aggregated measurements are stored. 1.0 would require 10 of 10 measurements from the next higher resolution (either form a rra or the native resolution), 0.1 would require 1 of 10 measurements

Modify the configuration

You can either explicitly configure a metric via the config method:

rrd = RReDis.new  
rrd.config("metic", {:steps => 10, :rows => 3})

Or change the default configuration which will be applied to every measurement without an explicit configuration:

rrd = RReDis.new
rrd.default_config = {:steps => 10, :rows => 3}

Performance

Even though redis supports a lot of data types, it was clearly not made to act as a round robin database, but still with lua scripting the performance is really nice.

With the default configuration RReDis is able to handle around 2.5k updates per second (ubuntu vm with two cores of an i5 750 in virtual box running on windows), which is still amazingly fast considering the complexity of the store.lua script.

Check out the default.rb script in the benchmark directory. Here are the results of my machine:

0.000395ms per op, 2529.6144076826317 op/s
415.557405432s for for 1051200 inserts
8639 stored measurements/aggregations
156 bytes used per stored measurement
6882960 measurements storable per gb of ram
794 metrics storable per gb of ram
5273285 redis commands performed
5 redis commands performed per stored measurement

Using pipelining, we are able to determine the limits of redis itself. On my box redis can handle about 10k updates per second. A "advanced" key-value store able to run a lua script 10 thousand times a second doing about 50 thousand internal operations per second is just plain amazing. Hats off! @antirez

LICENSE:

(The MIT License)

Copyright (c) 2012 Dominik Sander

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the 'Software'), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED 'AS IS', WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.