Real world performance metrics: vs. java.nio (The Sequel)

About 275% faster for my particular use case

The first set of results (September 2008) measuring the performance improvement gained by the switch to java.nio for FLV indexing were not particularly scientific.  Each data point was from a different file, of dramatically different sizes, with dramatically different key-frame spacing.  The improvements are visible, but fuzzy.

From the ever powerful yet flawed Wikipedia, there is a concept to help bring these metrics into focus:

Cēterīs paribus is a Latin phrase, literally translated as “with other things the same.” It is commonly rendered in English as “all other things being equal.” A prediction, or a statement about causal or logical connections between two states of affairs, is qualified by ceteris paribus in order to acknowledge, and to rule out, the possibility of other factors which could override the relationship between the antecedent and the consequent.

ceteris paribus assumption is often fundamental to the predictive purpose of scientific inquiry. In order to formulate scientific laws, it is usually necessary to rule out factors which interfere with examining a specific causal relationship. Experimentally, the ceteris paribus assumption is realized when a scientist controls for all of the independent variables other than the one under study, so that the effect of a singleindependent variable on the dependent variable can be isolated. By holding all the other relevant factors constant, a scientist is able to focus on the unique effects of a given factor in a complex causal situation.

Blah, blah, blah.  OK, back to gathering more data with this in mind.

With a single set of 8 files from production webcasts, more results were captured in two series.  The second series was measured immediately after the first series on physically separate copies of the files.  Measurements were taken one fine evening last November on the production server described in the first post–activity was not too busy at the time, maybe 10% of capacity.

(Drum roll please…) The results:

 File Size (KB)  Speed (KBps)
v2.2 ( v2.2 ( v2.4 (java.nio) v2.4 (java.nio)
61,793 67,965 72,647 200,239 202,806
70,079 31,418 30,798 73,225 91,648
82,645 30,529 31,286 84,291 91,887
82,951 53,388 50,290 144,458 154,158
88,086 29,106 29,134 71,360 69,012
101,500 28,491 28,935 75,644 80,758
122,606 30,839 31,954 84,035 92,383
289,423 42,374 41,479 112,543 112,773


  1. Much more consistent, although in hindsight I should have encoded a video from a single source to various different qualities.  This would have made the number of index points consistent across each file.
  2. On average, java.nio performed 273% faster than
  3. The mean performance increase was 277%
  4. The minimum was 241%
  5. The maximum improvement was 288%