Hist4J is a simple high-performace value aggregator that accepts large datasets with any distribution or range and provides several statistical functions, using a very small memory footprint and requiring no pre- or post-processing.
Hist4j has the following features:
- It adapts to any data distribution, keeping a more or less constant resolution throughout the data range by increasing the resolution where the data is more dense.
- It can process large amounts of data with a very small memory footprint.
- It doesn't need pre- or post-processing to deliver statistics about the data seen so far.
The following statistics are currently available:
- The cumulative density function for a given data point.
- The data point that splits the data set at a given percentile.
The default ant target will generate hist4j-trunk.jar.
Apache 2.0
A typical use case is measuring response times of a service. In this case, we can create a histogram object:
AdaptiveHistogram h = new Histogram();
Then, for every service response, we log the time:
h.addValue(elapsedTime);
On fixed intervals (maybe a few minutes, maybe a few hours), recreate the histogram object, and print the information of the old one:
hOld = h;
h = new Histogram();
//print hOld.getValueForPercentile(95)
In the root project directory, the file Hist4jExample.java shows a minimal but useful example. Just run ./run_example.sh to compile and run.