Spark implementation that takes a set of texts and use genetic programming which discover regex for grok that will match other similar texts
Add the following dependency to your POM file:
<dependency>
<groupId>com.github.chen0040</groupId>
<artifactId>spark-ml-regex-generator</artifactId>
<version>1.0.1</version>
</dependency>
The sample code below shows how the gp regex cultivator discover the regex for the message "":
GpCultivator generator = new GpCultivator();
generator.setDisplayEvery(2);
generator.setPopulationSize(1000);
generator.setMaxGenerations(50);
List<String> trainingData = new ArrayList<>();
trainingData.add("user root login at 127.0.0.1");
JavaSparkContext context = SparkContextFactory.createSparkContext("testing-1");
Grok generated_grok = generator.fit(context.parallelize(trainingData));
System.out.println("user root login at 127.0.0.1");
System.out.println(generator.getRegex()); // this is the regex generated
Match matched = generated_grok.match("user root login at 127.0.0.1");
matched.captures();
System.out.println(matched.toJson());
Below is the print out from the sample code above:
...
Generation: 4 (Pop: 1000), elapsed: 3 seconds
Global Cost: 0.2 Current Cost: 0.2
...
Global Cost: 0.14285714285714285 Current Cost: 0.16666666666666666
user root login at 127.0.0.1
%{LOGLEVEL} %{USER} %{URIPROTO} %{URIHOST} %{IPV4}
{"IPORHOST":"at","IPV4":"127.0.0.1","LOGLEVEL":"er","URIHOST":"at","URIPROTO":"login","USER":"root"}