Java tutorial
/* * avenir: Predictive analytic based on Hadoop Map Reduce * Author: Pranab Ghosh * * Licensed under the Apache License, Version 2.0 (the "License"); you * may not use this file except in compliance with the License. You may * obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or * implied. See the License for the specific language governing * permissions and limitations under the License. */ package flink.applications.model.fraud.prepare; import flink.applications.util.data.Tuple; import flink.applications.util.hadoop.Utility; import org.apache.hadoop.conf.Configured; import org.apache.hadoop.fs.Path; import org.apache.hadoop.io.IntWritable; import org.apache.hadoop.io.NullWritable; import org.apache.hadoop.io.Text; import org.apache.hadoop.mapreduce.Job; import org.apache.hadoop.mapreduce.lib.input.FileInputFormat; import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat; import org.apache.hadoop.util.Tool; import org.apache.hadoop.util.ToolRunner; /** * Markov state transition probability matrix * * @author pranab */ public class MarkovStateTransitionModel extends Configured implements Tool { public static void main(String[] args) throws Exception { int exitCode = ToolRunner.run(new MarkovStateTransitionModel(), args); System.exit(exitCode); } @Override public int run(String[] args) throws Exception { Job job = new Job(getConf()); String jobName = "Markov tate transition model"; job.setJobName(jobName); job.setJarByClass(MarkovStateTransitionModel.class); FileInputFormat.addInputPath(job, new Path(args[0])); FileOutputFormat.setOutputPath(job, new Path(args[1])); Utility.setConfiguration(job.getConfiguration(), "avenir"); job.setMapperClass(StateTransitionMapper.class); job.setReducerClass(StateTransitionReducer.class); job.setCombinerClass(StateTransitionCombiner.class); job.setMapOutputKeyClass(Tuple.class); job.setMapOutputValueClass(IntWritable.class); job.setOutputKeyClass(NullWritable.class); job.setOutputValueClass(Text.class); job.setNumReduceTasks(job.getConfiguration().getInt("num.reducer", 1)); int status = job.waitForCompletion(true) ? 0 : 1; return status; } }