Java tutorial
/** * Licensed to the Apache Software Foundation (ASF) under one or more * contributor license agreements. See the NOTICE file distributed with * this work for additional information regarding copyright ownership. * The ASF licenses this file to You 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 com.cloudera.knittingboar.sgd; import java.io.BufferedReader; import java.io.File; import java.io.FileInputStream; import java.io.IOException; import java.io.InputStream; import java.io.InputStreamReader; import org.apache.hadoop.conf.Configuration; import org.apache.hadoop.fs.FileSystem; import org.apache.hadoop.fs.Path; import org.apache.hadoop.mapred.FileInputFormat; import org.apache.hadoop.mapred.InputSplit; import org.apache.hadoop.mapred.JobConf; import org.apache.hadoop.mapred.TextInputFormat; import junit.framework.TestCase; import com.cloudera.knittingboar.io.InputRecordsSplit; import com.cloudera.knittingboar.records.RecordFactory; import com.google.common.base.Charsets; import com.google.common.collect.Sets; import com.google.common.io.Resources; public class TestBaseSGD extends TestCase { private static JobConf defaultConf = new JobConf(); private static FileSystem localFs = null; static { try { defaultConf.set("fs.defaultFS", "file:///"); localFs = FileSystem.getLocal(defaultConf); } catch (IOException e) { throw new RuntimeException("init failure", e); } } //private static Path workDir = new Path(System.getProperty("/Users/jpatterson/Documents/workspace/WovenWabbit/data/donut_no_header.csv")); private static Path workDir = new Path(System.getProperty("test.build.data", "/Users/jpatterson/Documents/workspace/WovenWabbit/data/donut_no_header.csv")); public Configuration generateDebugConfigurationObject() { Configuration c = new Configuration(); // feature vector size c.setInt("com.cloudera.knittingboar.setup.FeatureVectorSize", 20); c.setInt("com.cloudera.knittingboar.setup.numCategories", 2); c.setInt("com.cloudera.knittingboar.setup.BatchSize", 10); c.set("com.cloudera.knittingboar.setup.RecordFactoryClassname", RecordFactory.CSV_RECORDFACTORY); // local input split path c.set("com.cloudera.knittingboar.setup.LocalInputSplitPath", "hdfs://127.0.0.1/input/0"); // predictor label names c.set("com.cloudera.knittingboar.setup.PredictorLabelNames", "x,y"); // predictor var types c.set("com.cloudera.knittingboar.setup.PredictorVariableTypes", "numeric,numeric"); // target variables c.set("com.cloudera.knittingboar.setup.TargetVariableName", "color"); // column header names c.set("com.cloudera.knittingboar.setup.ColumnHeaderNames", "x,y,shape,color,k,k0,xx,xy,yy,a,b,c,bias"); //c.set( "com.cloudera.knittingboar.setup.ColumnHeaderNames", "\"x\",\"y\",\"shape\",\"color\",\"k\",\"k0\",\"xx\",\"xy\",\"yy\",\"a\",\"b\",\"c\",\"bias\"\n" ); return c; } public InputSplit[] generateDebugSplits(Path input_path, JobConf job) { long block_size = localFs.getDefaultBlockSize(); System.out.println("default block size: " + (block_size / 1024 / 1024) + "MB"); // ---- set where we'll read the input files from ------------- FileInputFormat.setInputPaths(job, input_path); // try splitting the file in a variety of sizes TextInputFormat format = new TextInputFormat(); format.configure(job); int numSplits = 1; InputSplit[] splits = null; try { splits = format.getSplits(job, numSplits); } catch (IOException e) { // TODO Auto-generated catch block e.printStackTrace(); } return splits; } public static BufferedReader open(String inputFile) throws IOException { InputStream in; try { in = Resources.getResource(inputFile).openStream(); } catch (IllegalArgumentException e) { in = new FileInputStream(new File(inputFile)); } return new BufferedReader(new InputStreamReader(in, Charsets.UTF_8)); } public void testConfigStuff() { String lambda = "1.0e-4"; double parsed_lambda = Double.parseDouble(lambda); System.out.println("Parsed Double: " + parsed_lambda); } public void testTrainer() throws Exception { POLRWorkerDriver olr_run = new POLRWorkerDriver(); // generate the debug conf ---- normally setup by YARN stuff olr_run.setConf(this.generateDebugConfigurationObject()); // ---- this all needs to be done in JobConf job = new JobConf(defaultConf); InputSplit[] splits = generateDebugSplits(workDir, job); InputRecordsSplit custom_reader = new InputRecordsSplit(job, splits[0]); // TODO: set this up to run through the conf pathways olr_run.setupInputSplit(custom_reader); olr_run.LoadConfigVarsLocally(); olr_run.Setup(); for (int x = 0; x < 25; x++) { olr_run.RunNextTrainingBatch(); System.out.println("---------- cycle " + x + " done ------------- "); } // for //olr_run.PrintModelStats(); //LogisticModelParameters lmp = model_builder.lmp;//TrainLogistic.getParameters(); assertEquals(1.0e-4, olr_run.polr_modelparams.getLambda(), 1.0e-9); assertEquals(20, olr_run.polr_modelparams.getNumFeatures()); assertTrue(olr_run.polr_modelparams.useBias()); assertEquals("color", olr_run.polr_modelparams.getTargetVariable()); //CsvRecordFactory csv = model_builder.lmp.getCsvRecordFactory(); // assertEquals("[1, 2]", Sets.newTreeSet(olr_run.csvVectorFactory.getTargetCategories()).toString()); // assertEquals("[Intercept Term, x, y]", Sets.newTreeSet(olr_run.csvVectorFactory.getPredictors()).toString()); System.out.println("done!"); assertNotNull(0); } }