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.IOException; import java.util.ArrayList; import org.apache.hadoop.conf.Configuration; import org.apache.hadoop.fs.FileSystem; import org.apache.hadoop.fs.Path; import org.apache.hadoop.io.Text; 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 com.cloudera.knittingboar.io.InputRecordsSplit; import com.cloudera.knittingboar.messages.GlobalParameterVectorUpdateMessage; import com.cloudera.knittingboar.messages.GradientUpdateMessage; import com.cloudera.knittingboar.records.RecordFactory; import junit.framework.TestCase; /** * A simulation of a single POLR master and a worker for each generated split of the data * for the RCV1 dataset: * * https://github.com/JohnLangford/vowpal_wabbit/wiki/Rcv1-example * * @author jpatterson * */ public class TestRunRCV1Subset 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 inputDir = new Path( System.getProperty("test.build.data", "/Users/jpatterson/Downloads/rcv1/subset/train/")); private static Path fullRCV1Dir = new Path("/Users/jpatterson/Downloads/rcv1/rcv1.train.vw"); public Configuration generateDebugConfigurationObject() { Configuration c = new Configuration(); // feature vector size c.setInt("com.cloudera.knittingboar.setup.FeatureVectorSize", 10000); c.setInt("com.cloudera.knittingboar.setup.numCategories", 2); c.setInt("com.cloudera.knittingboar.setup.BatchSize", 200); // local input split path c.set("com.cloudera.knittingboar.setup.LocalInputSplitPath", "hdfs://127.0.0.1/input/0"); // setup 20newsgroups c.set("com.cloudera.knittingboar.setup.RecordFactoryClassname", RecordFactory.RCV1_RECORDFACTORY); /* // 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 void testSplits() throws IOException { // ---- this all needs to be done in JobConf job = new JobConf(defaultConf); // TODO: work on this, splits are generating for everything in dir InputSplit[] splits = generateDebugSplits(inputDir, job); System.out.println("split count: " + splits.length); assertEquals(10, splits.length); InputSplit[] splits_full = generateDebugSplits(fullRCV1Dir, job); System.out.println("full rcv1 split count: " + splits_full.length); Text value = new Text(); for (int x = 0; x < splits_full.length; x++) { InputRecordsSplit custom_reader_0 = new InputRecordsSplit(job, splits_full[x]); custom_reader_0.next(value); System.out.println(x + " > " + value.toString()); custom_reader_0.next(value); System.out.println(x + " > " + value.toString()); custom_reader_0.next(value); System.out.println(x + " > " + value.toString() + "\n"); } } public void testRunRCV1Subset() throws IOException, Exception { int num_passes = 15; POLRMasterDriver master = new POLRMasterDriver(); // ------------------ // generate the debug conf ---- normally setup by YARN stuff master.setConf(this.generateDebugConfigurationObject()); // now load the conf stuff into locally used vars try { master.LoadConfigVarsLocally(); } catch (Exception e) { // TODO Auto-generated catch block e.printStackTrace(); System.out.println("Conf load fail: shutting down."); assertEquals(0, 1); } // now construct any needed machine learning data structures based on config master.Setup(); // ------------------ // ---- this all needs to be done in JobConf job = new JobConf(defaultConf); InputSplit[] splits = generateDebugSplits(fullRCV1Dir, job); System.out.println("split count: " + splits.length); ArrayList<POLRWorkerDriver> workers = new ArrayList<POLRWorkerDriver>(); for (int x = 0; x < splits.length; x++) { POLRWorkerDriver worker_model_builder = new POLRWorkerDriver(); //workers.get(x); worker_model_builder.internalID = String.valueOf(x); // simulates the conf stuff worker_model_builder.setConf(this.generateDebugConfigurationObject()); InputRecordsSplit custom_reader_0 = new InputRecordsSplit(job, splits[x]); // TODO: set this up to run through the conf pathways worker_model_builder.setupInputSplit(custom_reader_0); worker_model_builder.LoadConfigVarsLocally(); worker_model_builder.Setup(); workers.add(worker_model_builder); System.out.println("> Setup Worker " + x); } for (int x = 0; x < num_passes; x++) { for (int worker_id = 0; worker_id < workers.size(); worker_id++) { workers.get(worker_id).RunNextTrainingBatch(); GradientUpdateMessage msg0 = workers.get(worker_id).GenerateUpdateMessage(); master.AddIncomingGradientMessageToQueue(msg0); master.RecvGradientMessage(); // process msg } if (x < num_passes - 1) { master.GenerateGlobalUpdateVector(); GlobalParameterVectorUpdateMessage returned_msg = master.GetNextGlobalUpdateMsgFromQueue(); // process global updates for (int worker_id = 0; worker_id < workers.size(); worker_id++) { workers.get(worker_id).ProcessIncomingParameterVectorMessage(returned_msg); } System.out.println("---------- cycle " + x + " done ------------- "); } else { System.out.println("---------- cycle " + x + " done ------------- "); System.out.println("> Saving Model..."); master.SaveModelLocally("/tmp/master_sgd.model"); } // if } // for workers.get(0).Debug(); } }