| /* |
| * 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 org.apache.pig.tutorial; |
| |
| import java.io.IOException; |
| import java.util.ArrayList; |
| import java.util.HashMap; |
| import java.util.Iterator; |
| import java.util.List; |
| import java.util.Map; |
| |
| import org.apache.pig.EvalFunc; |
| import org.apache.pig.data.DataBag; |
| import org.apache.pig.data.DataType; |
| import org.apache.pig.data.DefaultBagFactory; |
| import org.apache.pig.data.Tuple; |
| import org.apache.pig.data.TupleFactory; |
| import org.apache.pig.impl.logicalLayer.FrontendException; |
| import org.apache.pig.impl.logicalLayer.schema.Schema; |
| |
| /** |
| * For each n-gram, we have a set of (hour, count) pairs. |
| * |
| * This function reads the set and retains those hours with above |
| * above mean count, and calculates the score of each retained hour as the |
| * multiplier of the count of the hour over the standard deviation. |
| * |
| * A score greater than 1.0 indicates the frequency of this n-gram |
| * in this particular hour is at least one standard deviation away |
| * from the average frequency among all hours |
| */ |
| |
| public class ScoreGenerator extends EvalFunc<DataBag> { |
| |
| private static double computeMean(List<Long> counts) { |
| int numCounts = counts.size(); |
| |
| // compute mean |
| double mean = 0.0; |
| for (Long count : counts) { |
| mean += ((double) count) / ((double) numCounts); |
| } |
| |
| return mean; |
| } |
| |
| private static double computeSD(List<Long> counts, double mean) { |
| int numCounts = counts.size(); |
| |
| // compute deviation |
| double deviation = 0.0; |
| for (Long count : counts) { |
| double d = ((double) count) - mean; |
| deviation += d * d / ((double) numCounts); |
| } |
| |
| return Math.sqrt(deviation); |
| } |
| |
| public DataBag exec(Tuple input) throws IOException { |
| if (input == null || input.size() == 0) |
| return null; |
| try{ |
| DataBag output = DefaultBagFactory.getInstance().newDefaultBag(); |
| DataBag in = (DataBag)input.get(0); |
| |
| Map<String, Long> pairs = new HashMap<String, Long>(); |
| List<Long> counts = new ArrayList<Long> (); |
| |
| Iterator<Tuple> it = in.iterator(); |
| while (it.hasNext()) { |
| Tuple t = it.next(); |
| String hour = (String)t.get(1); |
| Long count = (Long)t.get(2); |
| pairs.put(hour, count); |
| counts.add(count); |
| } |
| |
| double mean = computeMean(counts); |
| double standardDeviation = computeSD(counts, mean); |
| |
| Iterator<String> it2 = pairs.keySet().iterator(); |
| while (it2.hasNext()) { |
| String hour = it2.next(); |
| Long count = pairs.get(hour); |
| if ( count > mean ) { |
| Tuple t = TupleFactory.getInstance().newTuple(4); |
| t.set(0, hour); |
| t.set(1, ((double) count - mean) / standardDeviation ); // the score |
| t.set(2, count); |
| t.set(3, mean); |
| output.add(t); |
| } |
| } |
| return output; |
| }catch (Exception e){ |
| System.err.println("ScoreGenerator: failed to process input; error - " + e.getMessage()); |
| return null; |
| } |
| } |
| |
| @Override |
| /** |
| * This method gives a name to the column. |
| * @param input - schema of the input data |
| * @return schema of the output data |
| */ |
| public Schema outputSchema(Schema input) { |
| Schema bagSchema = new Schema(); |
| bagSchema.add(new Schema.FieldSchema("hour", DataType.CHARARRAY)); |
| bagSchema.add(new Schema.FieldSchema("score", DataType.DOUBLE)); |
| bagSchema.add(new Schema.FieldSchema("count", DataType.LONG)); |
| bagSchema.add(new Schema.FieldSchema("mean", DataType.DOUBLE)); |
| //TODO |
| //Here the schema of the bag is the schema of the tuple inside the bag |
| //We need to change this so that the bag has the tuple and the tuple has the schema |
| try{ |
| return new Schema(new Schema.FieldSchema(getSchemaName(this.getClass().getName().toLowerCase(), input), bagSchema, DataType.BAG)); |
| }catch (FrontendException e){ |
| return null; |
| } |
| } |
| |
| } |