package heyong;

import java.util.ArrayList;

import java.util.HashMap;

import java.util.List;

import java.util.Map;

import org.apache.hadoop.conf.Configuration;

import org.apache.hadoop.fs.FileSystem;

import org.apache.hadoop.fs.Path;

import org.apache.hadoop.io.LongWritable;

import org.apache.hadoop.io.SequenceFile;

import org.apache.hadoop.io.SequenceFile.Reader;

import org.apache.hadoop.io.Text;

import org.apache.mahout.common.Pair;

import org.apache.mahout.fpm.pfpgrowth.convertors.string.TopKStringPatterns;

public class ResultReaderS {

    public static Map<Integer, Long> readFrequency(Configuration configuration, String fileName) throws Exception {

        FileSystem fs = FileSystem.get(configuration);

        Reader frequencyReader = new SequenceFile.Reader(fs,

                new Path(fileName), configuration);

        Map<Integer, Long> frequency = new HashMap<Integer, Long>();

        Text key = new Text();

        LongWritable value = new LongWritable();

        while(frequencyReader.next(key, value)) {

            frequency.put(Integer.parseInt(key.toString()), value.get());

        }

        return frequency;

    }

    public static void readFrequentPatterns(

            Configuration configuration,

            String fileName,

            int transactionCount,

            Map<Integer, Long> frequency,

            double minSupport, double minConfidence) throws Exception {

        FileSystem fs = FileSystem.get(configuration);

        Reader frequentPatternsReader = new SequenceFile.Reader(fs,

                new Path(fileName), configuration);

        Text key = new Text();

        TopKStringPatterns value = new TopKStringPatterns();

        while(frequentPatternsReader.next(key, value)) {

            long firstFrequencyItem = -1;

            String firstItemId = null;

            List<Pair<List<String>, Long>> patterns = value.getPatterns();

            int i = 0;

            for(Pair<List<String>, Long> pair: patterns) {

                List<String> itemList = pair.getFirst();

                Long occurrence = pair.getSecond();

                if (i == 0) {

                    firstFrequencyItem = occurrence;

                    firstItemId = itemList.get(0);

                } else {

                    double support = (double)occurrence / transactionCount;

                    double confidence = (double)occurrence / firstFrequencyItem;

                    if ((support > minSupport

                            && confidence > minConfidence)) {

                        List<String> listWithoutFirstItem = new ArrayList<String>();

                        for(String itemId: itemList) {

                            if (!itemId.equals(firstItemId)) {

                                listWithoutFirstItem.add(itemId);

                            }

                        }

                        String firstItem = firstItemId;

                        listWithoutFirstItem.remove(firstItemId);

                        System.out.printf(

                            "%s => %s: supp=%.3f, conf=%.3f",

                            listWithoutFirstItem,

                            firstItem,

                            support,

                            confidence);

                        if (itemList.size() == 2) {

                            // we can easily compute the lift and the conviction for set of

                            // size 2, so do it

                            int otherItemId = -1;

                            for(String itemId: itemList) {

                                if (!itemId.equals(firstItemId)) {

                                    otherItemId = Integer.parseInt(itemId);

                                    break;

                                }

                            }

                            long otherItemOccurrence = frequency.get(otherItemId);

                            double lift = (double)occurrence / (firstFrequencyItem * otherItemOccurrence);

                            double conviction = (1.0 - (double)otherItemOccurrence / transactionCount) / (1.0 - confidence);

                            System.out.printf(

                                ", lift=%.3f, conviction=%.3f",

                                lift, conviction);

                        }

                        System.out.printf("\n");

                    }

                }

                i++;

            }

        }

        frequentPatternsReader.close();

    }

    public static void main(String args[]) throws Exception {

        int transactionCount = 88162;//事务总数

        String frequencyFilename = "data/fList.seq";//

        String frequentPatternsFilename = "data/frequentpatterns.seq";

        double minSupport = 0.001;//支持度

        double minConfidence = 0.3;//置信度

        Configuration configuration = new Configuration();

        Map<Integer, Long> frequency = readFrequency(configuration, frequencyFilename);

        readFrequentPatterns(configuration, frequentPatternsFilename,

                transactionCount, frequency, minSupport, minConfidence);

    }

}