package ca.pfv.spmf.algorithms.sequentialpatterns.spam;
import java.io.BufferedReader;
import java.io.BufferedWriter;
import java.io.File;
import java.io.FileInputStream;
import java.io.FileWriter;
import java.io.IOException;
import java.io.InputStreamReader;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.HashSet;
import java.util.Iterator;
import java.util.List;
import java.util.Map;
import java.util.Map.Entry;
import java.util.Set;
import ca.pfv.spmf.patterns.itemset_list_integers_without_support.Itemset;
import ca.pfv.spmf.tools.MemoryLogger;
/**
* *
* This is the original implementation of the CM-SPAM algorithm described
* in the paper by Fournier-Viger et al. at PAKDD 2014.
*
*
* Copyright (c) 2013 Philippe Fournier-Viger, Antonio Gomariz
*
*
* This file is part of the SPMF DATA MINING SOFTWARE
* (http://www.philippe-fournier-viger.com/spmf).
*
*
* SPMF is free software: you can redistribute it and/or modify it under the
* terms of the GNU General Public License as published by the Free Software
* Foundation, either version 3 of the License, or (at your option) any later
* version.
*
*
* SPMF is distributed in the hope that it will be useful, but WITHOUT ANY
* WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR
* A PARTICULAR PURPOSE. See the GNU General Public License for more details.
*
*
* You should have received a copy of the GNU General Public License along with
* SPMF. If not, see verticalDB = new HashMap();
// List indicating the number of bits per sequence
List sequencesSize = null;
int lastBitIndex = 0; // the last bit position that is used in bitmaps
// maximum pattern length in terms of item count
private int maximumPatternLength = Integer.MAX_VALUE;
// Map: key: item value: another item that followed the first item + support
// (could be replaced with a triangular matrix...)
Map> coocMapAfter = null;
Map> coocMapEquals = null;
// Map indicating for each item, the smallest tid containing this item
// in a sequence.
Map lastItemPositionMap;
boolean useCMAPPruning = true;
boolean useLastPositionPruning = false;
/**
* Default constructor
*/
public AlgoCMSPAM() {
}
/**
* Method to run the algorithm
*
* @param input path to an input file
* @param outputFilePath path for writing the output file
* @param minsupRel the minimum support as a relative value
* @throws IOException exception if error while writing the file or reading
*/
public void runAlgorithm(String input, String outputFilePath, double minsupRel) throws IOException {
Bitmap.INTERSECTION_COUNT = 0;
// create an object to write the file
writer = new BufferedWriter(new FileWriter(outputFilePath));
// initialize the number of patterns found
patternCount = 0;
// to log the memory used
MemoryLogger.getInstance().reset();
// record start time
startTime = System.currentTimeMillis();
// RUN THE ALGORITHM
spam(input, minsupRel);
// record end time
endTime = System.currentTimeMillis();
// close the file
writer.close();
}
/**
* This is the main method for the SPAM algorithm
*
* @param an input file
* @param minsupRel the minimum support as a relative value
* @throws IOException
*/
private void spam(String input, double minsupRel) throws IOException {
// the structure to store the vertical database
// key: an item value : bitmap
verticalDB = new HashMap();
// structure to store the horizontal database
List inMemoryDB = new ArrayList();
// STEP 0: SCAN THE DATABASE TO STORE THE FIRST BIT POSITION OF EACH SEQUENCE
// AND CALCULATE THE TOTAL NUMBER OF BIT FOR EACH BITMAP
sequencesSize = new ArrayList();
lastBitIndex = 0; // variable to record the last bit position that we will use in bitmaps
try {
// read the file
FileInputStream fin = new FileInputStream(new File(input));
BufferedReader reader = new BufferedReader(new InputStreamReader(fin));
String thisLine;
int bitIndex = 0;
// for each line (sequence) in the file until the end
while ((thisLine = reader.readLine()) != null) {
// if the line is a comment, is empty or is a
// kind of metadata
if (thisLine.isEmpty() == true
|| thisLine.charAt(0) == '#' || thisLine.charAt(0) == '%'
|| thisLine.charAt(0) == '@') {
continue;
}
// record the length of the current sequence (for optimizations)
sequencesSize.add(bitIndex);
// split the sequence according to spaces into tokens
String tokens[] = thisLine.split(" ");
int[] transactionArray = new int[tokens.length];
inMemoryDB.add(transactionArray);
for (int i = 0; i < tokens.length; i++) {
int item = Integer.parseInt(tokens[i]);
transactionArray[i] = item;
// if it is not an itemset separator
if (item == -1) { // indicate the end of an itemset
// increase the number of bits that we will need for each bitmap
bitIndex++;
}
}
}
// record the last bit position for the bitmaps
lastBitIndex = bitIndex - 1;
reader.close(); // close the input file
} catch (Exception e) {
e.printStackTrace();
}
// Calculate the absolute minimum support
// by multipling the percentage with the number of
// sequences in this database
// minsup = 163;
minsup = (int) Math.ceil((minsupRel * sequencesSize.size()));
if (minsup == 0) {
minsup = 1;
}
// STEP1: SCAN THE DATABASE TO CREATE THE BITMAP VERTICAL DATABASE REPRESENTATION
try {
FileInputStream fin = new FileInputStream(new File(input));
BufferedReader reader = new BufferedReader(new InputStreamReader(fin));
String thisLine;
int sid = 0; // to know which sequence we are scanning
int tid = 0; // to know which itemset we are scanning
// for each line (sequence) from the input file
while ((thisLine = reader.readLine()) != null) {
// split the sequence according to spaces into tokens
for (String token : thisLine.split(" ")) {
if (token.equals("-1")) { // indicate the end of an itemset
tid++;
} else if (token.equals("-2")) { // indicate the end of a sequence
// determineSection(bitindex - previousBitIndex); // register the sequence length for the bitmap
sid++;
tid = 0;
} else { // indicate an item
// Get the bitmap for this item. If none, create one.
Integer item = Integer.parseInt(token);
Bitmap bitmapItem = verticalDB.get(item);
if (bitmapItem == null) {
bitmapItem = new Bitmap(lastBitIndex);
verticalDB.put(item, bitmapItem);
}
// Register the bit in the bitmap for this item
bitmapItem.registerBit(sid, tid, sequencesSize);
}
}
}
reader.close();
} catch (Exception e) {
e.printStackTrace();
}
// STEP2: REMOVE INFREQUENT ITEMS FROM THE DATABASE BECAUSE THEY WILL NOT APPEAR IN ANY FREQUENT SEQUENTIAL PATTERNS
List frequentItems = new ArrayList();
Iterator> iter = verticalDB.entrySet().iterator();
// we iterate over items from the vertical database that we have in memory
while (iter.hasNext()) {
// we get the bitmap for this item
Map.Entry entry = (Map.Entry) iter.next();
// if the cardinality of this bitmap is lower than minsup
if (entry.getValue().getSupport() < minsup) {
// we remove this item from the database.
iter.remove();
} else {
// otherwise, we save this item as a frequent
// sequential pattern of size 1
savePattern(entry.getKey(), entry.getValue());
// and we add this item to a list of frequent items
// that we will use later.
frequentItems.add(entry.getKey());
}
}
// STEP 3.1 CREATE CMAP
coocMapEquals = new HashMap>(frequentItems.size());
coocMapAfter = new HashMap>(frequentItems.size());
if (useLastPositionPruning) {
lastItemPositionMap = new HashMap(frequentItems.size());
}
for (int[] transaction : inMemoryDB) {
short itemsetCount = 0;
Set alreadyProcessed = new HashSet();
Map> equalProcessed = new HashMap<>();
loopI:
for (int i = 0; i < transaction.length; i++) {
Integer itemI = transaction[i];
Set equalSet = equalProcessed.get(itemI);
if (equalSet == null) {
equalSet = new HashSet();
equalProcessed.put(itemI, equalSet);
}
if (itemI < 0) {
itemsetCount++;
continue;
}
// System.out.println(itemsetCount);
// update lastItemMap
if (useLastPositionPruning) {
Short last = lastItemPositionMap.get(itemI);
if (last == null || last < itemsetCount) {
lastItemPositionMap.put(itemI, itemsetCount);
}
}
Bitmap bitmapOfItem = verticalDB.get(itemI);
if (bitmapOfItem == null || bitmapOfItem.getSupport() < minsup) {
continue;
}
Set alreadyProcessedB = new HashSet(); // NEW
boolean sameItemset = true;
for (int j = i + 1; j < transaction.length; j++) {
Integer itemJ = transaction[j];
if (itemJ < 0) {
sameItemset = false;
continue;
}
Bitmap bitmapOfitemJ = verticalDB.get(itemJ);
if (bitmapOfitemJ == null || bitmapOfitemJ.getSupport() < minsup) {
continue;
}
// if (itemI != itemJ){
Map map = null;
if (sameItemset) {
if (!equalSet.contains(itemJ)) {
map = coocMapEquals.get(itemI);
if (map == null) {
map = new HashMap();
coocMapEquals.put(itemI, map);
}
Integer support = map.get(itemJ);
if (support == null) {
map.put(itemJ, 1);
} else {
map.put(itemJ, ++support);
}
equalSet.add(itemJ);
}
} else if (!alreadyProcessedB.contains(itemJ)) {
if (alreadyProcessed.contains(itemI)) {
continue loopI;
}
map = coocMapAfter.get(itemI);
if (map == null) {
map = new HashMap();
coocMapAfter.put(itemI, map);
}
Integer support = map.get(itemJ);
if (support == null) {
map.put(itemJ, 1);
} else {
map.put(itemJ, ++support);
}
alreadyProcessedB.add(itemJ); // NEW
}
}
alreadyProcessed.add(itemI);
}
}
// STEP3: WE PERFORM THE RECURSIVE DEPTH FIRST SEARCH
// to find longer sequential patterns recursively
if (maximumPatternLength == 1) {
return;
}
// for each frequent item
for (Entry entry : verticalDB.entrySet()) {
// We create a prefix with that item
Prefix prefix = new Prefix();
prefix.addItemset(new Itemset(entry.getKey()));
// We call the depth first search method with that prefix
// and the list of frequent items to try to find
// larger sequential patterns by appending some of these
// items.
dfsPruning(prefix, entry.getValue(), frequentItems, frequentItems, entry.getKey(), 2, entry.getKey());
}
}
/**
* This is the dfsPruning method as described in the SPAM paper.
*
* @param prefix the current prefix
* @param prefixBitmap the bitmap corresponding to the current prefix
* @param sn a list of items to be considered for i-steps
* @param in a list of items to be considered for s-steps
* @param hasToBeGreaterThanForIStep
* @param m size of the current prefix in terms of items
* @param lastAppendedItem the last appended item to the prefix
* @throws IOException if there is an error writing a pattern to the output
* file
*/
private void dfsPruning(Prefix prefix, Bitmap prefixBitmap, List sn, List in, int hasToBeGreaterThanForIStep, int m, Integer lastAppendedItem) throws IOException {
// System.out.println(prefix.toString());
// ====== S-STEPS ======
// Temporary variables (as described in the paper)
List sTemp = new ArrayList();
List sTempBitmaps = new ArrayList();
// for CMAP pruning, we will only check against the last appended item
Map mapSupportItemsAfter = coocMapAfter.get(lastAppendedItem);
// for each item in sn
loopi:
for (Integer i : sn) {
// LAST POSITION PRUNING
/*if (useLastPositionPruning && lastItemPositionMap.get(i) < prefixBitmap.firstItemsetID) {
// System.out.println("TEST");
continue loopi;
}*/
// CMAP PRUNING
// we only check with the last appended item
if (useCMAPPruning) {
if (mapSupportItemsAfter == null) {
continue loopi;
}
Integer support = mapSupportItemsAfter.get(i);
if (support == null || support < minsup) {
// System.out.println("PRUNE");
continue loopi;
}
}
// perform the S-STEP with that item to get a new bitmap
Bitmap.INTERSECTION_COUNT++;
Bitmap newBitmap = prefixBitmap.createNewBitmapSStep(verticalDB.get(i), sequencesSize, lastBitIndex);
// if the support is higher than minsup
if (newBitmap.getSupport() >= minsup) {
// record that item and pattern in temporary variables
sTemp.add(i);
sTempBitmaps.add(newBitmap);
}
}
// for each pattern recorded for the s-step
for (int k = 0; k < sTemp.size(); k++) {
int item = sTemp.get(k);
// create the new prefix
Prefix prefixSStep = prefix.cloneSequence();
prefixSStep.addItemset(new Itemset(item));
// create the new bitmap
Bitmap newBitmap = sTempBitmaps.get(k);
// save the pattern to the file
savePattern(prefixSStep, newBitmap);
// recursively try to extend that pattern
if (maximumPatternLength > m) {
dfsPruning(prefixSStep, newBitmap, sTemp, sTemp, item, m + 1, item);
}
}
Map mapSupportItemsEquals = coocMapEquals.get(lastAppendedItem);
// ======== I STEPS =======
// Temporary variables
List iTemp = new ArrayList();
List iTempBitmaps = new ArrayList();
// for each item in in
loop2:
for (Integer i : in) {
// the item has to be greater than the largest item
// already in the last itemset of prefix.
if (i > hasToBeGreaterThanForIStep) {
// LAST POSITION PRUNING
/*if (useLastPositionPruning && lastItemPositionMap.get(i) < prefixBitmap.firstItemsetID) {
continue loop2;
}*/
// CMAP PRUNING
if (useCMAPPruning) {
if (mapSupportItemsEquals == null) {
continue loop2;
}
Integer support = mapSupportItemsEquals.get(i);
if (support == null || support < minsup) {
continue loop2;
}
}
// Perform an i-step with this item and the current prefix.
// This creates a new bitmap
Bitmap.INTERSECTION_COUNT++;
Bitmap newBitmap = prefixBitmap.createNewBitmapIStep(verticalDB.get(i), sequencesSize, lastBitIndex);
// If the support is no less than minsup
if (newBitmap.getSupport() >= minsup) {
// record that item and pattern in temporary variables
iTemp.add(i);
iTempBitmaps.add(newBitmap);
}
}
}
// for each pattern recorded for the i-step
for (int k = 0; k < iTemp.size(); k++) {
int item = iTemp.get(k);
// create the new prefix
Prefix prefixIStep = prefix.cloneSequence();
prefixIStep.getItemsets().get(prefixIStep.size() - 1).addItem(item);
// create the new bitmap
Bitmap newBitmap = iTempBitmaps.get(k);
// save the pattern
savePattern(prefixIStep, newBitmap);
// recursively try to extend that pattern
if (maximumPatternLength > m) {
dfsPruning(prefixIStep, newBitmap, sTemp, iTemp, item, m + 1, item);
}
}
// check the memory usage
MemoryLogger.getInstance().checkMemory();
}
/**
* Save a pattern of size 1 to the output file
*
* @param item the item
* @param bitmap its bitmap
* @throws IOException exception if error while writing to the file
*/
private void savePattern(Integer item, Bitmap bitmap) throws IOException {
patternCount++; // increase the pattern count
StringBuilder r = new StringBuilder("");
r.append(item);
r.append(" -1 ");
r.append("SUP: ");
r.append(bitmap.getSupport());
writer.write(r.toString());
writer.newLine();
}
/**
* Save a pattern of size > 1 to the output file.
*
* @param prefix the prefix
* @param bitmap its bitmap
* @throws IOException exception if error while writing to the file
*/
private void savePattern(Prefix prefix, Bitmap bitmap) throws IOException {
patternCount++;
StringBuilder r = new StringBuilder("");
for (Itemset itemset : prefix.getItemsets()) {
// r.append('(');
for (Integer item : itemset.getItems()) {
String string = item.toString();
r.append(string);
r.append(' ');
}
r.append("-1 ");
}
r.append("SUP: ");
r.append(bitmap.getSupport());
writer.write(r.toString());
// System.out.println(r.toString());
writer.newLine();
}
/**
* Print the statistics of the algorithm execution to System.out.
*/
public void printStatistics() {
StringBuilder r = new StringBuilder(200);
r.append("============= Algorithm - STATISTICS =============\n Total time ~ ");
r.append(endTime - startTime);
r.append(" ms\n");
r.append(" Frequent sequences count : " + patternCount);
r.append('\n');
r.append(" Max memory (mb) : ");
r.append(MemoryLogger.getInstance().getMaxMemory());
r.append(patternCount);
r.append('\n');
r.append("minsup " + minsup);
r.append('\n');
r.append("Intersection count " + Bitmap.INTERSECTION_COUNT + " \n");
r.append("===================================================\n");
System.out.println(r.toString());
}
/**
* Get the maximum length of patterns to be found (in terms of itemset
* count)
*
* @return the maximumPatternLength
*/
public int getMaximumPatternLength() {
return maximumPatternLength;
}
/**
* Set the maximum length of patterns to be found (in terms of itemset
* count)
*
* @param maximumPatternLength the maximumPatternLength to set
*/
public void setMaximumPatternLength(int maximumPatternLength) {
this.maximumPatternLength = maximumPatternLength;
}
}
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