From 4c8b38a75958e11c54296ff4fdecbab9468cc41f Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Sylvain=20Hall=C3=A9?= Date: Fri, 16 Jan 2015 10:49:17 -0500 Subject: [PATCH] Fixed warnings in Javadoc target --- .../src/ca/uqac/dim/mapreduce/Collector.java | 244 +++++----- .../ca/uqac/dim/mapreduce/InCollector.java | 4 +- .../src/ca/uqac/dim/mapreduce/Mapper.java | 2 +- .../ca/uqac/dim/mapreduce/OutCollector.java | 3 +- .../uqac/dim/mapreduce/ParallelWorkflow.java | 328 +++++++------- .../uqac/dim/mapreduce/ResourceManager.java | 416 +++++++++--------- .../dim/mapreduce/SequentialWorkflow.java | 8 +- .../src/ca/uqac/dim/mapreduce/Workflow.java | 2 +- build.xml | 36 +- mrsim.jar | Bin 304681 -> 113812 bytes 10 files changed, 524 insertions(+), 519 deletions(-) diff --git a/Source/MapReduce/src/ca/uqac/dim/mapreduce/Collector.java b/Source/MapReduce/src/ca/uqac/dim/mapreduce/Collector.java index 1773490..f50ddf8 100644 --- a/Source/MapReduce/src/ca/uqac/dim/mapreduce/Collector.java +++ b/Source/MapReduce/src/ca/uqac/dim/mapreduce/Collector.java @@ -22,12 +22,12 @@ * Data source used both as the input and output of the map and reduce * phases. A Collector can be used to: *
    - *
  1. Store data tuples using the {@link collect} method
  2. - *
  3. Enumerate data tuples using the {@link hasNext} and {@link next} - * methods, like an {@link Iterator}
  4. + *
  5. Store data tuples using the {@link Collector#collect(Tuple)} method
  6. + *
  7. Enumerate data tuples using the {@link Collector#hasNext()} + * and {@link Collector#next()} methods, like an {@link Iterator}
  8. *
  9. Partition the set of tuples into a set of Collectors, grouping - * tuples by their key, using the {@link subCollector} and - * {@link subCollectors} methods
  10. + * tuples by their key, using the {@link Collector#subCollector(Object)} and + * {@link Collector#subCollectors()} methods *
* @author Sylvain Hallé * @version 1.1 @@ -35,121 +35,121 @@ */ public class Collector implements InCollector, OutCollector { - private List> m_tuples = new LinkedList>(); - private Iterator> m_it = null; - - /** - * Return the Collector's contents as a list of tuples - * @return The list of tuples - */ - public List> toList() - { - return m_tuples; - } - - /** - * Add a collection of tuples to the Collector - * @param list A collection of {@link Tuple} - */ - public void addAll(Collection> list) - { - synchronized (this) { - m_tuples.addAll(list); - } - } - - /** - * Add a new tuple to the Collector in a synchronized mode - * @param t The {@link Tuple} to add - */ - public void collect(Tuple t) - { - synchronized (this) { - m_tuples.add(t); - } - } - - /** - * Returns a new Collector whose content is made of all tuples with - * given key - * @param key The key to find - * @return A new {@link Collector} - */ - public Collector subCollector(K key) - { - Collector c = new Collector(); - synchronized (this) { - for (Tuple t : m_tuples) - { - if (t.getKey().equals(key)) - c.m_tuples.add(t); - } - } - return c; - - } - - public int count() - { - synchronized (this) { - return m_tuples.size(); - } - } - - /** - * Partitions the set of tuples into new collectors, each containing all - * tuples with the same key - * @return A map from keys to Collectors - */ - public Map> subCollectors() - { - Map> out = new HashMap>(); - - synchronized (this) { - for ( Tuple t : m_tuples) - { - K key = t.getKey(); - Collector c = out.get(key); - - if (c == null) - c = new Collector(); - - c.collect(t); - out.put(key, c); - } - } - return out; - } - - @Override - public boolean hasNext() - { - if (m_it == null) - m_it = m_tuples.iterator(); - return m_it.hasNext(); - } - - @Override - public Tuple next() - { - return m_it.next(); - } - - @Override - public void remove() - { - m_it.remove(); - } - - @Override - public String toString() - { - return m_tuples.toString(); - } - - @Override - public void rewind() - { - m_it = null; - } + private List> m_tuples = new LinkedList>(); + private Iterator> m_it = null; + + /** + * Return the Collector's contents as a list of tuples + * @return The list of tuples + */ + public List> toList() + { + return m_tuples; + } + + /** + * Add a collection of tuples to the Collector + * @param list A collection of {@link Tuple} + */ + public void addAll(Collection> list) + { + synchronized (this) { + m_tuples.addAll(list); + } + } + + /** + * Add a new tuple to the Collector in a synchronized mode + * @param t The {@link Tuple} to add + */ + public void collect(Tuple t) + { + synchronized (this) { + m_tuples.add(t); + } + } + + /** + * Returns a new Collector whose content is made of all tuples with + * given key + * @param key The key to find + * @return A new {@link Collector} + */ + public Collector subCollector(K key) + { + Collector c = new Collector(); + synchronized (this) { + for (Tuple t : m_tuples) + { + if (t.getKey().equals(key)) + c.m_tuples.add(t); + } + } + return c; + + } + + public int count() + { + synchronized (this) { + return m_tuples.size(); + } + } + + /** + * Partitions the set of tuples into new collectors, each containing all + * tuples with the same key + * @return A map from keys to Collectors + */ + public Map> subCollectors() + { + Map> out = new HashMap>(); + + synchronized (this) { + for ( Tuple t : m_tuples) + { + K key = t.getKey(); + Collector c = out.get(key); + + if (c == null) + c = new Collector(); + + c.collect(t); + out.put(key, c); + } + } + return out; + } + + @Override + public boolean hasNext() + { + if (m_it == null) + m_it = m_tuples.iterator(); + return m_it.hasNext(); + } + + @Override + public Tuple next() + { + return m_it.next(); + } + + @Override + public void remove() + { + m_it.remove(); + } + + @Override + public String toString() + { + return m_tuples.toString(); + } + + @Override + public void rewind() + { + m_it = null; + } } diff --git a/Source/MapReduce/src/ca/uqac/dim/mapreduce/InCollector.java b/Source/MapReduce/src/ca/uqac/dim/mapreduce/InCollector.java index 1cd2974..2c1fcbb 100644 --- a/Source/MapReduce/src/ca/uqac/dim/mapreduce/InCollector.java +++ b/Source/MapReduce/src/ca/uqac/dim/mapreduce/InCollector.java @@ -22,8 +22,8 @@ /** * Data source used as the input of the map and reduce * phases. An InCollector can be used to enumerate data - * tuples using the {@link hasNext} and {@link next} - * methods, like an {@link Iterator}. + * tuples using the {@link Collector#hasNext()} and + * {@link Collector#next()} methods, like an {@link Iterator}. * * @author Sylvain Hallé * @version 1.0 diff --git a/Source/MapReduce/src/ca/uqac/dim/mapreduce/Mapper.java b/Source/MapReduce/src/ca/uqac/dim/mapreduce/Mapper.java index b53d168..9435ab6 100644 --- a/Source/MapReduce/src/ca/uqac/dim/mapreduce/Mapper.java +++ b/Source/MapReduce/src/ca/uqac/dim/mapreduce/Mapper.java @@ -28,7 +28,7 @@ public interface Mapper { /** * Map function - * @param out A {@link OutCollector} that will be used to write output tuples + * @param c A {@link OutCollector} that will be used to write output tuples * @param t A {@link Tuple} to process */ public void map(OutCollector c, Tuple t); diff --git a/Source/MapReduce/src/ca/uqac/dim/mapreduce/OutCollector.java b/Source/MapReduce/src/ca/uqac/dim/mapreduce/OutCollector.java index f32814b..67b8172 100644 --- a/Source/MapReduce/src/ca/uqac/dim/mapreduce/OutCollector.java +++ b/Source/MapReduce/src/ca/uqac/dim/mapreduce/OutCollector.java @@ -20,7 +20,8 @@ /** * Data source used as the output of the map and reduce * phases. An OutCollector can be used to - * store data tuples using the {@link collect} method. + * store data tuples using the {@link OutCollector#collect(Tuple)} + * method. * * @author Sylvain Hallé * @version 1.1 diff --git a/Source/MapReduce/src/ca/uqac/dim/mapreduce/ParallelWorkflow.java b/Source/MapReduce/src/ca/uqac/dim/mapreduce/ParallelWorkflow.java index 5b0098b..388c106 100644 --- a/Source/MapReduce/src/ca/uqac/dim/mapreduce/ParallelWorkflow.java +++ b/Source/MapReduce/src/ca/uqac/dim/mapreduce/ParallelWorkflow.java @@ -34,173 +34,173 @@ */ public class ParallelWorkflow implements Workflow { - private Mapper m_mapper = null; - private Reducer m_reducer = null; - private InCollector m_source = null; - private ResourceManager m_managerMapper = null; - private ResourceManager m_managerReducer = null; - - /** - * The total number of tuples that the mappers will produce. - * This is only necessary for gathering statistics, and is not - * required in the MapReduce processing per se. - */ - protected long m_totalTuples = 0; - - /** - * The maximum number of tuples that a single reducer will process. - * This is used as a measure of the "linearity" of the MapReduce job: - * assuming all reducers worked on a separate thread, this value is - * proportional to the time the longest reducer would take. - * Intuitively, the ratio maxTuples/totalTuples indicates the "speedup" - * incurred by the use of parallel reducers compared to a strictly - * linear processing. - */ - protected long m_maxTuples = 0; - - public ParallelWorkflow(Mapper m, Reducer r, InCollector c) - { - super(); - setMapper(m); - setReducer(r); - setSource(c); - - ResourceManager rmM = new ResourceManager(); - setManagerMapper(rmM); - - ResourceManager rmR = new ResourceManager(); - setManagerReducer(rmR); - } - /** - * Create an instance of ParallelWorkflow. - * @param m The {@link Mapper} to use in the map phase - * @param r The {@link Reducer} to use in the reduce phase - * @param c The {@link InCollector} to use as the input source of tuples - * @param rmM The {@link ResourceManager} to use as a manager of threads for the Map phase - * @param rmR The {@link ResourceManager} to use as a manager of threads for the Reduce phase - */ - public ParallelWorkflow(Mapper m, Reducer r, InCollector c, ResourceManager rmM, ResourceManager rmR ) - { - super(); - setMapper(m); - setReducer(r); - setSource(c); - setManagerMapper(rmM); - setManagerReducer(rmR); - } - - public void setMapper(Mapper m) - { - m_mapper = m; - } - - public void setReducer(Reducer r) - { - m_reducer = r; - } - - public void setSource(InCollector c) - { - m_source = c; - } - - public void setManagerMapper(ResourceManager rmM) + private Mapper m_mapper = null; + private Reducer m_reducer = null; + private InCollector m_source = null; + private ResourceManager m_managerMapper = null; + private ResourceManager m_managerReducer = null; + + /** + * The total number of tuples that the mappers will produce. + * This is only necessary for gathering statistics, and is not + * required in the MapReduce processing per se. + */ + protected long m_totalTuples = 0; + + /** + * The maximum number of tuples that a single reducer will process. + * This is used as a measure of the "linearity" of the MapReduce job: + * assuming all reducers worked on a separate thread, this value is + * proportional to the time the longest reducer would take. + * Intuitively, the ratio maxTuples/totalTuples indicates the "speedup" + * incurred by the use of parallel reducers compared to a strictly + * linear processing. + */ + protected long m_maxTuples = 0; + + public ParallelWorkflow(Mapper m, Reducer r, InCollector c) + { + super(); + setMapper(m); + setReducer(r); + setSource(c); + + ResourceManager rmM = new ResourceManager(); + setManagerMapper(rmM); + + ResourceManager rmR = new ResourceManager(); + setManagerReducer(rmR); + } + /** + * Create an instance of ParallelWorkflow. + * @param m The {@link Mapper} to use in the map phase + * @param r The {@link Reducer} to use in the reduce phase + * @param c The {@link InCollector} to use as the input source of tuples + * @param rmM The {@link ResourceManager} to use as a manager of threads for the Map phase + * @param rmR The {@link ResourceManager} to use as a manager of threads for the Reduce phase + */ + public ParallelWorkflow(Mapper m, Reducer r, InCollector c, ResourceManager rmM, ResourceManager rmR ) + { + super(); + setMapper(m); + setReducer(r); + setSource(c); + setManagerMapper(rmM); + setManagerReducer(rmR); + } + + public void setMapper(Mapper m) + { + m_mapper = m; + } + + public void setReducer(Reducer r) + { + m_reducer = r; + } + + public void setSource(InCollector c) + { + m_source = c; + } + + public void setManagerMapper(ResourceManager rmM) + { + m_managerMapper = rmM; + } + + public void setManagerReducer(ResourceManager rmR) + { + m_managerReducer = rmR; + } + + public InCollector run() + { + if (m_mapper == null || m_reducer == null || m_source == null) + return null; + assert m_mapper != null; + assert m_reducer != null; + assert m_source != null; + Collector temp_coll = new Collector(); + m_source.rewind(); + + long timeBeforeMap = new Date().getTime(); + + while (m_source.hasNext()) { - m_managerMapper = rmM; + Tuple t = m_source.next(); + + //Thread for all mappers + Thread MThread = m_managerMapper.getThread(t, temp_coll, m_mapper); + MThread.start(); } - - public void setManagerReducer(ResourceManager rmR) + //WAIT all mapper theads to finish + m_managerMapper.waitThreads(); + + long timeAfterMap = new Date().getTime(); + long timePhaseMap = timeAfterMap - timeBeforeMap; + System.out.println("--------------------------------------------------------"); + System.out.println("------------------Time of every Phases------------------"); + System.out.println("--------------------------------------------------------"); + System.out.println(" Map : " + timePhaseMap + " Milliseconds"); + + Map> shuffle = temp_coll.subCollectors(); + Set keys = shuffle.keySet(); + Collector out = new Collector(); + + long timeBeforeReduce = new Date().getTime(); + for (K key : keys) { - m_managerReducer = rmR; + Collector s_source = shuffle.get(key); + int num_tuples = s_source.count(); + m_totalTuples += num_tuples; + m_maxTuples = Math.max(m_maxTuples, num_tuples); + + //Tread for all Reducers + Thread RThread = m_managerReducer.getThread(out, key, s_source, m_reducer); + RThread.start(); } - public InCollector run() - { - if (m_mapper == null || m_reducer == null || m_source == null) - return null; - assert m_mapper != null; - assert m_reducer != null; - assert m_source != null; - Collector temp_coll = new Collector(); - m_source.rewind(); - - long timeBeforeMap = new Date().getTime(); - - while (m_source.hasNext()) - { - Tuple t = m_source.next(); - - //Thread for all mappers - Thread MThread = m_managerMapper.getThread(t, temp_coll, m_mapper); - MThread.start(); - } - //WAIT all mapper theads to finish - m_managerMapper.waitThreads(); - - long timeAfterMap = new Date().getTime(); - long timePhaseMap = timeAfterMap - timeBeforeMap; - System.out.println("--------------------------------------------------------"); - System.out.println("------------------Time of every Phases------------------"); - System.out.println("--------------------------------------------------------"); - System.out.println(" Map : " + timePhaseMap + " Milliseconds"); - - Map> shuffle = temp_coll.subCollectors(); - Set keys = shuffle.keySet(); - Collector out = new Collector(); - - long timeBeforeReduce = new Date().getTime(); - for (K key : keys) - { - Collector s_source = shuffle.get(key); - int num_tuples = s_source.count(); - m_totalTuples += num_tuples; - m_maxTuples = Math.max(m_maxTuples, num_tuples); - - //Tread for all Reducers - Thread RThread = m_managerReducer.getThread(out, key, s_source, m_reducer); - RThread.start(); - } - - //WAIT all reduce theads to finish - m_managerReducer.waitThreads(); - - long timeAfterReduce = new Date().getTime(); - long timePhaseReduce = timeAfterReduce - timeBeforeReduce; - long timePhaseTotal = timePhaseMap + timePhaseReduce; - double timeSeconds = (double) timePhaseTotal/1000; - int timeMinutes = (int) (timePhaseTotal/1000)/60; - double timeSecMins = ( (double)timePhaseTotal/1000) - ( (double)timeMinutes * 60); - - System.out.println(" Reduce : " + timePhaseReduce + " Milliseconds"); - System.out.println("--------------------------------------------------------"); - System.out.println(" Total : " + timePhaseTotal + " Milliseconds"); - System.out.println(" Total Seconds : " + timeSeconds); - System.out.println(" Total Minutes : " + timeMinutes + "." + timeSecMins); - System.out.println("--------------------------------------------------------"); - return out; - } - - /** - * Returns the maximum number of tuples processed by a single - * reducer in the process. This method returns 0 if the MapReduce - * job hasn't executed yet (i.e. you should call it only after - * a call to {@link run}). - * @return - */ - public long getMaxTuples() - { - return m_maxTuples; - } - - /** - * Returns the total number of tuples processed by all reducers. - * This method returns 0 if the MapReduce - * job hasn't executed yet (i.e. you should call it only after - * a call to {@link run}). - * @return - */ - public long getTotalTuples() - { - return m_totalTuples; - } + //WAIT all reduce theads to finish + m_managerReducer.waitThreads(); + + long timeAfterReduce = new Date().getTime(); + long timePhaseReduce = timeAfterReduce - timeBeforeReduce; + long timePhaseTotal = timePhaseMap + timePhaseReduce; + double timeSeconds = (double) timePhaseTotal/1000; + int timeMinutes = (int) (timePhaseTotal/1000)/60; + double timeSecMins = ( (double)timePhaseTotal/1000) - ( (double)timeMinutes * 60); + + System.out.println(" Reduce : " + timePhaseReduce + " Milliseconds"); + System.out.println("--------------------------------------------------------"); + System.out.println(" Total : " + timePhaseTotal + " Milliseconds"); + System.out.println(" Total Seconds : " + timeSeconds); + System.out.println(" Total Minutes : " + timeMinutes + "." + timeSecMins); + System.out.println("--------------------------------------------------------"); + return out; + } + + /** + * Returns the maximum number of tuples processed by a single + * reducer in the process. This method returns 0 if the MapReduce + * job hasn't executed yet (i.e. you should call it only after + * a call to {@link ParallelWorkflow#run()}). + * @return The maximum number of tuples + */ + public long getMaxTuples() + { + return m_maxTuples; + } + + /** + * Returns the total number of tuples processed by all reducers. + * This method returns 0 if the MapReduce + * job hasn't executed yet (i.e. you should call it only after + * a call to {@link ParallelWorkflow#run()}). + * @return The total number of tuples + */ + public long getTotalTuples() + { + return m_totalTuples; + } } \ No newline at end of file diff --git a/Source/MapReduce/src/ca/uqac/dim/mapreduce/ResourceManager.java b/Source/MapReduce/src/ca/uqac/dim/mapreduce/ResourceManager.java index c54b5e1..0c861c9 100644 --- a/Source/MapReduce/src/ca/uqac/dim/mapreduce/ResourceManager.java +++ b/Source/MapReduce/src/ca/uqac/dim/mapreduce/ResourceManager.java @@ -36,169 +36,171 @@ * */ public class ResourceManager { - - /** - * The number of threads by default of the manager. This value is use when - * the builder is call without a integer parameter. - */ - private int threadDefault = 100; - - /** - * The maximum number of threads that can create the manager. The value is - * set by the builder. - */ - private int threadMax = 0; - - /** - * The list that contains all of the created threads of the manager. - * It's important to know that the manager is the only one to have acces to - * the list. - */ - private List listThread = new LinkedList(); - - /** - * Set the maximum of threads of the manager - * @param max Value of the maximum - */ - private void setThreadMax(int max) - { - this.threadMax = max; - } - - /** - * Returns the maximum number of threads of the manager can create - * @return - */ - public int getThreadMax() - { - return this.threadMax; - } - - /** - * Create an instance of ResourceManager with the default value of - * threads maximum - */ - public ResourceManager() - { - setThreadMax(threadDefault); - } - - /** - * Create an instance of ResourceManager - * @param maxThread Value of the threads maximum given by the user - */ - public ResourceManager(int maxThread) + + /** + * The number of threads by default of the manager. This value is use when + * the builder is call without a integer parameter. + */ + private int threadDefault = 100; + + /** + * The maximum number of threads that can create the manager. The value is + * set by the builder. + */ + private int threadMax = 0; + + /** + * The list that contains all of the created threads of the manager. + * It's important to know that the manager is the only one to have access to + * the list. + */ + private List listThread = new LinkedList(); + + /** + * Set the maximum of threads of the manager + * @param max Value of the maximum + */ + private void setThreadMax(int max) + { + this.threadMax = max; + } + + /** + * Returns the maximum number of threads of the manager can create + * @return The number of threads + */ + public int getThreadMax() + { + return this.threadMax; + } + + /** + * Create an instance of ResourceManager with the default value of + * threads maximum + */ + public ResourceManager() + { + setThreadMax(threadDefault); + } + + /** + * Create an instance of ResourceManager + * @param maxThread Value of the threads maximum given by the user + */ + public ResourceManager(int maxThread) + { + setThreadMax(maxThread); + } + + /** + * Creates a mapper thread + * @param t The tuple to analyze + * @param temp_coll The collector of all results + * @param m_mapper The {@link Mapper} to use in the map phase + * @return A thread + */ + public Thread getThread(Tuple t, Collector temp_coll, Mapper m_mapper) + { + int i=0; + boolean create = false; + MapThread MThread = null; + Thread ThreadTemp = null; + + if(listThread.size() < threadMax) { - setThreadMax(maxThread); + MThread = new MapThread(t,temp_coll,m_mapper); + listThread.add(MThread); } - - /** - * Function that create a mapper thread and return it to the calling line - * @param t The tuple to analyse - * @param temp_coll The collector of all results - * @param m_mapper The {@link Mapper} to use in the map phase - * @return - */ - public Thread getThread(Tuple t, Collector temp_coll, Mapper m_mapper) + else { - int i=0; - boolean create = false; - MapThread MThread = null; - Thread ThreadTemp = null; - - if(listThread.size() < threadMax) + while(create != true) + { + while(i < listThread.size()) { + ThreadTemp = listThread.get(i); + + if(!ThreadTemp.isAlive()) + { + listThread.remove(i); MThread = new MapThread(t,temp_coll,m_mapper); listThread.add(MThread); + create = true; + i = listThread.size(); + } + else + { + i++; + } } - else - { - while(create !=true) - { - while(i< listThread.size()) - { - ThreadTemp = listThread.get(i); - - if(!ThreadTemp.isAlive()) - { - listThread.remove(i); - MThread = new MapThread(t,temp_coll,m_mapper); - listThread.add(MThread); - create = true; - i = listThread.size(); - } - else - i++; - } - i=0; - } - } - return MThread; + i = 0; + } + } + return MThread; + } + + /** + * Creates a reducer thread + * @param out The collector of the final results + * @param key The key to reduce + * @param s_source The collector of all results of the mapper phase + * @param m_reducer The {@link Reducer} to use in the reduce phase + * @return A thread + */ + public Thread getThread(Collector out, K key, Collector s_source, Reducer m_reducer) + { + int i=0; + boolean create = false; + ReduceThread RThread = null; + Thread ThreadTemp = null; + + if(listThread.size() < threadMax) + { + RThread = new ReduceThread(out, key, s_source, m_reducer); + listThread.add(RThread); } - - /** - * Function that create a reducer thread and return it to the calling line - * @param out The collector of the final results - * @param key The key to reduce - * @param s_source The collector of all results of the mapper phase - * @param m_reducer The {@link Reducer} to use in the reduce phase - * @return - */ - public Thread getThread(Collector out, K key, Collector s_source, Reducer m_reducer) + else { - int i=0; - boolean create = false; - ReduceThread RThread = null; - Thread ThreadTemp = null; - - if(listThread.size() < threadMax) - { - RThread = new ReduceThread(out, key, s_source, m_reducer); - listThread.add(RThread); - } - else + while(create !=true) + { + while(i< listThread.size()) { - while(create !=true) - { - while(i< listThread.size()) - { - ThreadTemp = listThread.get(i); + ThreadTemp = listThread.get(i); - if(!ThreadTemp.isAlive()) - { - listThread.remove(i); - RThread = new ReduceThread(out, key, s_source, m_reducer); - listThread.add(RThread); - create = true; - i = listThread.size(); - } - else - i++; - } - i=0; - } + if(!ThreadTemp.isAlive()) + { + listThread.remove(i); + RThread = new ReduceThread(out, key, s_source, m_reducer); + listThread.add(RThread); + create = true; + i = listThread.size(); + } + else + i++; } - return RThread; + i=0; + } } - - /** - * Function who check if all threads of the list are dead and clear the list - */ - public void waitThreads() + return RThread; + } + + /** + * Function who check if all threads of the list are dead and clear the list + */ + public void waitThreads() + { + int i=0; + Thread ThreadTemp = null; + while(i < listThread.size()) { - int i=0; - Thread ThreadTemp = null; - while(i < listThread.size()) - { - ThreadTemp = listThread.get(i); - - if(ThreadTemp.isAlive()) - i = 0; - else - i++; - } - listThread.clear(); + ThreadTemp = listThread.get(i); + + if(ThreadTemp.isAlive()) + i = 0; + else + i++; } + listThread.clear(); + } } /** @@ -208,34 +210,34 @@ public void waitThreads() */ class MapThread extends Thread { - /** - * Informations needed to be transferred to the mapper - * For more information, see function getThread - */ - Tuple tThread = new Tuple(); - Collector Thread_Temp_col = new Collector(); - Mapper Thread_m_mapper = null; - - /** - * Create an instance of MapThread - * @param t The tuple to analyse - * @param temp_coll The collector of all results - * @param m_mapper The {@link Mapper} to use in the map phase - */ - MapThread(Tuple t, Collector temp_coll, Mapper m_mapper) - { - this.tThread = t; - this.Thread_Temp_col = temp_coll; - this.Thread_m_mapper = m_mapper; - } - - /** - * Function who start the execution of the mapper - */ - public void run() - { - Thread_m_mapper.map(Thread_Temp_col, tThread); - } + /** + * Informations needed to be transferred to the mapper + * For more information, see function getThread + */ + Tuple tThread = new Tuple(); + Collector Thread_Temp_col = new Collector(); + Mapper Thread_m_mapper = null; + + /** + * Create an instance of MapThread + * @param t The tuple to analyse + * @param temp_coll The collector of all results + * @param m_mapper The {@link Mapper} to use in the map phase + */ + MapThread(Tuple t, Collector temp_coll, Mapper m_mapper) + { + this.tThread = t; + this.Thread_Temp_col = temp_coll; + this.Thread_m_mapper = m_mapper; + } + + /** + * Function who start the execution of the mapper + */ + public void run() + { + Thread_m_mapper.map(Thread_Temp_col, tThread); + } } /** @@ -245,35 +247,35 @@ public void run() */ class ReduceThread extends Thread { - /** - * Informations needed to be transferred to the reducer - * For more information, see function getThread - */ - Collector outThread = new Collector(); - K Thread_key = null; - Collector Thread_s_source = new Collector(); - Reducer Thread_m_reducer = null; - - /** - * Create an instance of ReduceThread - * @param out The collector of the final results - * @param key The key to reduce - * @param s_source The collector of all results of the mapper phase - * @param m_reducer The {@link Reducer} to use in the reduce phase - */ - ReduceThread(Collector out, K key, Collector s_source, Reducer m_reducer) - { - this.outThread = out; - this.Thread_key = key; - this.Thread_s_source = s_source; - this.Thread_m_reducer = m_reducer; - } - - /** - * Function who start the execution of the reducer - */ - public void run() - { - Thread_m_reducer.reduce(outThread, Thread_key, Thread_s_source); - } + /** + * Informations needed to be transferred to the reducer + * For more information, see function getThread + */ + Collector outThread = new Collector(); + K Thread_key = null; + Collector Thread_s_source = new Collector(); + Reducer Thread_m_reducer = null; + + /** + * Create an instance of ReduceThread + * @param out The collector of the final results + * @param key The key to reduce + * @param s_source The collector of all results of the mapper phase + * @param m_reducer The {@link Reducer} to use in the reduce phase + */ + ReduceThread(Collector out, K key, Collector s_source, Reducer m_reducer) + { + this.outThread = out; + this.Thread_key = key; + this.Thread_s_source = s_source; + this.Thread_m_reducer = m_reducer; + } + + /** + * Function who start the execution of the reducer + */ + public void run() + { + Thread_m_reducer.reduce(outThread, Thread_key, Thread_s_source); + } } \ No newline at end of file diff --git a/Source/MapReduce/src/ca/uqac/dim/mapreduce/SequentialWorkflow.java b/Source/MapReduce/src/ca/uqac/dim/mapreduce/SequentialWorkflow.java index 0a6990c..ab40c2f 100644 --- a/Source/MapReduce/src/ca/uqac/dim/mapreduce/SequentialWorkflow.java +++ b/Source/MapReduce/src/ca/uqac/dim/mapreduce/SequentialWorkflow.java @@ -117,8 +117,8 @@ public InCollector run() * Returns the maximum number of tuples processed by a single * reducer in the process. This method returns 0 if the MapReduce * job hasn't executed yet (i.e. you should call it only after - * a call to {@link run}). - * @return + * a call to {@link SequentialWorkflow#run()}). + * @return The number of tuples */ public long getMaxTuples() { @@ -129,8 +129,8 @@ public long getMaxTuples() * Returns the total number of tuples processed by all reducers. * This method returns 0 if the MapReduce * job hasn't executed yet (i.e. you should call it only after - * a call to {@link run}). - * @return + * a call to {@link SequentialWorkflow#run()}). + * @return The number of tuples */ public long getTotalTuples() { diff --git a/Source/MapReduce/src/ca/uqac/dim/mapreduce/Workflow.java b/Source/MapReduce/src/ca/uqac/dim/mapreduce/Workflow.java index 6e265bf..25d44fe 100644 --- a/Source/MapReduce/src/ca/uqac/dim/mapreduce/Workflow.java +++ b/Source/MapReduce/src/ca/uqac/dim/mapreduce/Workflow.java @@ -28,7 +28,7 @@ public interface Workflow /** * Start a map-reduce job and output the results as a single * Collector containing all output tuples. - * @return + * @return An InputCollector containing all output tuples */ public InCollector run(); } diff --git a/build.xml b/build.xml index c44ae7c..8de805c 100644 --- a/build.xml +++ b/build.xml @@ -25,24 +25,26 @@ includeantruntime="false" /> - - MrSim Documentation]]> - Copyright © 2011-2015 Sylvain Hallé. All Rights Reserved.]]> - - + + + MrSim Documentation]]> + Copyright © 2011-2015 Sylvain Hallé. All Rights Reserved.]]> + + + - + diff --git a/mrsim.jar b/mrsim.jar index 124c58d35ee0199e1613c98d56f4a7db8f366855..54081d8dd93edfbf9fed3b18366d22920dfacf97 100644 GIT binary patch literal 113812 zcmaHSb9^Q1(sj%o+s?$cZQIF?ZDTSMPCT*AiEZ1qZDWE-GGETcd(L~`@7(?C{;#@s zcXd6hYOSYANfsOe4g>@S1O#4#Ndn|AKUfe55P5MmVR~r=3C8zP5D=w*nZkg;eV95z zcF@y&m{Wb6=pX0*n92()NK1&Tsxin*+{urR$;r|)%pl0p(@c&})u}Mevu+Skj0Ki9y39xI>4zq~T#PH?ZJ5gOX}O^G1tP^4fr zw?&ya*-pXTFSpj8;Jqq7DaCeXFh&-hJMo;UY{GecN<4NRysH3<@Xp+cOk~`*{mNgL zwAMPh_bA=m*tu8X_f~Q7iUw22$m{i0he*g`b5a}drL4lNAATsho*U=W76Y=a<#};g z^!axJapVR{>*{_Xg148w$;eevmKUm|e0LOxQ+YZOHGvL`JXCeCh56bx_!D8?B@2Y2 zl$Y5`+gX_hU2e%vpI)WU{UkOu+#(D3ti!Fwzrt#)A_qBf&h%2P1Zcr6*bt%$6IV4! zec=%+a&tw0pto3F13j6!R^-Y|e;PeE1bbVZ8%9d7;e3Nv!+^FnMoT+#`kbX#taj*j zzz*@VOVt)EvBQg&+q)N6)s4A2zr@BI8Q~mNi-R@6kF4b!p(#OPb^%pui7DGq+`O-y zhKDV=-j7nJn>dgzzS}v5a;qqZ3iZC-+h7PR9dm!7TNtsAFAeO_6FA)zcFuq`2X<(z 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