org.apache.hadoop.mapreduce.lib.input.MultipleInputs Java Examples

The following examples show how to use org.apache.hadoop.mapreduce.lib.input.MultipleInputs. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may check out the related API usage on the sidebar.
Example #1
Source File: PostCommentHierarchy.java    From hadoop-map-reduce-patterns with Apache License 2.0 8 votes vote down vote up
@Override
public int run(String[] args) throws Exception {
	Configuration conf = new Configuration();
	Job job = new Job(conf, "PostCommentHeirarchy");
	job.setJarByClass(PostCommentHierarchy.class);

	MultipleInputs.addInputPath(job, new Path(args[0]),
			TextInputFormat.class, PostMapper.class);
	MultipleInputs.addInputPath(job, new Path(args[1]),
			TextInputFormat.class, CommentMapper.class);

	job.setReducerClass(PostCommentHierarchyReducer.class);

	job.setOutputFormatClass(TextOutputFormat.class);
	TextOutputFormat.setOutputPath(job, new Path(args[2]));

	job.setOutputKeyClass(Text.class);
	job.setOutputValueClass(Text.class);

	return job.waitForCompletion(true) ? 0 : 2;
}
 
Example #2
Source File: ReduceSideJoin.java    From hadoop-map-reduce-patterns with Apache License 2.0 5 votes vote down vote up
@Override
public int run(String[] args) throws Exception {
	Configuration conf = new Configuration();
	GenericOptionsParser parser = new GenericOptionsParser(conf, args);
	String[] otherArgs = parser.getRemainingArgs();
	if (otherArgs.length != 4) {
		printUsage();
	}
	Job job = new Job(conf, "ReduceSideJoin");
	job.setJarByClass(ReduceSideJoin.class);

	// Use MultipleInputs to set which input uses what mapper
	// This will keep parsing of each data set separate from a logical
	// standpoint
	// The first two elements of the args array are the two inputs
	MultipleInputs.addInputPath(job, new Path(args[0]),
			TextInputFormat.class, UserJoinMapper.class);
	MultipleInputs.addInputPath(job, new Path(args[1]),
			TextInputFormat.class, CommentJoinMapper.class);
	job.getConfiguration().set("join.type", args[2]);

	job.setReducerClass(UserJoinReducer.class);

	job.setOutputFormatClass(TextOutputFormat.class);
	TextOutputFormat.setOutputPath(job, new Path(args[3]));

	job.setOutputKeyClass(Text.class);
	job.setOutputValueClass(Text.class);

	return job.waitForCompletion(true) ? 0 : 2;
}
 
Example #3
Source File: ReduceSideJoinBloomFilter.java    From hadoop-map-reduce-patterns with Apache License 2.0 5 votes vote down vote up
@Override
public int run(String[] args) throws Exception {
	Configuration conf = new Configuration();
	GenericOptionsParser parser = new GenericOptionsParser(conf, args);
	String[] otherArgs = parser.getRemainingArgs();
	if (otherArgs.length != 4) {
		printUsage();
	}
	Job job = new Job(conf, "ReduceSideJoinBloomFilter");
	job.setJarByClass(ReduceSideJoinBloomFilter.class);

	// Use MultipleInputs to set which input uses what mapper
	// This will keep parsing of each data set separate from a logical
	// standpoint
	// The first two elements of the args array are the two inputs
	MultipleInputs.addInputPath(job, new Path(args[0]),
			TextInputFormat.class, UserJoinMapper.class);
	MultipleInputs.addInputPath(job, new Path(args[1]),
			TextInputFormat.class, CommentJoinMapperWithBloom.class);
	job.getConfiguration().set("join.type", args[2]);

	job.setReducerClass(UserJoinReducer.class);

	job.setOutputFormatClass(TextOutputFormat.class);
	TextOutputFormat.setOutputPath(job, new Path(args[3]));

	job.setOutputKeyClass(Text.class);
	job.setOutputValueClass(Text.class);

	return job.waitForCompletion(true) ? 0 : 2;
}
 
Example #4
Source File: MapOperation.java    From incubator-retired-mrql with Apache License 2.0 5 votes vote down vote up
/** The cMap physical operator
 * @param map_fnc       mapper function
 * @param acc_fnc       optional accumulator function
 * @param zero          optional the zero value for the accumulator
 * @param source        input data source
 * @param stop_counter  optional counter used in repeat operation
 * @return a new data source that contains the result
 */
public final static DataSet cMap ( Tree map_fnc,         // mapper function
                                   Tree acc_fnc,         // optional accumulator function
                                   Tree zero,            // optional the zero value for the accumulator
                                   DataSet source,       // input data source
                                   String stop_counter ) // optional counter used in repeat operation
                            throws Exception {
    conf = MapReduceEvaluator.clear_configuration(conf);
    String newpath = new_path(conf);
    conf.set("mrql.mapper",map_fnc.toString());
    conf.set("mrql.counter",stop_counter);
    if (zero != null) {
        conf.set("mrql.accumulator",acc_fnc.toString());
        conf.set("mrql.zero",zero.toString());
    } else conf.set("mrql.zero","");
    setupSplits(source,conf);
    Job job = new Job(conf,newpath);
    distribute_compiled_arguments(job.getConfiguration());
    job.setJarByClass(MapReducePlan.class);
    job.setOutputKeyClass(MRContainer.class);
    job.setOutputValueClass(MRContainer.class);
    job.setOutputFormatClass(SequenceFileOutputFormat.class);
    for (DataSource p: source.source)
        MultipleInputs.addInputPath(job,new Path(p.path),(Class<? extends MapReduceMRQLFileInputFormat>)p.inputFormat,cMapMapper.class);
    FileOutputFormat.setOutputPath(job,new Path(newpath));
    job.setNumReduceTasks(0);
    job.waitForCompletion(true);
    long c = (stop_counter.equals("-")) ? 0
             : job.getCounters().findCounter("mrql",stop_counter).getValue();
    return new DataSet(new BinaryDataSource(newpath,conf),c,outputRecords(job));
}
 
Example #5
Source File: ReplicatedUserJoin.java    From hadoop-map-reduce-patterns with Apache License 2.0 5 votes vote down vote up
@Override
public int run(String[] args) throws Exception {
	Configuration conf = new Configuration();
	GenericOptionsParser parser = new GenericOptionsParser(conf, args);
	String[] otherArgs = parser.getRemainingArgs();
	if (otherArgs.length != 4) {
		printUsage();
	}
	Job job = new Job(conf, "ReduceSideJoin");
	job.setJarByClass(ReplicatedUserJoin.class);

	// Use MultipleInputs to set which input uses what mapper
	// This will keep parsing of each data set separate from a logical
	// standpoint
	// The first two elements of the args array are the two inputs
	MultipleInputs.addInputPath(job, new Path(args[0]),
			TextInputFormat.class, UserJoinMapper.class);
	MultipleInputs.addInputPath(job, new Path(args[1]),
			TextInputFormat.class, CommentJoinMapper.class);
	job.getConfiguration().set("join.type", args[2]);

	job.setReducerClass(UserJoinReducer.class);

	job.setOutputFormatClass(TextOutputFormat.class);
	TextOutputFormat.setOutputPath(job, new Path(args[3]));

	job.setOutputKeyClass(Text.class);
	job.setOutputValueClass(Text.class);

	return job.waitForCompletion(true) ? 0 : 2;
}
 
Example #6
Source File: JoinSelectStatsUtil.java    From rya with Apache License 2.0 5 votes vote down vote up
public static void initJoinMRJob(Job job, String prospectsPath, String spoPath, Class<? extends Mapper<CompositeType,TripleCard,?,?>> mapperClass,
    String outPath, String auths) throws AccumuloSecurityException {

  MultipleInputs.addInputPath(job, new Path(prospectsPath), SequenceFileInputFormat.class, mapperClass);
  MultipleInputs.addInputPath(job, new Path(spoPath), SequenceFileInputFormat.class, mapperClass);
  job.setMapOutputKeyClass(CompositeType.class);
  job.setMapOutputValueClass(TripleCard.class);

  SequenceFileOutputFormat.setOutputPath(job, new Path(outPath));
  job.setOutputFormatClass(SequenceFileOutputFormat.class);
  job.setOutputKeyClass(TripleEntry.class);
  job.setOutputValueClass(CardList.class);

}
 
Example #7
Source File: JoinSelectStatisticsTest.java    From rya with Apache License 2.0 5 votes vote down vote up
@Override
public int run(String[] args) throws Exception {

    Configuration conf = getConf();
    String outpath = conf.get(OUTPUTPATH);
    
    Job job = new Job(conf, this.getClass().getSimpleName() + "_" + System.currentTimeMillis());
    job.setJarByClass(this.getClass());
    conf.setBoolean(MRJobConfig.MAPREDUCE_JOB_USER_CLASSPATH_FIRST, true);
    
    MultipleInputs.addInputPath(job, new Path(PROSPECTSOUT.getAbsolutePath()), 
            SequenceFileInputFormat.class, JoinSelectAggregateMapper.class);
    MultipleInputs.addInputPath(job,new Path(SPOOUT.getAbsolutePath()) , 
            SequenceFileInputFormat.class, JoinSelectAggregateMapper.class);
    job.setMapOutputKeyClass(CompositeType.class);
    job.setMapOutputValueClass(TripleCard.class);

    tempDir = new File(File.createTempFile(outpath, "txt").getParentFile(), System.currentTimeMillis() + "");
    SequenceFileOutputFormat.setOutputPath(job, new Path(tempDir.getAbsolutePath()));
    job.setOutputFormatClass(SequenceFileOutputFormat.class);
    job.setOutputKeyClass(TripleEntry.class);
    job.setOutputValueClass(CardList.class);


    job.setSortComparatorClass(JoinSelectSortComparator.class);
    job.setGroupingComparatorClass(JoinSelectGroupComparator.class);
    job.setPartitionerClass(JoinSelectPartitioner.class);
    job.setReducerClass(JoinReducer.class);
    job.setNumReduceTasks(32);
    job.waitForCompletion(true);
    
    return job.isSuccessful() ? 0 : 1;          
}
 
Example #8
Source File: AbstractReasoningTool.java    From rya with Apache License 2.0 5 votes vote down vote up
/**
 * Set up the MapReduce job to use Accumulo as an input.
 * @param tableMapper Mapper class to use
 */
protected void configureAccumuloInput(Class<? extends Mapper<Key,Value,?,?>> tableMapper)
        throws AccumuloSecurityException {
    MRReasoningUtils.configureAccumuloInput(job);
    MultipleInputs.addInputPath(job, new Path("/tmp/input"),
        AccumuloInputFormat.class, tableMapper);
}
 
Example #9
Source File: AbstractReasoningTool.java    From rya with Apache License 2.0 5 votes vote down vote up
/**
 * Set up the MapReduce job to use an RDF file as an input.
 * @param rdfMapper class to use
 */
protected void configureRdfInput(Path inputPath,
        Class<? extends Mapper<LongWritable, RyaStatementWritable, ?, ?>> rdfMapper) {
    Configuration conf = job.getConfiguration();
    String format = conf.get(MRUtils.FORMAT_PROP, RDFFormat.RDFXML.getName());
    conf.set(MRUtils.FORMAT_PROP, format);
    MultipleInputs.addInputPath(job, inputPath,
        RdfFileInputFormat.class, rdfMapper);
}
 
Example #10
Source File: StreamingRepartitionJoin.java    From hiped2 with Apache License 2.0 5 votes vote down vote up
/**
 * The MapReduce driver - setup and launch the job.
 *
 * @param args the command-line arguments
 * @return the process exit code
 * @throws Exception if something goes wrong
 */
public int run(final String[] args) throws Exception {

  Cli cli = Cli.builder().setArgs(args).addOptions(Options.values()).build();
  int result = cli.runCmd();

  if (result != 0) {
    return result;
  }

  Path usersPath = new Path(cli.getArgValueAsString(Options.USERS));
  Path userLogsPath = new Path(cli.getArgValueAsString(Options.USER_LOGS));
  Path outputPath = new Path(cli.getArgValueAsString(Options.OUTPUT));

  Configuration conf = super.getConf();

  Job job = new Job(conf);
  job.setJarByClass(StreamingRepartitionJoin.class);

  MultipleInputs.addInputPath(job, usersPath, TextInputFormat.class, UserMap.class);
  MultipleInputs.addInputPath(job, userLogsPath, TextInputFormat.class, UserLogMap.class);

  ShuffleUtils.configBuilder()
      .useNewApi()
      .setSortIndices(KeyFields.USER, KeyFields.DATASET)
      .setPartitionerIndices(KeyFields.USER)
      .setGroupIndices(KeyFields.USER)
      .configure(job.getConfiguration());

  job.setReducerClass(Reduce.class);

  job.setMapOutputKeyClass(Tuple.class);
  job.setMapOutputValueClass(Tuple.class);

  FileOutputFormat.setOutputPath(job, outputPath);

  return job.waitForCompletion(true) ? 0 : 1;
}
 
Example #11
Source File: IndexerJobDriver.java    From incubator-retired-blur with Apache License 2.0 5 votes vote down vote up
private boolean runMrOnly(TableDescriptor descriptor, List<Path> inprogressPathList, String table, Path fileCache,
    Path outputPath, int reducerMultipler) throws IOException, ClassNotFoundException, InterruptedException {
  Job job = Job.getInstance(getConf(), "Blur Row Updater for table [" + table + "]");
  Path tablePath = new Path(descriptor.getTableUri());
  BlurInputFormat.setLocalCachePath(job, fileCache);
  BlurInputFormat.addTable(job, descriptor, MRUPDATE_SNAPSHOT);
  MultipleInputs.addInputPath(job, tablePath, BlurInputFormat.class, ExistingDataMapper.class);

  for (Path p : inprogressPathList) {
    FileInputFormat.addInputPath(job, p);
    MultipleInputs.addInputPath(job, p, SequenceFileInputFormat.class, NewDataMapper.class);
  }

  BlurOutputFormat.setOutputPath(job, outputPath);
  BlurOutputFormat.setupJob(job, descriptor);

  job.setReducerClass(UpdateReducer.class);
  job.setMapOutputKeyClass(IndexKey.class);
  job.setMapOutputValueClass(IndexValue.class);
  job.setPartitionerClass(IndexKeyPartitioner.class);
  job.setGroupingComparatorClass(IndexKeyWritableComparator.class);

  BlurOutputFormat.setReducerMultiplier(job, reducerMultipler);

  boolean success = job.waitForCompletion(true);
  Counters counters = job.getCounters();
  LOG.info("Counters [" + counters + "]");
  return success;
}
 
Example #12
Source File: BloomJoin.java    From hiped2 with Apache License 2.0 5 votes vote down vote up
/**
 * The MapReduce driver - setup and launch the job.
 *
 * @param args the command-line arguments
 * @return the process exit code
 * @throws Exception if something goes wrong
 */
public int run(final String[] args) throws Exception {

  Cli cli = Cli.builder().setArgs(args).addOptions(Options.values()).build();
  int result = cli.runCmd();

  if (result != 0) {
    return result;
  }

  Path usersPath = new Path(cli.getArgValueAsString(Options.USERS));
  Path userLogsPath = new Path(cli.getArgValueAsString(Options.USER_LOGS));
  Path bloomPath = new Path(cli.getArgValueAsString(Options.BLOOM_FILE));
  Path outputPath = new Path(cli.getArgValueAsString(Options.OUTPUT));

  Configuration conf = super.getConf();

  Job job = new Job(conf);

  job.setJarByClass(BloomJoin.class);
  MultipleInputs.addInputPath(job, usersPath, TextInputFormat.class, UserMap.class);
  MultipleInputs.addInputPath(job, userLogsPath, TextInputFormat.class, UserLogMap.class);

  job.setMapOutputKeyClass(Text.class);
  job.setMapOutputValueClass(Tuple.class);

  job.setReducerClass(Reduce.class);

  job.addCacheFile(bloomPath.toUri());
  job.getConfiguration().set(AbstractFilterMap.DISTCACHE_FILENAME_CONFIG, bloomPath.getName());

  FileInputFormat.setInputPaths(job, userLogsPath);
  FileOutputFormat.setOutputPath(job, outputPath);

  return job.waitForCompletion(true) ? 0 : 1;
}
 
Example #13
Source File: IndexerJobDriver.java    From incubator-retired-blur with Apache License 2.0 5 votes vote down vote up
private boolean runMrWithLookup(String uuid, TableDescriptor descriptor, List<Path> inprogressPathList, String table,
    Path fileCache, Path outputPath, int reducerMultipler, Path tmpPath, TableStats tableStats, String snapshot)
    throws ClassNotFoundException, IOException, InterruptedException {
  PartitionedInputResult result = buildPartitionedInputData(uuid, tmpPath, descriptor, inprogressPathList, snapshot,
      fileCache);

  Job job = Job.getInstance(getConf(), "Blur Row Updater for table [" + table + "]");

  ExistingDataIndexLookupMapper.setSnapshot(job, MRUPDATE_SNAPSHOT);
  FileInputFormat.addInputPath(job, result._partitionedInputData);
  MultipleInputs.addInputPath(job, result._partitionedInputData, SequenceFileInputFormat.class,
      ExistingDataIndexLookupMapper.class);

  for (Path p : inprogressPathList) {
    FileInputFormat.addInputPath(job, p);
    MultipleInputs.addInputPath(job, p, SequenceFileInputFormat.class, NewDataMapper.class);
  }

  BlurOutputFormat.setOutputPath(job, outputPath);
  BlurOutputFormat.setupJob(job, descriptor);

  job.setReducerClass(UpdateReducer.class);
  job.setMapOutputKeyClass(IndexKey.class);
  job.setMapOutputValueClass(IndexValue.class);
  job.setPartitionerClass(IndexKeyPartitioner.class);
  job.setGroupingComparatorClass(IndexKeyWritableComparator.class);

  BlurOutputFormat.setReducerMultiplier(job, reducerMultipler);

  boolean success = job.waitForCompletion(true);
  Counters counters = job.getCounters();
  LOG.info("Counters [" + counters + "]");
  return success;
}
 
Example #14
Source File: MultInput2.java    From MapReduce-Demo with MIT License 4 votes vote down vote up
public static void main(String[] args) throws Exception {		
	//1.设置HDFS配置信息
	String namenode_ip = "192.168.17.10";
	String hdfs = "hdfs://" + namenode_ip + ":9000";			
	Configuration conf = new Configuration();
	conf.set("fs.defaultFS", hdfs);
	conf.set("mapreduce.app-submission.cross-platform", "true");

	//2.设置MapReduce作业配置信息
	String jobName = "MultInput2";					//作业名称
	Job job = Job.getInstance(conf, jobName);
	job.setJarByClass(MultInput2.class);			//指定运行时作业类
	job.setJar("export\\MultInput2.jar");			//指定本地jar包
	
	//job.setMapperClass(MultInput2Mapper.class);	//无需指定Mapper类,而在MultipleInputs.addInputPath()方法中指定
	job.setMapOutputKeyClass(Text.class);			//设置Mapper输出Key类型
	job.setMapOutputValueClass(IntWritable.class);	//设置Mapper输出Value类型
	job.setReducerClass(MultInput2Reducer.class);	//指定Reducer类
	job.setOutputKeyClass(Text.class);				//设置Reduce输出Key类型
	job.setOutputValueClass(IntWritable.class); 	//设置Reduce输出Value类型
	
	//3.设置作业输入和输出路径	
	//方法五:MultipleInputs.addInputPath()
	MultipleInputs.addInputPath(job, new Path(hdfs+"/expr/multinput/data/txt1"), TextInputFormat.class, TxtFileMapper.class);
	MultipleInputs.addInputPath(job, new Path(hdfs+"/expr/multinput/data/csv"), TextInputFormat.class, CsvFileMapper.class);
	
	Path outPath = new Path(hdfs + "/expr/multinput/output3");		//输出目录
	FileOutputFormat.setOutputPath(job, outPath);
	FileSystem fs = FileSystem.get(conf);
	if(fs.exists(outPath)) {
		fs.delete(outPath, true);
	}
	
	//4.运行作业
	System.out.println("Job: " + jobName + " is running...");
	if(job.waitForCompletion(true)) {
		System.out.println("success!");
		System.exit(0);
	} else {
		System.out.println("failed!");
		System.exit(1);
	}
}
 
Example #15
Source File: Driver.java    From incubator-retired-blur with Apache License 2.0 4 votes vote down vote up
@Override
public int run(String[] args) throws Exception {
  int c = 0;
  if (args.length < 5) {
    System.err
        .println("Usage Driver <table> <mr inc working path> <output path> <zk connection> <reducer multipler> <extra config files...>");
    return 1;
  }
  String table = args[c++];
  String mrIncWorkingPathStr = args[c++];
  String outputPathStr = args[c++];
  String blurZkConnection = args[c++];
  int reducerMultipler = Integer.parseInt(args[c++]);
  for (; c < args.length; c++) {
    String externalConfigFileToAdd = args[c];
    getConf().addResource(new Path(externalConfigFileToAdd));
  }

  Path outputPath = new Path(outputPathStr);
  Path mrIncWorkingPath = new Path(mrIncWorkingPathStr);
  FileSystem fileSystem = mrIncWorkingPath.getFileSystem(getConf());

  Path newData = new Path(mrIncWorkingPath, NEW);
  Path inprogressData = new Path(mrIncWorkingPath, INPROGRESS);
  Path completeData = new Path(mrIncWorkingPath, COMPLETE);
  Path fileCache = new Path(mrIncWorkingPath, CACHE);

  fileSystem.mkdirs(newData);
  fileSystem.mkdirs(inprogressData);
  fileSystem.mkdirs(completeData);
  fileSystem.mkdirs(fileCache);

  List<Path> srcPathList = new ArrayList<Path>();
  for (FileStatus fileStatus : fileSystem.listStatus(newData)) {
    srcPathList.add(fileStatus.getPath());
  }
  if (srcPathList.isEmpty()) {
    return 0;
  }

  List<Path> inprogressPathList = new ArrayList<Path>();
  boolean success = false;
  Iface client = null;
  try {
    inprogressPathList = movePathList(fileSystem, inprogressData, srcPathList);

    Job job = Job.getInstance(getConf(), "Blur Row Updater for table [" + table + "]");
    client = BlurClient.getClientFromZooKeeperConnectionStr(blurZkConnection);
    waitForOtherSnapshotsToBeRemoved(client, table, MRUPDATE_SNAPSHOT);
    client.createSnapshot(table, MRUPDATE_SNAPSHOT);
    TableDescriptor descriptor = client.describe(table);
    Path tablePath = new Path(descriptor.getTableUri());

    BlurInputFormat.setLocalCachePath(job, fileCache);
    BlurInputFormat.addTable(job, descriptor, MRUPDATE_SNAPSHOT);
    MultipleInputs.addInputPath(job, tablePath, BlurInputFormat.class, MapperForExistingData.class);
    for (Path p : inprogressPathList) {
      FileInputFormat.addInputPath(job, p);
      MultipleInputs.addInputPath(job, p, SequenceFileInputFormat.class, MapperForNewData.class);
    }

    BlurOutputFormat.setOutputPath(job, outputPath);
    BlurOutputFormat.setupJob(job, descriptor);

    job.setReducerClass(UpdateReducer.class);
    job.setMapOutputKeyClass(IndexKey.class);
    job.setMapOutputValueClass(IndexValue.class);
    job.setPartitionerClass(IndexKeyPartitioner.class);
    job.setGroupingComparatorClass(IndexKeyWritableComparator.class);

    BlurOutputFormat.setReducerMultiplier(job, reducerMultipler);

    success = job.waitForCompletion(true);
    Counters counters = job.getCounters();
    LOG.info("Counters [" + counters + "]");

  } finally {
    if (success) {
      LOG.info("Indexing job succeeded!");
      movePathList(fileSystem, completeData, inprogressPathList);
    } else {
      LOG.error("Indexing job failed!");
      movePathList(fileSystem, newData, inprogressPathList);
    }
    if (client != null) {
      client.removeSnapshot(table, MRUPDATE_SNAPSHOT);
    }
  }

  if (success) {
    return 0;
  } else {
    return 1;
  }

}
 
Example #16
Source File: IndexerJobDriver.java    From incubator-retired-blur with Apache License 2.0 4 votes vote down vote up
private boolean runAutomatic(String uuid, TableDescriptor descriptor, List<Path> inprogressPathList, String table,
    Path fileCache, Path outputPath, int reducerMultipler, Path tmpPath, TableStats tableStats, String snapshot)
    throws ClassNotFoundException, IOException, InterruptedException {
  PartitionedInputResult result = buildPartitionedInputData(uuid, tmpPath, descriptor, inprogressPathList, snapshot,
      fileCache);

  Job job = Job.getInstance(getConf(), "Blur Row Updater for table [" + table + "]");

  InputSplitPruneUtil.setBlurLookupRowIdFromNewDataCounts(job, table, result._rowIdsFromNewData);
  InputSplitPruneUtil.setBlurLookupRowIdUpdateFromNewDataCounts(job, table, result._rowIdsToUpdateFromNewData);
  InputSplitPruneUtil.setBlurLookupRowIdFromIndexCounts(job, table, result._rowIdsFromIndex);
  InputSplitPruneUtil.setTable(job, table);

  BlurInputFormat.setLocalCachePath(job, fileCache);

  // Existing data - This adds the copy data files first open and stream
  // through all documents.
  {
    Path tablePath = new Path(descriptor.getTableUri());
    BlurInputFormat.addTable(job, descriptor, MRUPDATE_SNAPSHOT);
    MultipleInputs.addInputPath(job, tablePath, PrunedBlurInputFormat.class, ExistingDataMapper.class);
  }

  // Existing data - This adds the row id lookup
  {
    ExistingDataIndexLookupMapper.setSnapshot(job, MRUPDATE_SNAPSHOT);
    FileInputFormat.addInputPath(job, result._partitionedInputData);
    MultipleInputs.addInputPath(job, result._partitionedInputData, PrunedSequenceFileInputFormat.class,
        ExistingDataIndexLookupMapper.class);
  }

  // New Data
  for (Path p : inprogressPathList) {
    FileInputFormat.addInputPath(job, p);
    MultipleInputs.addInputPath(job, p, SequenceFileInputFormat.class, NewDataMapper.class);
  }

  BlurOutputFormat.setOutputPath(job, outputPath);
  BlurOutputFormat.setupJob(job, descriptor);

  job.setReducerClass(UpdateReducer.class);
  job.setMapOutputKeyClass(IndexKey.class);
  job.setMapOutputValueClass(IndexValue.class);
  job.setPartitionerClass(IndexKeyPartitioner.class);
  job.setGroupingComparatorClass(IndexKeyWritableComparator.class);

  BlurOutputFormat.setReducerMultiplier(job, reducerMultipler);

  boolean success = job.waitForCompletion(true);
  Counters counters = job.getCounters();
  LOG.info("Counters [" + counters + "]");
  return success;
}
 
Example #17
Source File: MapReduceOperation.java    From incubator-retired-mrql with Apache License 2.0 4 votes vote down vote up
/**
 * The MapReduce physical operator
 * @param map_fnc          the mapper function
 * @param combine_fnc      optional in-mapper combiner function
 * @param reduce_fnc       the reducer function
 * @param acc_fnc          optional accumulator function
 * @param zero             optional the zero value for the accumulator
 * @param source           the input data source
 * @param num_reduces      number of reducers
 * @param stop_counter     optional counter used in repeat operation
 * @param orderp           does the result need to be ordered?
 * @return a new data source that contains the result
 */
public final static DataSet mapReduce ( Tree map_fnc,         // mapper function
                                        Tree combine_fnc,     // optional in-mapper combiner function
                                        Tree reduce_fnc,      // reducer function
                                        Tree acc_fnc,         // optional accumulator function
                                        Tree zero,            // optional the zero value for the accumulator
                                        DataSet source,       // input data source
                                        int num_reduces,      // number of reducers
                                        String stop_counter,  // optional counter used in repeat operation
                                        boolean orderp )      // does the result need to be ordered?
                            throws Exception {
    conf = MapReduceEvaluator.clear_configuration(conf);
    String newpath = new_path(conf);
    conf.set("mrql.mapper",map_fnc.toString());
    if (combine_fnc != null)
        conf.set("mrql.combiner",combine_fnc.toString());
    conf.set("mrql.reducer",reduce_fnc.toString());
    if (zero != null) {   // will use in-mapper combiner
        conf.set("mrql.accumulator",acc_fnc.toString());
        conf.set("mrql.zero",zero.toString());
    } else conf.set("mrql.zero","");
    conf.set("mrql.counter",stop_counter);
    setupSplits(source,conf);
    Job job = new Job(conf,newpath);
    distribute_compiled_arguments(job.getConfiguration());
    job.setJarByClass(MapReducePlan.class);
    job.setOutputKeyClass(MRContainer.class);
    job.setOutputValueClass(MRContainer.class);
    job.setPartitionerClass(MRContainerPartitioner.class);
    job.setSortComparatorClass(MRContainerKeyComparator.class);
    job.setGroupingComparatorClass(MRContainerKeyComparator.class);
    job.setOutputFormatClass(SequenceFileOutputFormat.class);
    for (DataSource p: source.source)
        MultipleInputs.addInputPath(job,new Path(p.path),(Class<? extends MapReduceMRQLFileInputFormat>)p.inputFormat,MRMapper.class);
    FileOutputFormat.setOutputPath(job,new Path(newpath));
    job.setReducerClass(MRReducer.class);
    if (Config.trace && PlanGeneration.streamed_MapReduce_reducer(reduce_fnc))
        System.out.println("Streamed MapReduce reducer");
    if (num_reduces > 0)
        job.setNumReduceTasks(num_reduces);
    job.waitForCompletion(true);
    long c = (stop_counter.equals("-")) ? 0
             : job.getCounters().findCounter("mrql",stop_counter).getValue();
    DataSource s = new BinaryDataSource(newpath,conf);
    s.to_be_merged = orderp;
    return new DataSet(s,c,outputRecords(job));
}
 
Example #18
Source File: Phase4RemoveDuplicatesUsingReduceSideJoins.java    From dkpro-c4corpus with Apache License 2.0 4 votes vote down vote up
@Override
public int run(String[] args)
        throws Exception
{
    Job job = Job.getInstance(getConf());

    job.setJarByClass(Phase4RemoveDuplicatesUsingReduceSideJoins.class);
    job.setJobName(Phase4RemoveDuplicatesUsingReduceSideJoins.class.getName());

    // paths
    // text files of ids to be deleted
    String textFilePath = args[0];
    // corpus with *.warc.gz
    String commaSeparatedInputFiles = args[1];
    // output
    String outputPath = args[2];

    //second input the look up text file
    MultipleInputs.addInputPath(job, new Path(textFilePath), TextInputFormat.class,
            JoinTextMapper.class);
    //first input the data set (check comma separated availability)
    MultipleInputs.addInputPath(job, new Path(commaSeparatedInputFiles), WARCInputFormat.class,
            JoinWARCMapper.class);

    job.setPartitionerClass(SourceJoiningKeyPartitioner.class);
    job.setGroupingComparatorClass(SourceJoiningGroupingComparator.class);

    job.setMapOutputKeyClass(CompositeKey.class);
    job.setMapOutputValueClass(WARCWritable.class);

    job.setReducerClass(JoinReducer.class);

    job.setOutputFormatClass(WARCOutputFormat.class);
    job.setOutputKeyClass(NullWritable.class);
    job.setOutputValueClass(WARCWritable.class);
    FileOutputFormat.setOutputPath(job, new Path(outputPath));
    FileOutputFormat.setCompressOutput(job, true);
    FileOutputFormat.setOutputCompressorClass(job, GzipCodec.class);

    return job.waitForCompletion(true) ? 0 : 1;
}
 
Example #19
Source File: ParseLogJob_End.java    From 163-bigdate-note with GNU General Public License v3.0 4 votes vote down vote up
public int run(String[] args) throws Exception {
        //创建job
        Configuration config = getConf();
        //添加自定义配置
        config.addResource("mr.xml");
        Job job = Job.getInstance(config);
        //通过job设置一些参数
        //通过job设置一些参数
        job.setJarByClass(ParseLogJob_End.class);
        job.setJobName("parselog");
        job.setMapperClass(LogMapper.class);
        job.setReducerClass(LogReducer.class);
        job.setMapOutputKeyClass(TextLongWritable.class);
        job.setGroupingComparatorClass(TextLongGroupComparator.class);
        job.setPartitionerClass(TextLongPartition.class);
        job.setMapOutputValueClass(LogWritable.class);
        job.setOutputValueClass(Text.class);

        //设置CombineFileInputFormat
        job.setInputFormatClass(CombineTextInputFormat.class);

        //添加分布式缓存
        job.addCacheFile(new URI(config.get("ip.file.path")));

        //设置OutputFormat
//        job.setOutputFormatClass(LogOutputFormat.class);


        //设置压缩类型
//        FileOutputFormat.setCompressOutput(job, true);
//        FileOutputFormat.setOutputCompressorClass(job, LzopCodec.class);

        FileSystem fs = FileSystem.get(config);
        //添加输入和输出数据
        FileStatus[] fileStatuses = fs.listStatus(new Path(args[0]));
        for (int i = 0; i < fileStatuses.length; i++) {
            MultipleInputs.addInputPath(job, fileStatuses[i].getPath(), TextInputFormat.class, LogMapper.class);
            String inputPath = fileStatuses[i].getPath().toString();
            String dir_name = inputPath.substring(inputPath.lastIndexOf('/')+1);
            System.out.println(dir_name);
        }

        Path outputPath = new Path(args[1]);
        FileOutputFormat.setOutputPath(job, outputPath);
        if (fs.exists(outputPath)) {
            fs.delete(outputPath, true);
        }
        //运行程序
        if (!job.waitForCompletion(true)) {
            throw new RuntimeException(job.getJobName() + "failed!");
        }

        return 0;
    }
 
Example #20
Source File: MultiInOutput.java    From MapReduce-Demo with MIT License 4 votes vote down vote up
public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
	// 1.设置HDFS配置信息
	String namenode_ip = "192.168.17.10";
	String hdfs = "hdfs://" + namenode_ip + ":9000";
	Configuration conf = new Configuration();
	conf.set("fs.defaultFS", hdfs);
	conf.set("mapreduce.app-submission.cross-platform", "true");

	// 2.设置MapReduce作业配置信息
	String jobName = "MultInputOutput"; // 作业名称
	Job job = Job.getInstance(conf, jobName);
	job.setJarByClass(MultiInOutput.class); // 指定运行时作业类
	job.setJar("export\\MultiInOutput.jar"); // 指定本地jar包
	job.setMapOutputKeyClass(Text.class); // 设置Mapper输出Key类型
	job.setMapOutputValueClass(IntWritable.class); // 设置Mapper输出Value类型
	job.setReducerClass(MultOutputReducer.class); // 指定Reducer类
	// job.setOutputKeyClass(Text.class); //设置Reduce输出Key类型
	// job.setOutputValueClass(IntWritable.class); //设置Reduce输出Value类型
	
	// 3.指定作业多输入路径,及Map所使用的类
	MultipleInputs.addInputPath(job, new Path(hdfs+"/expr/multiinoutput/data/txt"), TextInputFormat.class, TxtFileMapper.class);
	MultipleInputs.addInputPath(job, new Path(hdfs+"/expr/multiinoutput/data/csv"), TextInputFormat.class, CsvFileMapper.class);
	
	// 定义多文件输出的文件名、输出格式、Reduce输出键类型,值类型
	MultipleOutputs.addNamedOutput(job, "f2015", TextOutputFormat.class, Text.class, IntWritable.class);
	MultipleOutputs.addNamedOutput(job, "f2016", SequenceFileOutputFormat.class, Text.class, IntWritable.class);
	MultipleOutputs.addNamedOutput(job, "f2017", MapFileOutputFormat.class, Text.class, IntWritable.class);

	// 设置作业输出路径
	String outputDir = "/expr/multiinoutput/output"; // 实验输出目录
	Path outPath = new Path(hdfs + outputDir);
	FileOutputFormat.setOutputPath(job, outPath);
	FileSystem fs = FileSystem.get(conf);
	if (fs.exists(outPath)) {
		fs.delete(outPath, true);
	}

	// 4.运行作业
	System.out.println("Job: " + jobName + " is running...");
	if (job.waitForCompletion(true)) {
		System.out.println("success!");
		System.exit(0);
	} else {
		System.out.println("failed!");
		System.exit(1);
	}
}
 
Example #21
Source File: SimpleRepartitionJoin.java    From hiped2 with Apache License 2.0 3 votes vote down vote up
/**
 * The MapReduce driver - setup and launch the job.
 *
 * @param args the command-line arguments
 * @return the process exit code
 * @throws Exception if something goes wrong
 */
public int run(final String[] args) throws Exception {

  Cli cli = Cli.builder().setArgs(args).addOptions(Options.values()).build();
  int result = cli.runCmd();

  if (result != 0) {
    return result;
  }

  Path usersPath = new Path(cli.getArgValueAsString(Options.USERS));
  Path userLogsPath = new Path(cli.getArgValueAsString(Options.USER_LOGS));
  Path outputPath = new Path(cli.getArgValueAsString(Options.OUTPUT));

  Configuration conf = super.getConf();

  Job job = new Job(conf);
  job.setJarByClass(SimpleRepartitionJoin.class);

  MultipleInputs.addInputPath(job, usersPath, TextInputFormat.class, UserMap.class);
  MultipleInputs.addInputPath(job, userLogsPath, TextInputFormat.class, UserLogMap.class);

  job.setReducerClass(Reduce.class);

  job.setMapOutputKeyClass(Text.class);
  job.setMapOutputValueClass(Tuple.class);

  FileOutputFormat.setOutputPath(job, outputPath);

  return job.waitForCompletion(true) ? 0 : 1;
}
 
Example #22
Source File: SimpleRepartitionMapReduce2.java    From hiped2 with Apache License 2.0 3 votes vote down vote up
/**
 * The MapReduce driver - setup and launch the job.
 *
 * @param args the command-line arguments
 * @return the process exit code
 * @throws Exception if something goes wrong
 */
public int run(final String[] args) throws Exception {

  Cli cli = Cli.builder().setArgs(args).addOptions(Options.values()).build();
  int result = cli.runCmd();

  if (result != 0) {
    return result;
  }

  Path usersPath = new Path(cli.getArgValueAsString(Options.USERS));
  Path userLogsPath = new Path(cli.getArgValueAsString(Options.USER_LOGS));
  Path outputPath = new Path(cli.getArgValueAsString(Options.OUTPUT));

  Configuration conf = super.getConf();

  Job job = new Job(conf);
  job.setJarByClass(SimpleRepartitionMapReduce2.class);

  MultipleInputs.addInputPath(job, usersPath, TextInputFormat.class, UserMap.class);
  MultipleInputs.addInputPath(job, userLogsPath, TextInputFormat.class, UserLogMap.class);

  job.setReducerClass(Reduce.class);

  job.setMapOutputKeyClass(Tuple.class);
  job.setMapOutputValueClass(Tuple.class);

  FileOutputFormat.setOutputPath(job, outputPath);

  return job.waitForCompletion(true) ? 0 : 1;
}