Java Code Examples for org.apache.hadoop.io.IntWritable

@Override
public void collect(Configuration conf, BaseDimension key, BaseStatsValueWritable value,
    PreparedStatement preparedStatement, IDimensionConverter converter)
    throws SQLException, IOException {
  StatsUserDimension statsUser = (StatsUserDimension)key;
  MapWritableValue mapWritableValue = (MapWritableValue)value;
  IntWritable activeUserValue = (IntWritable) mapWritableValue.getValue().get(new IntWritable(-1));

  int i = 0;
  preparedStatement.setInt(++i, converter.getDimensionIdByValue(statsUser.getStatsCommon().getPlatform()));
  preparedStatement.setInt(++i, converter.getDimensionIdByValue(statsUser.getStatsCommon().getDate()));
  preparedStatement.setInt(++i, activeUserValue.get());
  preparedStatement.setString(++i, conf.get(GlobalConstants.RUNNING_DATE_PARAMS));
  preparedStatement.setInt(++i, activeUserValue.get());
  preparedStatement.addBatch();
}
 

/** Queries the job tracker for a set of outputs ready to be copied
 * @param fromEventId the first event ID we want to start from, this is
 * modified by the call to this method
 * @param jobClient the job tracker
 * @return a set of locations to copy outputs from
 * @throws IOException
 */  
private List<TaskCompletionEvent> queryJobTracker(IntWritable fromEventId,
                                                  JobID jobId,
                                                  InterTrackerProtocol jobClient)
  throws IOException {

  TaskCompletionEvent t[] = jobClient.getTaskCompletionEvents(
                                                              jobId,
                                                              fromEventId.get(),
                                                              probe_sample_size);
  //we are interested in map task completion events only. So store
  //only those
  List <TaskCompletionEvent> recentMapEvents = 
    new ArrayList<TaskCompletionEvent>();
  for (int i = 0; i < t.length; i++) {
    if (t[i].isMap) {
      recentMapEvents.add(t[i]);
    }
  }
  fromEventId.set(fromEventId.get() + t.length);
  return recentMapEvents;
}
 

@Test
public void testConfigurableMapper() throws Exception {
	final ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();

	JobConf conf = new JobConf();
	conf.set("my.filterPrefix", "Hello");

	DataSet<Tuple2<IntWritable, Text>> ds = HadoopTestData.getKVPairDataSet(env);
	DataSet<Tuple2<IntWritable, Text>> hellos = ds.
			flatMap(new HadoopMapFunction<IntWritable, Text, IntWritable, Text>(new ConfigurableMapper(), conf));

	String resultPath = tempFolder.newFile().toURI().toString();

	hellos.writeAsText(resultPath, FileSystem.WriteMode.OVERWRITE);
	env.execute();

	String expected = "(2,Hello)\n" +
			"(3,Hello world)\n" +
			"(4,Hello world, how are you?)\n";

	compareResultsByLinesInMemory(expected, resultPath);
}
 

@Override
public void collect(Configuration conf, BaseDimension key, BaseStatsValueWritable value, PreparedStatement pstmt, IDimensionConverter converter) throws SQLException, IOException {
 // 进行强制后获取对应的值
    StatsUserDimension statsUser = (StatsUserDimension) key;
    IntWritable activeUserValue = (IntWritable) ((MapWritableValue) value).getValue().get(new IntWritable(-1));

    // 进行参数设置
    int i = 0;
    pstmt.setInt(++i, converter.getDimensionIdByValue(statsUser.getStatsCommon().getPlatform()));
    pstmt.setInt(++i, converter.getDimensionIdByValue(statsUser.getStatsCommon().getDate()));
    pstmt.setInt(++i, converter.getDimensionIdByValue(statsUser.getBrowser()));
    pstmt.setInt(++i, activeUserValue.get());
    pstmt.setString(++i, conf.get(GlobalConstants.RUNNING_DATE_PARAMES));
    pstmt.setInt(++i, activeUserValue.get());

    // 添加到batch中
    pstmt.addBatch();
}
 

public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {  
    // TODO Auto-generated method stub  
    Configuration conf1 = new Configuration();  

    Job job1 = new Job(conf1, "wiki  job one");  
    job1.setOutputFormatClass(SequenceFileOutputFormat.class);  
    job1.setInputFormatClass(SequenceFileInputFormat.class);  
    job1.setNumReduceTasks(1);  
    job1.setJarByClass(Step32.class);  
    job1.setMapperClass(WikiMapper32.class);  
    job1.setMapOutputKeyClass(IntWritable.class);  
    job1.setMapOutputValueClass(VectorOrPrefWritable.class);  
  
    job1.setReducerClass(WiKiReducer32.class);  
    job1.setOutputKeyClass(IntWritable.class);  
    job1.setOutputValueClass(VectorOrPrefWritable.class);  
      
    // the WiKiDriver's out put is this one's input  
    SequenceFileInputFormat.addInputPath(job1, new Path(INPUT_PATH));  
    SequenceFileOutputFormat.setOutputPath(job1, new Path(OUTPUT_PATH));     
    if(!job1.waitForCompletion(true)){  
        System.exit(1); // run error then exit  
    }  
}
 

public void run() throws Exception{
	long startTime = System.currentTimeMillis();
	Configuration conf = new Configuration();
	conf.set(TableOutputFormat.OUTPUT_TABLE, Constants.hbase_user_item_pref_table);
	Job job = Job.getInstance(conf, "hbasewriter"+System.currentTimeMillis());
	job.setJarByClass(UpdateCFJob.class);
	job.setMapperClass(TokenizerMapper.class);
	job.setReducerClass(HBaseWriteReducer.class);
	job.setMapOutputKeyClass(IntWritable.class);  
	job.setMapOutputValueClass(Text.class);
	job.setOutputFormatClass(TableOutputFormat.class);
	FileInputFormat.addInputPath(job, new Path(input));
	long endTime = System.currentTimeMillis();
	boolean isFinish = job.waitForCompletion(true);
	if(isFinish){
		logger.info("UpdateCFJob job ["+job.getJobName()+"] run finish.it costs"+ (endTime - startTime) / 1000 +"s.");
	} else {
		logger.error("UpdateCFJob job ["+job.getJobName()+"] run failed.");
	}
}
 

public static Job createJob() throws IOException {
  final Configuration conf = new Configuration();
  final Job baseJob = Job.getInstance(conf);
  baseJob.setOutputKeyClass(Text.class);
  baseJob.setOutputValueClass(IntWritable.class);
  baseJob.setMapperClass(NewMapTokenizer.class);
  baseJob.setCombinerClass(NewSummer.class);
  baseJob.setReducerClass(NewSummer.class);
  baseJob.setNumReduceTasks(1);
  baseJob.getConfiguration().setInt(JobContext.IO_SORT_MB, 1);
  baseJob.getConfiguration().set(JobContext.MAP_SORT_SPILL_PERCENT, "0.50");
  baseJob.getConfiguration().setInt(JobContext.MAP_COMBINE_MIN_SPILLS, 3);
  org.apache.hadoop.mapreduce.lib.input.FileInputFormat.setMinInputSplitSize(
      baseJob, Long.MAX_VALUE);
  return baseJob;
}
 

@Test
public void TestIntParse() throws Exception {
	Configuration config = new Configuration();
	Text value = new Text();

	AbstractSerDe jserde = new EsriJsonSerDe();
	Properties proptab = new Properties();
	proptab.setProperty(HiveShims.serdeConstants.LIST_COLUMNS, "num");
	proptab.setProperty(HiveShims.serdeConstants.LIST_COLUMN_TYPES, "int");
	jserde.initialize(config, proptab);
       StructObjectInspector rowOI = (StructObjectInspector)jserde.getObjectInspector();

       //value.set("{\"attributes\":{\"num\":7},\"geometry\":null}");
       value.set("{\"attributes\":{\"num\":7}}");
	Object row = jserde.deserialize(value);
	StructField f0 = rowOI.getStructFieldRef("num");
	Object fieldData = rowOI.getStructFieldData(row, f0);
	Assert.assertEquals(7, ((IntWritable)fieldData).get());
       value.set("{\"attributes\":{\"num\":9}}");
       row = jserde.deserialize(value);
	f0 = rowOI.getStructFieldRef("num");
	fieldData = rowOI.getStructFieldData(row, f0);
	Assert.assertEquals(9, ((IntWritable)fieldData).get());
}
 

@Test
//Test appendValue with DataInputBuffer
public void testAppendValueWithDataInputBuffer() throws IOException {
  List<KVPair> data = KVDataGen.generateTestData(false, rnd.nextInt(100));
  IFile.Writer writer = new IFile.Writer(defaultConf, localFs, outputPath,
      Text.class, IntWritable.class, codec, null, null);

  final DataInputBuffer previousKey = new DataInputBuffer();
  DataInputBuffer key = new DataInputBuffer();
  DataInputBuffer value = new DataInputBuffer();
  for (KVPair kvp : data) {
    populateData(kvp, key, value);

    if ((previousKey != null && BufferUtils.compare(key, previousKey) == 0)) {
      writer.appendValue(value);
    } else {
      writer.append(key, value);
    }
    previousKey.reset(k.getData(), 0, k.getLength());
  }

  writer.close();

  readAndVerifyData(writer.getRawLength(), writer.getCompressedLength(), data, codec);
}
 

private DAG createDAG(int numGenTasks, int totalSourceDataSize, int numFetcherTasks) {
  int bytesPerSource = totalSourceDataSize / numGenTasks;
  LOG.info("DataPerSourceTask(bytes)=" + bytesPerSource);
  ByteBuffer payload = ByteBuffer.allocate(4);
  payload.putInt(0, bytesPerSource);

  Vertex broadcastVertex = Vertex.create("DataGen",
      ProcessorDescriptor.create(InputGenProcessor.class.getName())
          .setUserPayload(UserPayload.create(payload)), numGenTasks);
  Vertex fetchVertex = Vertex.create("FetchVertex",
      ProcessorDescriptor.create(InputFetchProcessor.class.getName()), numFetcherTasks);
  UnorderedKVEdgeConfig edgeConf = UnorderedKVEdgeConfig.newBuilder(NullWritable.class
  .getName(), IntWritable.class.getName()).setCompression(false, null, null).build();

  DAG dag = DAG.create("BroadcastLoadGen");
  dag.addVertex(broadcastVertex).addVertex(fetchVertex).addEdge(
      Edge.create(broadcastVertex, fetchVertex, edgeConf.createDefaultBroadcastEdgeProperty()));
  return dag;
}
 

@Test(timeout = 5000)
// Test empty file case
public void testEmptyFileBackedInMemIFileWriter() throws IOException {
  List<KVPair> data = new ArrayList<>();
  TezTaskOutputFiles
      tezTaskOutput = new TezTaskOutputFiles(defaultConf, "uniqueId", 1);

  IFile.FileBackedInMemIFileWriter writer = new IFile.FileBackedInMemIFileWriter(defaultConf, localFs, tezTaskOutput,
      Text.class, IntWritable.class, codec, null, null,
      100);

  // empty ifile
  writer.close();

  byte[] bytes = new byte[(int) writer.getRawLength()];

  IFile.Reader.readToMemory(bytes,
      new ByteArrayInputStream(ByteString.copyFrom(writer.getData()).toByteArray()),
      (int) writer.getCompressedLength(), codec, false, -1);

  readUsingInMemoryReader(bytes, data);
}
 

@Override
public void collect(Configuration conf, BaseDimension key, BaseStatsValueWritable value, 
		PreparedStatement pstmt, IDimensionConverter converter) 
				throws SQLException, IOException {
    StatsUserDimension statsUserDimension = (StatsUserDimension) key;
    MapWritableValue mapWritableValue = (MapWritableValue) value;
    IntWritable newInstallUsers = (IntWritable) mapWritableValue.getValue().get(new IntWritable(-1));

    int i = 0;
    pstmt.setInt(++i, converter.getDimensionIdByValue(statsUserDimension.getStatsCommon().getPlatform()));
    pstmt.setInt(++i, converter.getDimensionIdByValue(statsUserDimension.getStatsCommon().getDate()));
    pstmt.setInt(++i, newInstallUsers.get());
    pstmt.setString(++i, conf.get(GlobalConstants.RUNNING_DATE_PARAMES));
    pstmt.setInt(++i, newInstallUsers.get());
    pstmt.addBatch();//往批处理放入数据
}
 

private List<TezMerger.Segment> createInMemorySegments(int segmentCount, int keysPerSegment)
    throws IOException {
  List<TezMerger.Segment> segmentList = Lists.newLinkedList();
  Random rnd = new Random();
  DataInputBuffer key = new DataInputBuffer();
  DataInputBuffer value = new DataInputBuffer();
  for (int i = 0; i < segmentCount; i++) {
    BoundedByteArrayOutputStream stream = new BoundedByteArrayOutputStream(10000);
    InMemoryWriter writer = new InMemoryWriter(stream);

    for (int j = 0; j < keysPerSegment; j++) {
      populateData(new IntWritable(rnd.nextInt()), new LongWritable(rnd.nextLong()), key, value);
      writer.append(key, value);
    }
    writer.close();
    InMemoryReader reader = new InMemoryReader(merger, null, stream.getBuffer(), 0, stream.getLimit());

    segmentList.add(new TezMerger.Segment(reader, null));
  }
  return segmentList;
}
 

public void testNestedIterable() throws Exception {
  Random r = new Random();
  Writable[] writs = {
    new BooleanWritable(r.nextBoolean()),
    new FloatWritable(r.nextFloat()),
    new FloatWritable(r.nextFloat()),
    new IntWritable(r.nextInt()),
    new LongWritable(r.nextLong()),
    new BytesWritable("dingo".getBytes()),
    new LongWritable(r.nextLong()),
    new IntWritable(r.nextInt()),
    new BytesWritable("yak".getBytes()),
    new IntWritable(r.nextInt())
  };
  TupleWritable sTuple = makeTuple(writs);
  assertTrue("Bad count", writs.length == verifIter(writs, sTuple, 0));
}
 

public void map(IntWritable key, IntWritable value,
        OutputCollector<IntWritable, NullWritable> output, Reporter reporter)
        throws IOException {

    //it is expected that every map processes mapSleepCount number of records. 
    try {
        reporter.setStatus("Sleeping... ("
                + (mapSleepDuration * (mapSleepCount - count)) + ") ms left");
        Thread.sleep(mapSleepDuration);
    } catch (InterruptedException ex) {
        throw (IOException) new IOException(
                "Interrupted while sleeping").initCause(ex);
    }
    ++count;
    // output reduceSleepCount * numReduce number of random values, so that
    // each reducer will get reduceSleepCount number of keys.
    int k = key.get();
    for (int i = 0; i < value.get(); ++i) {
        output.collect(new IntWritable(k + i), NullWritable.get());
    }
}
 

public DoubleWritable evaluate(Map<IntWritable, FloatWritable> map, List<IntWritable> keys) {
    double sum = 0d;
    for (IntWritable k : keys) {
        FloatWritable v = map.get(k);
        if (v != null) {
            sum += (double) v.get();
        }
    }
    return val(sum);
}
 

/** {@inheritDoc} */
@Override public void reduce(Text key, Iterable<IntWritable> values, Context ctx) throws IOException,
    InterruptedException {
    while (reduceLockFile.exists())
        Thread.sleep(50);

    int wordCnt = 0;

    for (IntWritable value : values)
        wordCnt += value.get();

    totalWordCnt.set(wordCnt);

    ctx.write(key, totalWordCnt);
}
 

@Override
public void reduce(Text key, Iterator<IntWritable> values,
    OutputCollector<Text, IntWritable> output, Reporter reporter)
    throws IOException {
  int sum = 0;
  while (values.hasNext()) {
    sum += values.next().get();
  }
  if (key.equals(OPEN_EXECTIME)){
    executionTime[OPEN] = sum;
  } else if (key.equals(NUMOPS_OPEN)){
    numOfOps[OPEN] = sum;
  } else if (key.equals(LIST_EXECTIME)){
    executionTime[LIST] = sum;
  } else if (key.equals(NUMOPS_LIST)){
    numOfOps[LIST] = sum;
  } else if (key.equals(DELETE_EXECTIME)){
    executionTime[DELETE] = sum;
  } else if (key.equals(NUMOPS_DELETE)){
    numOfOps[DELETE] = sum;
  } else if (key.equals(CREATE_EXECTIME)){
    executionTime[CREATE] = sum;
  } else if (key.equals(NUMOPS_CREATE)){
    numOfOps[CREATE] = sum;
  } else if (key.equals(WRITE_CLOSE_EXECTIME)){
    System.out.println(WRITE_CLOSE_EXECTIME + " = " + sum);
    executionTime[WRITE_CLOSE]= sum;
  } else if (key.equals(NUMOPS_WRITE_CLOSE)){
    numOfOps[WRITE_CLOSE] = sum;
  } else if (key.equals(TOTALOPS)){
    totalOps = sum;
  } else if (key.equals(ELAPSED_TIME)){
    totalTime = sum;
  }
  result.set(sum);
  output.collect(key, result);
  // System.out.println("Key = " + key + " Sum is =" + sum);
  // printResults(System.out);
}
 

@Override
public void collect(Configuration conf, BaseDimension key, BaseStatsValueWritable value, PreparedStatement pstmt, IDimensionConverter converter) throws SQLException, IOException {
    StatsUserDimension statsUser = (StatsUserDimension) key;
    MapWritableValue mapWritableValue = (MapWritableValue) value;

    int i = 0;
    // 设置参数
    switch (mapWritableValue.getKpi()) {
    case NEW_MEMBER: // 统计new member的kpi
        IntWritable v1 = (IntWritable) mapWritableValue.getValue().get(new IntWritable(-1));
        pstmt.setInt(++i, converter.getDimensionIdByValue(statsUser.getStatsCommon().getPlatform()));
        pstmt.setInt(++i, converter.getDimensionIdByValue(statsUser.getStatsCommon().getDate()));
        pstmt.setInt(++i, v1.get());
        pstmt.setString(++i, conf.get(GlobalConstants.RUNNING_DATE_PARAMES));
        pstmt.setInt(++i, v1.get());
        break;
    case BROWSER_NEW_MEMBER: // 统计browser new member 的kpi
        IntWritable v2 = (IntWritable) mapWritableValue.getValue().get(new IntWritable(-1));
        pstmt.setInt(++i, converter.getDimensionIdByValue(statsUser.getStatsCommon().getPlatform()));
        pstmt.setInt(++i, converter.getDimensionIdByValue(statsUser.getStatsCommon().getDate()));
        pstmt.setInt(++i, converter.getDimensionIdByValue(statsUser.getBrowser()));
        pstmt.setInt(++i, v2.get());
        pstmt.setString(++i, conf.get(GlobalConstants.RUNNING_DATE_PARAMES));
        pstmt.setInt(++i, v2.get());
        break;
    case INSERT_MEMBER_INFO: // 插入member info信息
        Text v3 = (Text) mapWritableValue.getValue().get(new IntWritable(-1));
        pstmt.setString(++i, v3.toString());
        pstmt.setString(++i, conf.get(GlobalConstants.RUNNING_DATE_PARAMES));
        pstmt.setString(++i, conf.get(GlobalConstants.RUNNING_DATE_PARAMES));
        pstmt.setString(++i, conf.get(GlobalConstants.RUNNING_DATE_PARAMES));
        break;
    default:
        throw new RuntimeException("不支持该种kpi输出操作" + mapWritableValue.getKpi());
    }

    // 添加batch
    pstmt.addBatch();
}
 

public void reduce(IntWritable key, Iterator<IntWritable> it,
                   OutputCollector<IntWritable, IntWritable> out,
                   Reporter reporter) throws IOException {
  while (it.hasNext()) {
    out.collect(it.next(), null);
  }
}
 

public int run(String[] args) throws Exception {

    GfxdDataSerializable.initTypes();

    JobConf conf = new JobConf(getConf());
    conf.setJobName("Busy Airport Count");

    Path outputPath = new Path(args[0]);
    String hdfsHomeDir = args[1];
    String tableName = args[2];

    outputPath.getFileSystem(conf).delete(outputPath, true);

    conf.set(RowInputFormat.HOME_DIR, hdfsHomeDir);
    conf.set(RowInputFormat.INPUT_TABLE, tableName);
    conf.setBoolean(RowInputFormat.CHECKPOINT_MODE, false);

    conf.setInputFormat(RowInputFormat.class);
    conf.setMapperClass(SampleMapper.class);
    conf.setMapOutputKeyClass(Text.class);
    conf.setMapOutputValueClass(IntWritable.class);

    conf.setReducerClass(SampleReducer.class);
    conf.setOutputKeyClass(Text.class);
    conf.setOutputValueClass(IntWritable.class);

    FileOutputFormat.setOutputPath(conf, outputPath);

    JobClient.runJob(conf);
    return 0;
  }
 

@Override
public IntWritable reduce(IntWritable k1, IntWritable k2) {
    if (k1 != null && k2 != null) {
        k1.set(k1.get() + k2.get());
    }

    return k1;
}
 

private void handleBrowserSessions(StatsUserDimension key, Iterable<TimeOutputValue> values,
      Context context)
      throws IOException, InterruptedException {
    //开始计算memberId的个数
    for (TimeOutputValue value : values) {
//        this.unique.add(value.getId());
      TimeChain chain = this.timeChainMap.get(value.getId());
      if (chain == null) {
        chain = new TimeChain(value.getTime())
        ;
        this.timeChainMap.put(value.getId(), chain);//保存
      }
      chain.addTime(value.getTime());
    }
    //计算间隔秒数
    int sessionsLength = 0;
    // 1计算间隔毫秒数
    for (Map.Entry<String, TimeChain> entry : this.timeChainMap.entrySet()) {
      long tmp = entry.getValue().getTimeOfMillis();
      if (tmp < 0 || tmp > GlobalConstants.DAY_OF_MILLISECONDS) {
        continue;//如果计算的值小于0 或者大于一天的毫秒数,直接过滤
      }
      sessionsLength += tmp;
    }
    //2计算间隔秒数
    if (sessionsLength % 1000 == 0) {
      sessionsLength = sessionsLength / 1000;
    } else {
      sessionsLength = sessionsLength / 1000 + 1;
    }

    //设置value
    this.map.put(new IntWritable(-1), new IntWritable(this.timeChainMap.size()));
    this.map.put(new IntWritable(-2), new IntWritable(sessionsLength));
    outputValue.setValue(this.map);

    //设置kpi
    outputValue.setKpi(KpiType.BROWSER_SESSIONS);
    context.write(key, outputValue);
  }
 

private static void parseLine(@Nonnull String line, @Nonnull IntWritable user,
        @Nonnull IntWritable posItem, @Nonnull IntWritable negItem) {
    String[] cols = StringUtils.split(line, ' ');
    Assert.assertEquals(3, cols.length);
    user.set(Integer.parseInt(cols[0]));
    posItem.set(Integer.parseInt(cols[1]));
    negItem.set(Integer.parseInt(cols[2]));
}
 

public void map(LongWritable key, Text value,
                OutputCollector<Text, IntWritable> output,
                Reporter reporter) throws IOException {
  String line = value.toString();
  StringTokenizer itr = new StringTokenizer(line);
  while (itr.hasMoreTokens()) {
    word.set(itr.nextToken());
    output.collect(word, one);
  }
}
 

static private IntWritable deduceInputFile(JobConf job) {
  Path[] inputPaths = FileInputFormat.getInputPaths(job);
  Path inputFile = new Path(job.get(JobContext.MAP_INPUT_FILE));

  // value == one for sort-input; value == two for sort-output
  return (inputFile.getParent().equals(inputPaths[0])) ? 
      sortInput : sortOutput;
}
 

public void reduce(Text key, Iterable<IntWritable> values, Context context)
		throws IOException, InterruptedException {
	int sum = 0;
	for (IntWritable val : values) {
		sum += val.get();
	}
	result.set(sum);
	context.write(key, result);
}
 

@Override
protected void cleanup(Context context) throws IOException, InterruptedException {
 for (Map.Entry<Integer, List<VectorWritable>> entry : referencePoints.entrySet()) {
    IntWritable iw = new IntWritable(entry.getKey());
    for (VectorWritable vw : entry.getValue()) {
      context.write(iw, vw);
    }
  }
  super.cleanup(context);
}
 

@SuppressWarnings("unchecked")
@Test
public void testMapperOnComma() throws IOException {
    mapDriver.clearInput();
    LongWritable inputKey1 = new LongWritable(1);
    LongWritable inputKey2 = new LongWritable(2);
    LongWritable inputKey3 = new LongWritable(3);
    LongWritable inputKey4 = new LongWritable(4);
    LongWritable inputKey5 = new LongWritable(5);
    LongWritable inputKey6 = new LongWritable(6);
    LongWritable inputKey7 = new LongWritable(7);

    mapDriver.addInput(inputKey1, new Text());
    mapDriver.addInput(inputKey2, new Text(strArr));
    mapDriver.addInput(inputKey3, new Text(strArr));
    mapDriver.addInput(inputKey4, new Text(strArr));
    mapDriver.addInput(inputKey5, new Text(strArr));
    mapDriver.addInput(inputKey6, new Text(strArr));
    mapDriver.addInput(inputKey7, new Text(strArr));

    List<Pair<IntWritable, BytesWritable>> result = mapDriver.run();

    assertEquals(9, result.size());

    int key1 = result.get(0).getFirst().get();
    BytesWritable value1 = result.get(0).getSecond();
    byte[] bytes = value1.getBytes();
    HyperLogLogPlusCounter hllc = new HyperLogLogPlusCounter();
    hllc.readRegisters(ByteBuffer.wrap(bytes));
    System.out.println("ab\177ab".length());
    assertTrue(key1 > 0);
    assertEquals(1, hllc.getCountEstimate());
}
 

public void reduce(IntWritable key,Iterable<VectorOrPrefWritable> values ,Context context ) throws IOException, InterruptedException{  
      
    for(VectorOrPrefWritable va:values){  
        context.write(key, va);  
        System.err.println("key"+key.toString()+",vlaue"+va);  
    }  
}