Apache Gora™ 服务于大数据的内存模型框架

 {
  "type": "record",
  "name": "Pageview",
  "namespace": "org.apache.gora.tutorial.log.generated",
  "fields" : [
    {"name": "url", "type": "string"},
    {"name": "timestamp", "type": "long"},
    {"name": "ip", "type": "string"},
    {"name": "httpMethod", "type": "string"},
    {"name": "httpStatusCode", "type": "int"},
    {"name": "responseSize", "type": "int"},
    {"name": "referrer", "type": "string"},
    {"name": "userAgent", "type": "string"}
  ]
}
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public class LogManager {
  ..
  private DataStore<Long, Pageview> dataStore; 
   ... 
}
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public class LogAnalytics extends Configured implements Tool {

  private static final Logger log = LoggerFactory.getLogger(LogAnalytics.class);
  
  /** The number of miliseconds in a day */
  private static final long DAY_MILIS = 1000 * 60 * 60 * 24;
    
  /**
   * The Mapper takes Long keys and Pageview objects, and emits 
   * tuples of <url, day> as keys and 1 as values. Input values are 
   * read from the input data store.
   * Note that all Hadoop serializable classes can be used as map output key and value.
   */
  public static class LogAnalyticsMapper 
    extends GoraMapper<Long, Pageview, TextLong, LongWritable> {
    
    private LongWritable one = new LongWritable(1L);
  
    private TextLong tuple;
    
    @[author]Override[/author]
    protected void setup(Context context) throws IOException ,InterruptedException {
      tuple = new TextLong();
      tuple.setKey(new Text());
      tuple.setValue(new LongWritable());
    };
    
    @[author]Override[/author]
    protected void map(Long key, Pageview pageview, Context context) 
      throws IOException ,InterruptedException {
      
      Utf8 url = pageview.getUrl();
      long day = getDay(pageview.getTimestamp());
      
      tuple.getKey().set(url.toString());
      tuple.getValue().set(day);
      
      context.write(tuple, one);
    };
    
    /** Rolls up the given timestamp to the day cardinality, so that 
     * data can be aggregated daily */
    private long getDay(long timeStamp) {
      return (timeStamp / DAY_MILIS) * DAY_MILIS; 
    }
  }
  
  /**
   * The Reducer receives tuples of <url, day> as keys and a list of 
   * values corresponding to the keys, and emits a combined keys and
   * {@link MetricDatum} objects. The metric datum objects are stored 
   * as job outputs in the output data store.
   */
  public static class LogAnalyticsReducer 
    extends GoraReducer<TextLong, LongWritable, String, MetricDatum> {
    
    private MetricDatum metricDatum = new MetricDatum();
    
    @[author]Override[/author]
    protected void reduce(TextLong tuple
        , Iterable<LongWritable> values, Context context) 
      throws IOException ,InterruptedException {
      
      long sum = 0L; //sum up the values
      for(LongWritable value: values) {
        sum+= value.get();
      }
      
      String dimension = tuple.getKey().toString();
      long timestamp = tuple.getValue().get();
      
      metricDatum.setMetricDimension(new Utf8(dimension));
      metricDatum.setTimestamp(timestamp);
      
      String key = metricDatum.getMetricDimension().toString();
      key += "_" + Long.toString(timestamp);
      metricDatum.setMetric(sum);
      
      context.write(key, metricDatum);
    };
  }
  
  /**
   * Creates and returns the {@link Job} for submitting to Hadoop mapreduce.
   * @param dataStore
   * @param query
   * @return
   * @throws IOException
   */
  public Job createJob(DataStore<Long, Pageview> inStore
      , DataStore<String, MetricDatum> outStore, int numReducer) throws IOException {
    Job job = new Job(getConf());

    job.setJobName("Log Analytics");
    job.setNumReduceTasks(numReducer);
    job.setJarByClass(getClass());

    /* Mappers are initialized with GoraMapper.initMapper() or 
     * GoraInputFormat.setInput()*/
    GoraMapper.initMapperJob(job, inStore, TextLong.class, LongWritable.class
        , LogAnalyticsMapper.class, true);

    /* Reducers are initialized with GoraReducerinitReducer().
     * If the output is not to be persisted via Gora, any reducer 
     * can be used instead. */
    GoraReducer.initReducerJob(job, outStore, LogAnalyticsReducer.class);
    
    return job;
  }
  
  @[author]Override[/author]
  public int run(String[] args) throws Exception {
    
    DataStore<Long, Pageview> inStore;
    DataStore<String, MetricDatum> outStore;
    Configuration conf = new Configuration();    

    if(args.length > 0) {
      String dataStoreClass = args[0];
      inStore = DataStoreFactory.
          getDataStore(dataStoreClass, Long.class, Pageview.class, conf);
      if(args.length > 1) {
        dataStoreClass = args[1];
      }
      outStore = DataStoreFactory.
          getDataStore(dataStoreClass, 
			 String.class, MetricDatum.class, conf);
    } else {
	inStore = DataStoreFactory.getDataStore(Long.class, Pageview.class, conf);
	outStore = DataStoreFactory.getDataStore(String.class, MetricDatum.class, conf);
    }
    
    Job job = createJob(inStore, outStore, 3);
    boolean success = job.waitForCompletion(true);
    
    inStore.close();
    outStore.close();
    
    log.info("Log completed with " + (success ? "success" : "failure"));
    
    return success ? 0 : 1;
  }
  
  public static void main(String[] args) throws Exception {
    //run as any other MR job
    int ret = ToolRunner.run(new LogAnalytics(), args);
    System.exit(ret);
  }
  
}
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