Package org.apache.mahout.cf.taste.hadoop

Examples of org.apache.mahout.cf.taste.hadoop.RecommendedItemsWritable

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    List<RecommendedItem> recommendations = new ArrayList<RecommendedItem>(
        topItems.size());
    recommendations.addAll(topItems);
    Collections.sort(recommendations,
        ByValueRecommendedItemComparator.getInstance());
    context.write(key, new RecommendedItemsWritable(recommendations));
  }
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    }
   
    List<RecommendedItem> recommendations = new ArrayList<RecommendedItem>(topItems.size());
    recommendations.addAll(topItems);
    Collections.sort(recommendations);
    output.collect(userID, new RecommendedItemsWritable(recommendations));
  }
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    while (it.hasNext()) {
      if (Float.isNaN(it.next().getValue())) {
        it.remove();
      }
    }
    RecommendedItemsWritable writable = new RecommendedItemsWritable(recommendedItems);
    output.collect(new LongWritable(userID), writable);
    reporter.getCounter(ReducerMetrics.USERS_PROCESSED).increment(1L);
    reporter.getCounter(ReducerMetrics.RECOMMENDATIONS_MADE).increment(recommendedItems.size());
  }
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    while (it.hasNext()) {
      if (Float.isNaN(it.next().getValue())) {
        it.remove();
      }
    }
    RecommendedItemsWritable writable = new RecommendedItemsWritable(recommendedItems);
    context.write(key, writable);
    context.getCounter(ReducerMetrics.USERS_PROCESSED).increment(1L);
    context.getCounter(ReducerMetrics.RECOMMENDATIONS_MADE).increment(recommendedItems.size());
  }
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      for (RecommendedItem topItem : topKItems.retrieve()) {
        recommendedItems.add(new GenericRecommendedItem(topItem.getItemID(), Math.min(topItem.getValue(), maxRating)));
      }

      if (!topKItems.isEmpty()) {
        ctx.write(userIDWritable, new RecommendedItemsWritable(recommendedItems));
      }
    }
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        }
      }
    }

    if (!recommendations.isEmpty()) {
      context.write(userID, new RecommendedItemsWritable(recommendations));
    }
  }
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    if (!topItems.isEmpty()) {
      List<RecommendedItem> recommendations = new ArrayList<RecommendedItem>(topItems.size());
      recommendations.addAll(topItems);
      Collections.sort(recommendations, ByValueRecommendedItemComparator.getInstance());
      context.write(userID, new RecommendedItemsWritable(recommendations));
    }
  }
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  static RecommendedItemsWritable recommendationsMatch(final RecommendedItem... items) {
    EasyMock.reportMatcher(new IArgumentMatcher() {
      @Override
      public boolean matches(Object argument) {
        if (argument instanceof RecommendedItemsWritable) {
          RecommendedItemsWritable recommendedItemsWritable = ((RecommendedItemsWritable) argument);
          List<RecommendedItem> expectedItems = new LinkedList<RecommendedItem>(Arrays.asList(items));
          return expectedItems.equals(recommendedItemsWritable.getRecommendedItems());
        }
        return false;
      }

      @Override
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    while (it.hasNext()) {
      if (Float.isNaN(it.next().getValue())) {
        it.remove();
      }
    }
    RecommendedItemsWritable writable = new RecommendedItemsWritable(recommendedItems);
    context.write(key, writable);
    context.getCounter(ReducerMetrics.USERS_PROCESSED).increment(1L);
    context.getCounter(ReducerMetrics.RECOMMENDATIONS_MADE).increment(recommendedItems.size());
  }
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  static RecommendedItemsWritable recommendationsMatch(final RecommendedItem... items) {
    EasyMock.reportMatcher(new IArgumentMatcher() {
      @Override
      public boolean matches(Object argument) {
        if (argument instanceof RecommendedItemsWritable) {
          RecommendedItemsWritable recommendedItemsWritable = (RecommendedItemsWritable) argument;
          List<RecommendedItem> expectedItems = Arrays.asList(items);
          return expectedItems.equals(recommendedItemsWritable.getRecommendedItems());
        }
        return false;
      }

      @Override
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Related Classes of org.apache.mahout.cf.taste.hadoop.RecommendedItemsWritable

  • mia.recommender.ch06.AggregateAndRecommendReducer
  • org.apache.mahout.cf.taste.hadoop.als.RecommenderJob$PredictionMapper
  • org.apache.mahout.cf.taste.hadoop.item.AggregateAndRecommendReducer
  • org.apache.mahout.cf.taste.hadoop.item.RecommenderJobTest
  • org.apache.mahout.cf.taste.hadoop.item.RecommenderMapper
  • org.apache.mahout.cf.taste.hadoop.pseudo.RecommenderReducer
  • org.apache.mahout.cf.taste.impl.recommender.GenericRecommendedItem
  • org.apache.mahout.cf.taste.model.Item
  • org.apache.mahout.cf.taste.recommender.RecommendedItem
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