public RandomMultiGraphNeighborsResponse getRandomMultiGraphNeighbors()

in graphjet-core/src/main/java/com/twitter/graphjet/algorithms/randommultigraphneighbors/RandomMultiGraphNeighbors.java [88:153]
57 lines of code
8 McCabe index (conditional complexity)

  public RandomMultiGraphNeighborsResponse getRandomMultiGraphNeighbors(
      RandomMultiGraphNeighborsRequest request,
      Random random,
      RelatedTweetFilterChain filterChain) {
    Long2DoubleMap leftSeedNodeWithWeights = request.getLeftSeedNodesWithWeight();
    int maxNumSamples = request.getMaxNumSamples();
    int maxNumResults = Math.min(
      request.getMaxNumResults(),
      RecommendationRequest.MAX_RECOMMENDATION_RESULTS
    );

    // construct a IndexArray and AliasTableArray to sample from LHS seed nodes
    long[] indexArray = new long[leftSeedNodeWithWeights.size()];
    int[] aliasTableArray = IntArrayAliasTable.generateAliasTableArray(
      leftSeedNodeWithWeights.size());
    constructAliasTableArray(leftSeedNodeWithWeights, indexArray, aliasTableArray);

    // first, get number of samples for each of the seed nodes
    Long2IntMap nodeToNumSamples = new Long2IntOpenHashMap(leftSeedNodeWithWeights.size());
    nodeToNumSamples.defaultReturnValue(0);
    for (int i = 0; i < maxNumSamples; i++) {
      int index = AliasTableUtil.getRandomSampleFromAliasTable(aliasTableArray, random);
      long sampledLHSNode = indexArray[index];
      nodeToNumSamples.put(sampledLHSNode, nodeToNumSamples.get(sampledLHSNode) + 1);
    }

    // now actually retrieve neighbors of sampled seed nodes
    Long2IntMap seedNodeRightNeighbors = new Long2IntOpenHashMap(1024);
    seedNodeRightNeighbors.defaultReturnValue(0);
    for (Long2IntMap.Entry entry : nodeToNumSamples.long2IntEntrySet()) {
      long node = entry.getLongKey();
      int numSamples = entry.getIntValue();
      EdgeIterator currentIterator = bipartiteGraph.getRandomLeftNodeEdges(
        node, numSamples, random);
      if (currentIterator != null) {
        while (currentIterator.hasNext()) {
          long neighbor = currentIterator.nextLong();
          seedNodeRightNeighbors.put(
              neighbor, seedNodeRightNeighbors.get(neighbor) + 1);
        }
      }
    }

    // normalize and select top neighbors
    PriorityQueue<NeighborInfo> topResults = new PriorityQueue<NeighborInfo>(maxNumResults);
    numOfUniqueNeighborsCounter.incr(seedNodeRightNeighbors.size());
    for (Long2IntMap.Entry entry : seedNodeRightNeighbors.long2IntEntrySet()) {
      long neighborNode = entry.getLongKey();
      int occurrence = entry.getIntValue();
      numOfNeighborsCounter.incr(occurrence);
      if (filterChain.filter(neighborNode)) {
        continue;
      }
      int neighborNodeDegree = bipartiteGraph.getRightNodeDegree(neighborNode);
      NeighborInfo neighborInfo = new NeighborInfo(
        neighborNode, (double) occurrence / (double) maxNumSamples, neighborNodeDegree);
      addResultToPriorityQueue(topResults, neighborInfo, maxNumResults);
    }
    List<NeighborInfo> outputResults = Lists.newArrayListWithCapacity(topResults.size());
    while (!topResults.isEmpty()) {
      outputResults.add(topResults.poll());
    }
    Collections.reverse(outputResults);

    return new RandomMultiGraphNeighborsResponse(outputResults);
  }