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v2.x
    v2.x

    Algorithm

    List Algorithm

    List<Table> tables = client.listAlgo();

    Degree Calculation

    Out Degree

    OutDegreeRequest request = new OutDegreeRequest();
request.setNodeId(12L);
List<Table> tables = client.outDegree(request);

    Out Degree - all nodes

    OutDegreeAllRequest request = new OutDegreeAllRequest();
List<Table> tables = client.outDegreeAll(request);

    In Degree

    InDegreeRequest request = new InDegreeRequest();
request.setNodeId(12L);
List<Table> tables = client.inDegree(request);

    In Degree - all nodes

    InDegreeAllRequest request = new InDegreeAllRequest();
List<Table> tables = client.inDegreeAll(request);

    Degree Centrality

    DegreeCentralityRequest request = new DegreeCentralityRequest();
request.setNodeId(12L);
List<Table> tables = client.degreeCentrality(request);

    Degree Centrality - all nodes

    DegreeCentralityAllRequest request = new DegreeCentralityAllRequest();
List<Table> tables = client.degreeCentralityAll(request);

    Centrality Calculation

    Closeness Centrality

    ClosenessCentralityRequest request = new ClosenessCentralityRequest();
request.setNodeId(12L);
List<Table> tables = client.closenessCentrality(request);

    Out Closeness Centrality

    OutClosenessCentralityRequest request = new OutClosenessCentralityRequest();
request.setNodeId(12L);
List<Table> tables = client.outClosenessCentrality(request);

    In Closeness Centrality

    InClosenessCentralityRequest request = new InClosenessCentralityRequest();
request.setNodeId(12L);
List<Table> tables = client.inClosenessCentrality(request);

    Graph Centrality

    GraphCentralityRequest request = new GraphCentralityRequest();
request.setNodeId(12L);
List<Table> tables = client.graphCentrality(request);

    Betweenness Centrality

    BetweennessCentralityRequest request = new BetweennessCentralityRequest();
request.setNodeId(12L);
List<Table> tables = client.betweennessCentrality(request);

    General Graph Algorithm

    Graph-Wide K-Hop

    KhopAlgoRequest request = new KhopAlgoRequest();
request.setDepth(1);
List<Table> tables = client.khopAlgo(request);

    Connected Component

    List<Table> tables = client.connectedComponent();

    Triangle Counting

    List<Table> tables = client.triangleCounting();

    Common Neighbours

    CommonNeighboursRequest request = new CommonNeighboursRequest();
request.setNodeId1(12);
request.setNodeId2(24);
List<Table> tables = client.commonNeighbours(request);

    Subgraph

    SubgraphRequest request = new SubgraphRequest();
request.setNodeIds(new int[] {1,2,3,4});
List<Table> tables = client.subGraph(request);

    dvanced Graph Algorithm

    hyperANF

    HyperANFRequest request = new HyperANFRequest();
request.setLoopNum(2);
request.setRegisterNum(4);
List<Table> tables = client.hyperANF(request);

    kNN

    KNearestNeighborRequest request = new KNearestNeighborRequest();
request.setNodeId(2);
request.setNodePropertyNames(Arrays.asList("age"));
request.setTop(10);
request.setTargetPropertyName("name");
List<Table> tables = client.kNearestNeighbor(request);

    k-Core

    KCoreRequest request = new KCoreRequest();
request.setK(5);
List<Table> tables = client.kCore(request);

    MST

    MinimumSpanningTreeRequest request = new MinimumSpanningTreeRequest();
request.setStartNodeId(12);
request.setEdgePropertyName("rank");
request.setWriteBack(true);
List<Table> tables = client.minimumSpanningTree(request);

    k-Means

    KMeansRequest request = new KMeansRequest();
request.setK(3);
request.setStartIds(Arrays.asList(1,2,3,4));
request.setLoopNum(2);
request.setNodePropertyNames(Arrays.asList("age"));
request.setDistanceType(DistanceType.CosineSimilarityDistance);
List<Table> tables = client.kMeans(request);

    Clustering Coefficient

    ClusteringCoefficientRequest request = 
new ClusteringCoefficientRequest();
request.setNodeId(12);
List<Table> tables = client.clusteringCoefficient(request);

    Community Detection & Propagation Algorithm

    Page Rank

    PageRankRequest request = new PageRankRequest();
request.setLoopNum(2);
request.setDamping(0.8f);
List<Table> tables = client.pageRank(request);

    Sybil Rank

    SybilRankRequest request = new SybilRankRequest();
request.setLoopNum(2);
request.setSybilNum(10);
request.setTrustSeeds(Arrays.asList(63342,12324,52356,18974,9634,34));
request.setTotalTrust(100);
List<Table> tables = client.sybilRank(request);

    LPA

    LabelPropagationRequest request = new LabelPropagationRequest();
request.setLoopNum(2);
request.setNodePropertyName("name");
List<Table> tables = client.labelPropagation(request);

    HANP （Hop Attenuation & Node Preference）

    HANPRequest request = new HANPRequest();
request.setLoopNum(2);
request.setDelta(1);
request.setEdgePropertyName("rank");
request.setNodePropertyName("age");
request.setM(2);
request.setWriteBack(true);
List<Table> tables = client.hanp(request);

    Louvain

    LouvainRequest request = new LouvainRequest();
request.setPhase1Loop(5);
request.setMinModularityIncrease(0.01f);
request.setEdgePropertyName("rank");
List<Table> tables = client.louvain(request);

    Louvain Visualization

    LouvaindvRequest request = new LouvaindvRequest();
request.setTaskId(1);
request.setTop(1);
request.setTotal(500);
List<Table> tables = client.louvainDv(request);

    Similarity

    Jaccard Similarity

    JaccardSimilarityRequest request = new JaccardSimilarityRequest();
request.setNodeId1(1);
request.setNodeId2(2);
request.setTop(3);
List<Table> tables = client.jaccardSimilarity(request);

    Cosine Similarity

    CosineSimilarityRequest request = new CosineSimilarityRequest();
request.setNodeId1(1);
request.setNodeId2(2);
request.setNodePropertyNames(Arrays.asList("name", "age"));
List<Table> tables = client.cosineSimilarity(request);

    Graph Embedding

    Random Walk

    RandomWalkRequest request = new RandomWalkRequest();
request.setWalkNum(2);
request.setWalkLength(2);
request.setEdgePropertyName("age");
List<Table> tables = client.randomWalk(request);

    Node2Vec Random Walk

    RandomWalkNode2VecRequest request = new RandomWalkNode2VecRequest();
request.setWalkNum(1);
request.setWalkLength(1);
request.setP(1);
request.setQ(1);
request.setEdgePropertyName("age");
List<Table> tables = client.randomWalkNode2Vec(request);

    Struc2Vec Random Walk

    RandomWalkStruc2VecRequest request = new RandomWalkStruc2VecRequest();
request.setWalkNum(1);
request.setWalkLength(1);
request.setK(1);
request.setStayProbability(0.5f);
List<Table> tables = client.randomWalkStruc2Vec(request);

    Node2Vec Embedding

    Node2VecRequest request = new Node2VecRequest();
request.setLoopNum(1);
request.setContextSize(1);
request.setDimension(1);
request.setEdgePropertyName("rank");
request.setIterNum(1);
request.setLearningRate(.5);
request.setMinFrequency(1);
request.setMinLearningRate(.5);
request.setNegNum(1);
request.setP(.5f);
request.setQ(.5f);
request.setResolution(1);
request.setSubSampleAlpha(.5);
request.setWalkLength(1);
request.setWalkNum(1);
List<Table> tables = client.node2Vec(request);

    LINE（Large Information Network Embedding）

    LINERequest request = new LINERequest();
request.setDimension(1);
request.setEdgePropertyName("rank");
request.setNegNum(1);
request.setResolution(1);
request.setStartAlpha(.5);
request.setTotalSample(1);
request.setTrainOrder(1);
List<Table> tables = client.line(request);

    Struc2Vec Embedding

    Struc2VecRequest request = new Struc2VecRequest();
request.setContextSize(1);
request.setDimension(1);
request.setK(1);
request.setLearningRate(.5);
request.setLoopNum(1);
request.setMinFrequency(1);
request.setMinLearningRate(.5);
request.setNegNum(1);
request.setResolution(1);
request.setStayProbability(.5f);
request.setSubSampleAlpha(.5);
request.setWalkLength(1);
request.setWalkNum(1);
request.setWindowSize(1);
List<Table> tables = client.struc2vec(request);