C++ graphchi_vertex::inedge方法代码示例

    /**
     *  Vertex update function.
     */
    void update(graphchi_vertex<VertexDataType, EdgeDataType> &vertex, graphchi_context &gcontext) {        
        if (first_iteration) {
            vertex.set_data(SCCinfo(vertex.id()));
        }
        
        if (vertex.get_data().confirmed) {
            return;
        }   
        
        /* Vertices with only in or out edges cannot be part of a SCC (Trimming) */
        if (vertex.num_inedges() == 0 || vertex.num_outedges() == 0) {
            if (vertex.num_edges() > 0) {
                // TODO: check this logic!
                vertex.set_data(SCCinfo(vertex.id()));
            }
            vertex.remove_alledges();
            return;
        }
        remainingvertices = true;

        VertexDataType vertexdata = vertex.get_data();
        bool propagate = false;
        if (gcontext.iteration == 0) {
            vertexdata = vertex.id();
            propagate = true;
            /* Clean up in-edges. This would be nicer in the messaging abstraction... */
            for(int i=0; i < vertex.num_inedges(); i++) {
                bidirectional_label edgedata = vertex.inedge(i)->get_data();
                edgedata.my_label(vertex.id(), vertex.inedge(i)->vertexid) = vertex.id();
                vertex.inedge(i)->set_data(edgedata);
            }
        } else {
            
            /* Loop over in-edges and choose minimum color */
            vid_t minid = vertexdata.color;
            for(int i=0; i < vertex.num_inedges(); i++) {
                minid = std::min(minid, vertex.inedge(i)->get_data().neighbor_label(vertex.id(), vertex.inedge(i)->vertexid));
            }
            
            if (minid != vertexdata.color) {
                vertexdata.color = minid;
                propagate = true;
            }            
        }
        vertex.set_data(vertexdata);
        
        if (propagate) {
            for(int i=0; i < vertex.num_outedges(); i++) {
                bidirectional_label edgedata = vertex.outedge(i)->get_data();
                edgedata.my_label(vertex.id(), vertex.outedge(i)->vertexid) = vertexdata.color;
                vertex.outedge(i)->set_data(edgedata);
                gcontext.scheduler->add_task(vertex.outedge(i)->vertexid, true);
            }
        }
    }

 /**
  *  Vertex update function.
  */
 void update(graphchi_vertex<VertexDataType, EdgeDataType> &vertex, graphchi_context &gcontext) {
     
     if (vertex.get_data().confirmed) {
         return;
     }
     
     VertexDataType vertexdata = vertex.get_data();
     bool propagate = false;
     if (gcontext.iteration == 0) {
         /* "Leader" of the SCC */
         if (vertexdata.color == vertex.id()) {
             propagate = true;
             vertex.remove_alloutedges();
         }
         
     } else {
         
         /* Loop over in-edges and see if there is a match */
         bool match = false;
         for(int i=0; i < vertex.num_outedges(); i++) {
             if (!vertex.outedge(i)->get_data().deleted()) {
                 if (vertex.outedge(i)->get_data().neighbor_label(vertex.id(), vertex.outedge(i)->vertexid) == vertexdata.color) {
                     match = true;
                     
                     break;
                 }
             }
         }
         if (match) {
             propagate = true;
             vertex.remove_alloutedges();
             vertex.set_data(SCCinfo(vertexdata.color, true));
         } else {
             vertex.set_data(SCCinfo(vertex.id(), false));
         }
     }
     
     
     if (propagate) {
         for(int i=0; i < vertex.num_inedges(); i++) {
             bidirectional_label edgedata = vertex.inedge(i)->get_data();
             if (!edgedata.deleted()) {
                 edgedata.my_label(vertex.id(), vertex.inedge(i)->vertexid) = vertexdata.color;
                 vertex.inedge(i)->set_data(edgedata);
                 gcontext.scheduler->add_task(vertex.inedge(i)->vertexid, true);
             }
         }
     }
 }

 /**
  *  Vertex update function.
  */
 void update(graphchi_vertex<VertexDataType, EdgeDataType > &vertex, graphchi_context &gcontext) {
     if (gcontext.iteration == 0) {
         for(int i=0; i < vertex.num_outedges(); i++) {
             chivector<vid_t> * evector = vertex.outedge(i)->get_vector();
             evector->clear();
             assert(evector->size() == 0);
             
             evector->add(vertex.id());
             assert(evector->size() == 1);
             assert(evector->get(0) == vertex.id());
         }
         
     } else {
         for(int i=0; i < vertex.num_inedges(); i++) {
             graphchi_edge<EdgeDataType> * edge = vertex.inedge(i);
             chivector<vid_t> * evector = edge->get_vector();
             assert(evector->size() >= gcontext.iteration);
             for(int j=0; j < evector->size(); j++) {
                 vid_t expected = edge->vertex_id() + j;
                 vid_t has = evector->get(j);
                 if (has != expected) {
                     std::cout << "Mismatch: " << has << " != " << expected << std::endl;
                 }
                 assert(has == expected);
             }
         }
         for(int i=0; i < vertex.num_outedges(); i++) {
             vertex.outedge(i)->get_vector()->add(vertex.id() + gcontext.iteration);
         }
     }
     vertex.set_data(gcontext.iteration + 1);
 }

    /**
      * Pagerank update function.
      */
    void update(graphchi_vertex<VertexDataType, EdgeDataType> &v, graphchi_context &ginfo) {
        float sum=0;
        if (ginfo.iteration == 0) {
            /* On first iteration, initialize vertex and out-edges. 
               The initialization is important,
               because on every run, GraphChi will modify the data in the edges on disk. 
             */
	    update_edge_data(v, 1.0);
            v.set_data(RANDOMRESETPROB); 
        } else {
            /* Compute the sum of neighbors' weighted pageranks by
               reading from the in-edges. */
            for(int i=0; i < v.num_inedges(); i++) {
                //float val = v.inedge(i)->get_data();
                //sum += val;                    
		struct weightE eData = v.inedge(i)->get_data();
		sum += eData.pagerank;
            }
            
            /* Compute my pagerank */
            float pagerank = RANDOMRESETPROB + (1 - RANDOMRESETPROB) * sum;
            
            /* Write my pagerank divided by the number of out-edges to
               each of my out-edges. */
	    update_edge_data(v, pagerank);
                
            /* Keep track of the progression of the computation.
               GraphChi engine writes a file filename.deltalog. */
            ginfo.log_change(std::abs(pagerank - v.get_data()));
            
            /* Set my new pagerank as the vertex value */
            v.set_data(pagerank); 
        }
    }

 /**
  *  Vertex update function.
  */
 void update(graphchi_vertex<VertexDataType, EdgeDataType> &vertex, graphchi_context &gcontext) {
     int ninedges = 0;
     if (gcontext.iteration == 0) {
         for(int i=0; i < vertex.num_inedges(); i++) {
             vertex.inedge(i)->set_data(vertex.id());        
             ninedges++;
         }
     } else {
         // Keep track of the number of edegs to ensure that
         // deletion works fine.
         if (vertex.get_data() != vertex.num_inedges())  {
             logstream(LOG_ERROR) << "Discrepancy in edge counts: " << vertex.get_data() << " != " << vertex.num_inedges() << std::endl;
         }
         assert(vertex.get_data() == vertex.num_inedges());
         
         for(int i=0; i < vertex.num_outedges(); i++) {
             graphchi_edge<vid_t> * edge = vertex.outedge(i);
             vid_t outedgedata = edge->get_data();
             vid_t expected = edge->vertex_id() + gcontext.iteration - (edge->vertex_id() > vertex.id());
             if (!is_deleted_edge_value(edge->get_data())) {
                 if (outedgedata != expected) {
                     logstream(LOG_ERROR) << outedgedata << " != " << expected << std::endl;
                     assert(false);
                 }
             }
         }
         for(int i=0; i < vertex.num_inedges(); i++) {
             vertex.inedge(i)->set_data(vertex.id() + gcontext.iteration);
             
             if (std::rand()  % 4 == 1) {
                 vertex.remove_inedge(i);
                 __sync_add_and_fetch(&ndeleted, 1);
             } else {
                 ninedges++;
             }
         }
     }
     
     if (gcontext.iteration == gcontext.num_iterations - 1) {
         vertex.set_data(gcontext.iteration + 1);
     } else {
         vertex.set_data(ninedges);
     }
 }

 void update(graphchi_vertex<VertexDataType, EdgeDataType>& v, graphchi_context& ginfo)
 {
     if (ginfo.iteration > 0) {
         float sum = 0;
         for (int i = 0; i < v.num_inedges(); i++) {
             sum += pr[v.inedge(i)->vertexid];
         }
         if (v.outc > 0) {
             pr[v.id()] = (RANDOMRESETPROB + (1 - RANDOMRESETPROB) * sum) / v.outc;
         } else {
             pr[v.id()] = (RANDOMRESETPROB + (1 - RANDOMRESETPROB) * sum);
         }
     } else if (ginfo.iteration == 0) {
         if (v.outc > 0)
             pr[v.id()] = 1.0f / v.outc;
     }
     if (ginfo.iteration == ginfo.num_iterations - 1) {
         /* On last iteration, multiply pr by degree and store the result */
         v.set_data(v.outc > 0 ? pr[v.id()] * v.outc : pr[v.id()]);
     }
 }

    /**
      * Pagerank update function.
      */
    void update(graphchi_vertex<VertexDataType, EdgeDataType> &v, graphchi_context &ginfo) {
        float sum=0;
	float prv = 0.0;
	float pagerankcont = 0.0;	

        if (ginfo.iteration == 0) {
            /* On first iteration, initialize vertex and out-edges. 
               The initialization is important,
               because on every run, GraphChi will modify the data in the edges on disk. 
             */
	    /* For the weighted version */
	    update_edge_data(v, 1.0, true);
            v.set_data(RANDOMRESETPROB); 
            //v.set_data(1.0); 
        } else {
	    /* We need to come up with the weighted version */
            for(int i=0; i < v.num_inedges(); i++) {
                chivector<float> * evector = v.inedge(i)->get_vector();
                assert(evector->size() >= 2);
                sum += evector->get(1);
    		//std::cout <<  v.id() << " with data: " << evector->get(1) << " with weight " << evector->get(0) << std::endl;
    		//std::cout <<  v.id() << " edge endpoint: " << v.inedge(i)->vertex_id() << std::endl;
		//evector->clear();
	    }

            /* Compute my pagerank */
            prv = RANDOMRESETPROB + (1 - RANDOMRESETPROB) * sum;
	    //std::cout << "sum" << sum << "pagerank: " << prv << std::endl;

	    update_edge_data(v, prv, false);
            /* Keep track of the progression of the computation.
               GraphChi engine writes a file filename.deltalog. */
	    double delta = std::abs(prv - v.get_data());
	    //std::cout << "pagerank: " << prv << "v.data" << v.get_data() << "delta: " << delta << std::endl;
            ginfo.log_change(delta);
            
            /* Set my new pagerank as the vertex value */
            v.set_data(prv);
        }
    }

    /**
     *  Vertex update function.
     */
    void update(graphchi_vertex<VertexDataType, EdgeDataType> &vertex, graphchi_context &gcontext) {
              
		VertexDataType vertexdata; //= vertex.get_data();
		//bool propagate = false;
		if (gcontext.iteration == 0) {
			//vertex.set_data(SCCinfo(vertex.id()));
			vertexdata = vertex.get_data();
			/* vertices that is not visited in Fw phase is not in the giant SCC!
			 * minor improve by mzj 2016/3/13
			 */
			if(!vertexdata.confirmed)
				return;
			//assert(vertexdata.color == root);
			if(vertex.id() == root){
				//vertexdata.confirmed = true;
				vertexdata.color = vertex.id(); 
				vertexdata.reconfirmed = true; 
				for(int i=0; i<vertex.num_inedges(); i++){
					bidirectional_label edgedata = vertex.inedge(i)->get_data();
					edgedata.my_label(vertex.id(), vertex.inedge(i)->vertexid) = vertex.id();
					vertex.inedge(i)->set_data(edgedata);
					if(scheduler) gcontext.scheduler->add_task(vertex.inedge(i)->vertexid);	
					vertex.inedge(i)->set_data(edgedata);
				}	
				vertex.set_data(vertexdata);	
			}else{
				vertexdata.reconfirmed = false;
				vertexdata.color = vertex.id(); 
				for(int i=0; i<vertex.num_inedges(); i++){
					bidirectional_label edgedata = vertex.inedge(i)->get_data();
					edgedata.my_label(vertex.id(), vertex.inedge(i)->vertexid) = vertex.id();
					vertex.inedge(i)->set_data(edgedata);
					//if(scheduler) gcontext.scheduler->add_task(vertex.outedge(i)->vertexid);	
				}	
				vertex.set_data(vertexdata);	
			}
			//vertex.set_data(vertexdata);	
		} else {
			vertexdata = vertex.get_data();
			if(!vertexdata.confirmed)
				return ;
			vid_t min_color = vertexdata.color;
			for(int i=0; i<vertex.num_outedges(); i++){
				//min_color = std::min(min_color, vertexdata.inedge(i)->get_data().neighbor_label(vertex.id(), vertex.inedge(i)->vertexid));		
				if(root == (vertex.outedge(i)->get_data()).neighbor_label(vertex.id(), vertex.outedge(i)->vertexid)){
						min_color = root;
						break;
				}
			}
			if(min_color != vertexdata.color){
				converged = false;
				//vertexdata.confirmed = true;
				vertexdata.reconfirmed = true;
				vertexdata.color = min_color;
				for(int i=0; i<vertex.num_inedges(); i++){
					bidirectional_label edgedata = vertex.inedge(i)->get_data();
					edgedata.my_label(vertex.id(), vertex.inedge(i)->vertexid) = min_color;
					if(scheduler) gcontext.scheduler->add_task(vertex.inedge(i)->vertexid);	
					vertex.inedge(i)->set_data(edgedata);
				}	
				vertex.set_data(vertexdata);
			}
		}
    }

    void update(graphchi_vertex<VertexDataType, EdgeDataType> &vertex, graphchi_context &gcontext) {


        //For iteration 0
        if (gcontext.iteration == 0) {
            
           
            chivector<vid_t> * v_vector = vertex.get_vector();
            v_vector->clear();
            
            /* Initialize a json object, rvec to maintain the result vector of the current node.
             * Maintain the list of outedges of the current vector. 
             * These outedges are the children and must match the children of the query node.
             * Maintain a vector for all the nodes set to false in the current iteraion. 
             */
            nlohmann::json rvec;
            std::vector<vid_t> vertex_outedges;
            std::vector<vid_t> vertex_false;
            
            for (int i = 0; i < vertex.num_outedges(); i++) {
                vertex_outedges.push_back(vertex.outedge(i)->vertex_id());
            }
            
            /*
             * Iterate through all the query nodes, and check the equality with the current node. 
             * If the current node matches the query node, add the dependencies of the query node to the rvec.
             * If the query node does not have any dependencies, set rvec[i] as true. (This implies a direct match)
             * If the query node and the current node don't match, set rvec[i] to false and add i to vertex_false.
             */
            for(unsigned int i=0; i < query_json["node"].size(); i++) {
                if(check_equal(vertex_json[vertex.id()],query_json["node"][i])) {    
                    unsigned int out_d = query_json["node"][i]["out_degree"];
                    if(out_d == 0){
                        rvec[i] = true;
                        v_vector->add(i);
                    }
                    else if(vertex_outedges.size() == 0)
                    {
                        rvec[i] = false;
                        vertex_false.push_back(i);
                    }
                    else
                    {    for(unsigned int j=0; j <query_json["edge"].size(); j++){
                            unsigned int source = query_json["edge"][j]["source"], target = query_json["edge"][j]["target"];
                            if(i == source )
                                rvec[i][target] = vertex_outedges;
                        }
                        v_vector->add(i);
                    }
                    
                }
                else
                {
                    rvec[i] = false;
                    vertex_false.push_back(i);
                }
            }
            
            // Access the element of rvec_map with key equal to current vertex id. 
            // Assign rvec as the value for current vertex id.
            tbb::concurrent_hash_map<unsigned int, nlohmann::json>::accessor ac;
            rvec_map.insert(ac,vertex.id());
            ac->second = rvec;
            ac.release();
            
            /*
             * If the size of vertex_false is not zero, changes have been made in the current iteration.
             * For all the inedges, add the all the elements of vertex_false to the edge vector.
             * Schedule all the inedges for the next iteration.
             * 
             */
            
            if(vertex_false.size() != 0) {
                for(int i = 0; i < vertex.num_inedges(); i++) {
                    chivector<vid_t> * e_vector = vertex.inedge(i)->get_vector();
                    e_vector->clear();
                    for(unsigned int j = 0; j< vertex_false.size(); j++){
                        e_vector->add(vertex_false[j]);
                    }
                    gcontext.scheduler->add_task(vertex.inedge(i)->vertex_id());
                }
            }    

        } 
        
        //For iteration 1..n
        else{
            
            /*
             * Retrieve the rvec for the current node from the rvec_map. 
             * Intialize vertex_false to maintain the vertices set to false.  
             */
            tbb::concurrent_hash_map<unsigned int, nlohmann::json>::accessor ac;
            rvec_map.find(ac,vertex.id());
            nlohmann::json rvec = ac->second;
            std::vector<vid_t> vertex_false;
            
            chivector<vid_t> * v_vector = vertex.get_vector();
            
                    
//.........这里部分代码省略.........

//.........这里部分代码省略.........
                                rvec[i][target] = vertex.num_outedges();
                        }
                        dependencies++;
                    }

                }
                else
                {
                    rvec[i] = false;
                    vertex_false.push_back(i);
                }
            }
            /*
             * If the vertex has dependencies, schedule the children of the current vertex (outedges).
             */
            if(dependencies != 0){
                for(int i = 0; i <vertex.num_outedges();i++)
                    gcontext.scheduler->add_task(vertex.outedge(i)->vertex_id());
            }
            
            /*
             * Vertex data is set to the number of dependencies.
             * If the vertex data is greater than 0, then it is processed whenever it is scheduled in the subsequent iterations.
             * If the vertex data is 0, it is not processed in the subsequent iterations.  
             */
            vertex.set_data(dependencies);
        } 
            
        dependencies = vertex.get_data();
        
        /*
         * If the current vertex has dependencies, it has to be processed.
         * Collect the edge data of all it's outgoing edges and for each outgoing edge which is updated, update the corresponding dependency.
         * Else, clear all the outedges. 
         */
        
        if(dependencies != 0 ) {
            
            nlohmann::json updates;
            
            for(int i = 0; i < vertex.num_outedges(); i++){
                chivector<vid_t> * e_vector = vertex.outedge(i)->get_vector();
                int evector_size = e_vector->size();
                for( int j =0; j < evector_size; j++){
                    vid_t t = e_vector->get(j);
                    if(updates[t].is_null())
                        updates[t] = 1;
                    else {
                        int n = updates[t];
                        updates[t] = n +1;
                    }
                }
                e_vector->clear();
            }
            
            for(vid_t i = 0; i < updates.size(); i++ ) {
                if(updates[i].is_null())
                    continue;
                int cur_updates = updates[i];
                for(size_t j = 0; j < rvec.size(); j++){
                    if(rvec[j].is_boolean())
                        continue;
                    if(rvec[j][i].is_number()){
                        int prev_dep = rvec[j][i];
                        if(prev_dep <= cur_updates) {
                            rvec[j] = false;
                            vertex_false.push_back(j);
                            dependencies --;
                        }
                        else
                            rvec[j][i] = prev_dep - cur_updates;
                    }
                }
            }
            vertex.set_data(dependencies);
        } else {
            for(int i = 0; i < vertex.num_outedges(); i++){
                chivector<vid_t> * e_vector = vertex.outedge(i)->get_vector();
                if(e_vector->size())
                    e_vector ->clear();
            }
        }
   
        /*
         * If a node has been set to false in the current iteration, propagate the update through all the inedges.
         */
        if(vertex_false.size() != 0){
            for(int i=0; i < vertex.num_inedges(); i++){
                chivector<vid_t> * e_vector = vertex.inedge(i) -> get_vector();
                 for(unsigned int j = 0; j < vertex_false.size(); j++)
                     e_vector->add(vertex_false[j]);
                 gcontext.scheduler->add_task(vertex.inedge(i)->vertex_id());
            }
        }
        
        // Update the result vector and release the accsessor. 
        ac->second = rvec;
        ac.release();

    }