graphchi-cpp/example_apps/trianglecounting.cpp at master · GraphChi/graphchi-cpp · GitHub

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/**

* @file

* @author Aapo Kyrola <akyrola@cs.cmu.edu>

* @version 1.0

* @section LICENSE

* Copyright [2012] [Aapo Kyrola, Guy Blelloch, Carlos Guestrin / Carnegie Mellon University]

* Licensed under the Apache License, Version 2.0 (the "License");

* you may not use this file except in compliance with the License.

* You may obtain a copy of the License at

* http://www.apache.org/licenses/LICENSE-2.0

* Unless required by applicable law or agreed to in writing, software

* distributed under the License is distributed on an "AS IS" BASIS,

* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

* See the License for the specific language governing permissions and

* limitations under the License.

* @section DESCRIPTION

* Triangle counting application. Counts the number of incident (full) triangles

* for each vertex. Edge direction is ignored.

* This algorithm is quite complicated and requires 'trickery' to work

* well on GraphChi. The complexity stems from the need to store large number

* of adjacency lists in memory: we cannot store the adjacency lists reasonable

* to edges, nor can we store all of them once at memory. Therefore the problems

* is solved in a series of phases. On each phase, the relevant adjacency lists of an interval

* of vertices (called 'pivots') is loaded into memory, and all vertices that have id smaller than the

* pivots are matched with them. With 'relevant adjacency list' I mean the list of neighbors

* that have higher id then the pivots themselves. That is, we only count triangles a -> b -> c

* where a > b > c.

* The application involves a special preprocessing step which orders the vertices in ascending

* order of their degree. This turns out to be a very important optimization on big graphs.

* This algorithm also utilizes the dynamic graph engine, and deletes edges after they have been

* accounted for.

#include <string>

#include <vector>

/**

* Need to define prior to including GraphChi

* headers. This enabled edge-deletion in the vertex object.

#define SUPPORT_DELETIONS 1

#define GRAPHCHI_DISABLE_COMPRESSION

#include "graphchi_basic_includes.hpp"

#include "engine/dynamic_graphs/graphchi_dynamicgraph_engine.hpp"

#include "engine/auxdata/degree_data.hpp"

#include "preprocessing/util/orderbydegree.hpp"

using namespace graphchi;

/**

* Type definitions. Vertex data stores the number of incident triangles.

* Edge stores number of unaccounted triangles that the edge participates on.

* When vertex is updated, it updates its vertex count by summing up the

* counts from edges (after which the edges are deleted).

typedef uint32_t VertexDataType;

typedef uint32_t EdgeDataType;

* Class for writing the output number of triangles for each node

class OutputVertexCallback : public VCallback<VertexDataType> {

public:

virtual void callback(vid_t vertex_id, VertexDataType &value) {

if (value > 0)

std::cout << vertex_id << " " << value << std::endl;

}

};

/**

* Code for intersection size computation and

* pivot management.

int grabbed_edges = 0;

// Linear search

inline bool findadj_linear(vid_t * datachunk, size_t n, vid_t target) {

for(int i=0; i<(int)n; i++) {

if (datachunk[i] == target) return true;

else if (datachunk[i] > target) return false;

}

return false;

}

// Binary search

inline bool findadj(vid_t * datachunk, size_t n, vid_t target) {

if (n<32) return findadj_linear(datachunk, n, target);

while(hi>lo) {

vid_t eto = datachunk[m];

if (target == eto) {

return true;

}

if (target > eto) {

lo = m+1;

} else {

hi = m;

}

m = lo + (hi-lo)/2;

}

return false;

}

struct dense_adj {

int count;

vid_t * adjlist;

dense_adj() { adjlist = NULL; }

dense_adj(int _count, vid_t * _adjlist) : count(_count), adjlist(_adjlist) {

}

};

// This is used for keeping in-memory

class adjlist_container {

std::vector<dense_adj> adjs;

mutex m;

public:

vid_t pivot_st, pivot_en;

adjlist_container() {

pivot_st = 0;

pivot_en = 0;

}

void clear() {

for(std::vector<dense_adj>::iterator it=adjs.begin(); it != adjs.end(); ++it) {

if (it->adjlist != NULL) {

free(it->adjlist);

it->adjlist = NULL;

}

adjs.clear();

pivot_st = pivot_en;

}

/**

* Extend the interval of pivot vertices to en.

void extend_pivotrange(vid_t en) {

assert(en>=pivot_en);

pivot_en = en;

adjs.resize(pivot_en - pivot_st);

}

/**

* Grab pivot's adjacency list into memory.

int grab_adj(graphchi_vertex<uint32_t, uint32_t> &v) {

if(is_pivot(v.id())) {

int ncount = v.num_edges();

// Count how many neighbors have larger id than v

v.sort_edges_indirect();

int actcount = 0;

vid_t lastvid = 0;

for(int i=0; i<ncount; i++) {

if (v.edge(i)->vertexid > v.id() && v.edge(i)->vertexid != lastvid)

actcount++; // Need to store only ids larger than me

lastvid = v.edge(i)->vertex_id();

}

// Allocate the in-memory adjacency list, using the

// knowledge of the number of edges.

dense_adj dadj = dense_adj(actcount, (vid_t*) calloc(sizeof(vid_t), actcount));

actcount = 0;

lastvid = 0;

for(int i=0; i<ncount; i++) {

if (v.edge(i)->vertexid > v.id() && v.edge(i)->vertexid != lastvid) { // Need to store only ids larger than me

dadj.adjlist[actcount++] = v.edge(i)->vertex_id();

}

lastvid = v.edge(i)->vertex_id();

}

assert(dadj.count == actcount);

adjs[v.id() - pivot_st] = dadj;

assert(v.id() - pivot_st < adjs.size());

__sync_add_and_fetch(&grabbed_edges, actcount);

return actcount;

}

return 0;

}

int acount(vid_t pivot) {

return adjs[pivot - pivot_st].count;

}

/**

* Compute size of the relevant intersection of v and a pivot

int intersection_size(graphchi_vertex<uint32_t, uint32_t> &v, vid_t pivot, int start_i) {

assert(is_pivot(pivot));

int count = 0;

if (pivot > v.id()) {

dense_adj &dadj = adjs[pivot - pivot_st];

int vc = v.num_edges();

/**

* If the adjacency list sizes are not too different, use

* 'merge'-type of operation to compute size intersection.

if (dadj.count < 32 * (vc - start_i)) { // TODO: do real profiling to find best cutoff value

// Do merge-style of check

assert(v.edge(start_i)->vertex_id() == pivot);

int i1 = 0;

int i2 = start_i+1;

int nedges = v.num_edges();

while (i1 < dadj.count && i2 < nedges) {

vid_t dst = v.edge(i2)->vertexid;

vid_t a = dadj.adjlist[i1];

if (a == dst) {

/* Add one to edge between v and the match */

v.edge(i2)->set_data(v.edge(i2)->get_data() + 1);

count++;

i1++; i2++;

} else {

i1 += a < dst;

i2 += a > dst;

}

} else {

/**

* Otherwise, use linear/binary search.

vid_t lastvid = 0;

for(int i=start_i+1; i < vc; i++) {

vid_t nb = v.edge(i)->vertexid;

if (nb > pivot && nb != lastvid) {

int match = findadj(dadj.adjlist, dadj.count, nb);

count += match;

if (match > 0) {

/* Add one to edge between v and the match */

v.edge(i)->set_data(v.edge(i)->get_data() + 1);

}

lastvid = nb;

}

return count;

}

inline bool is_pivot(vid_t vid) {

return vid >= pivot_st && vid < pivot_en;

}

};

adjlist_container * adjcontainer;

/**

* GraphChi programs need to subclass GraphChiProgram<vertex-type, edge-type>

* class. The main logic is usually in the update function.

struct TriangleCountingProgram : public GraphChiProgram<VertexDataType, EdgeDataType> {

/**

* Vertex update function.

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

if (gcontext.iteration % 2 == 0) {

adjcontainer->grab_adj(v);

} else {

uint32_t oldcount = v.get_data();

uint32_t newcounts = 0;

v.sort_edges_indirect();

vid_t lastvid = 0;

/**

* Iterate through the edges, and if an edge is from a

* pivot vertex, compute intersection of the relevant

* adjacency lists.

for(int i=0; i<v.num_edges(); i++) {

graphchi_edge<uint32_t> * e = v.edge(i);

if (e->vertexid > v.id() && e->vertexid >= adjcontainer->pivot_st) {

assert(!is_deleted_edge_value(e->get_data()));

if (e->vertexid != lastvid) { // Handles reciprocal edges (a->b, b<-a)

if (adjcontainer->is_pivot(e->vertexid)) {

uint32_t pivot_triangle_count = adjcontainer->intersection_size(v, e->vertexid, i);

newcounts += pivot_triangle_count;

/* Write the number of triangles into edge between this vertex and pivot */

if (pivot_triangle_count == 0 && e->get_data() == 0) {

/* ... or remove the edge, if the count is zero. */

v.remove_edge(i);

} else {

e->set_data(e->get_data() + pivot_triangle_count);

}

} else {

break;

}

lastvid = e->vertexid;

}

assert(newcounts >= 0);

}

if (newcounts > 0) {

v.set_data(oldcount + newcounts);

}

/* Collect triangle counts matched by vertices with id lower than

his one, and delete */

if (gcontext.iteration % 2 == 0) {

int newcounts = 0;

for(int i=0; i < v.num_edges(); i++) {

graphchi_edge<uint32_t> * e = v.edge(i);

if (e->vertexid < v.id()) {

newcounts += e->get_data();

e->set_data(0);

// This edge can be now deleted. Is there some other situations we can delete?

if (v.id() < adjcontainer->pivot_st && e->vertexid < adjcontainer->pivot_st) {

v.remove_edge(i);

}

v.set_data(v.get_data() + newcounts);

}

/**

* Called before an iteration starts.

void before_iteration(int iteration, graphchi_context &gcontext) {

if (gcontext.iteration % 2 == 0) {

// Schedule vertices that were pivots on last iteration, so they can

// keep count of the triangles counted by their lower id neighbros.

for(vid_t i=adjcontainer->pivot_st; i < adjcontainer->pivot_en; i++) {

gcontext.scheduler->add_task(i, true);

}

grabbed_edges = 0;

adjcontainer->clear();

} else {

// Schedule everything that has id < pivot

logstream(LOG_INFO) << "Now pivots: " << adjcontainer->pivot_st << " " << adjcontainer->pivot_en << std::endl;

for(vid_t i=0; i < gcontext.nvertices; i++) {

if (i < adjcontainer->pivot_en) {

gcontext.scheduler->add_task(i, true);

}

/**

* Called after an iteration has finished.

void after_iteration(int iteration, graphchi_context &gcontext) {

}

/**

* Called before an execution interval is started.

* On every even iteration, we store pivot's adjacency lists to memory.

* Here we manage the memory to ensure that we do not load too much

* edges into memory.

void before_exec_interval(vid_t window_st, vid_t window_en, graphchi_context &gcontext) {

if (gcontext.iteration % 2 == 0) {

if (adjcontainer->pivot_st <= window_en) {

size_t max_grab_edges = get_option_long("membudget_mb", 1024) * 1024 * 1024 / 8;

if (grabbed_edges < max_grab_edges * 0.8) {

logstream(LOG_DEBUG) << "Window init, grabbed: " << grabbed_edges << " edges" << std::endl;

for(vid_t vid=window_st; vid <= window_en; vid++) {

gcontext.scheduler->add_task(vid, true);

}

adjcontainer->extend_pivotrange(window_en + 1);

if (window_en == gcontext.nvertices) {

// Last iteration needed for collecting last triangle counts

gcontext.set_last_iteration(gcontext.iteration + 3);

}

} else {

std::cout << "Too many edges, already grabbed: " << grabbed_edges << std::endl;

}

/**

* Called after an execution interval has finished.

void after_exec_interval(vid_t window_st, vid_t window_en, graphchi_context &gcontext) {

}

};

int main(int argc, const char ** argv) {

/* GraphChi initialization will read the command line

arguments and the configuration file. */

graphchi_init(argc, argv);

/* Metrics object for keeping track of performance counters

and other information. Currently required. */

metrics m("triangle-counting");

/* Basic arguments for application */

std::string filename = get_option_string("file"); // Base filename

int niters = 100000; // Automatically determined during running

bool scheduler = true;

/* Preprocess the file, and order the vertices in the order of their degree.

Mapping from original ids to new ids is saved separately. */

int nshards = convert_if_notexists_novalues<EdgeDataType>(filename,

get_option_string("nshards", "auto"));

if (nshards == 1) {

logstream(LOG_FATAL) << "Triangle counting does not work in in-memory mode. Please set --nshards=2" << std::endl;

exit(1);

}

assert(nshards > 1);

nshards = order_by_degree<EdgeDataType>(filename, nshards, m);

/* Initialize adjacency container */

adjcontainer = new adjlist_container();

// TODO: ordering by degree.

/* Run */

TriangleCountingProgram program;

graphchi_dynamicgraph_engine<VertexDataType, EdgeDataType> engine(filename + "_degord",

nshards, scheduler, m);

engine.set_enable_deterministic_parallelism(false);

// Low memory budget is required to prevent swapping as triangle counting

// uses more memory than standard GraphChi apps.

engine.set_membudget_mb(std::min(get_option_int("membudget_mb", 1024), 1024));

engine.run(program, niters);

/* Report execution metrics */

metrics_report(m);

/* Count triangles */

size_t ntriangles = sum_vertices<vid_t, size_t>(filename + "_degord", 0, (vid_t)engine.num_vertices());

std::cout << "Number of triangles: " << ntriangles / 3 << "(" << ntriangles << ")" << std::endl;

/* If run as a test, see the number matches */

size_t expected = get_option_long("assertequals", 0);

if (expected > 0) {

std::cout << "Testing the result is as expected: " << (ntriangles / 3) << " vs. " << expected << std::endl;

assert(expected == ntriangles / 3);

}

/* write the output */

// OutputVertexCallback callback;

// foreach_vertices<VertexDataType>(filename + "_degord", 0, engine.num_vertices(), callback);

return 0;

}

graphchi-cpp/example_apps/trianglecounting.cpp at master · GraphChi/graphchi-cpp · GitHub

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