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492 lines (411 loc) · 17 KB
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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);
register size_t lo = 0;
register size_t hi = n;
register size_t m = lo + (hi-lo)/2;
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;
}
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