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Automatically exported from code.google.com/p/graphchi
If GraphChi uses multiple disks, also vertex data needs to be read in a striped
fashion.
Original issue reported on code.google.com by [email protected]
on 27 Jun 2012 at 3:02
LPAm is a more advanced community detection algorithm based on label
propagation. It requires a community count to be recomputed on every iteration.
This should be relatively easy with the aggregators.
Original issue reported on code.google.com by [email protected]
on 1 Jul 2012 at 4:16
Now if in-edges are not properly commited, the test can still succeed.
Original issue reported on code.google.com by [email protected]
on 30 Jun 2012 at 9:15
All current example apps initialize their vertex data in the update function,
on first iteration. For some applications, such as common in belief
propagation, vertices have predefined values. This is easy to accomplish in
GraphChi: simply write the [file-prefix].vout file before running the
application. This file is just a flat binary array.
However, it would be useful to have a tool to parse a text file into the vertex
data file, at least to show an example.
Original issue reported on code.google.com by [email protected]
on 27 Jun 2012 at 4:32
Currently it is required that all edge values are of same type and size. For
some algorithms, it might be that some edges need more data than others. It is
fairly easy to accomplish this by writing a size-word and perhaps a type-byte
before each edge data value. However, this means that edge data must be loaded
synchronously with adjacency data as we could not just compute the pointers.
How to implement different types or variable size containers cleanly in the C++
code is a question.
Original issue reported on code.google.com by [email protected]
on 27 Jun 2012 at 4:35
What is the expected output? What do you see instead?
1.the output should tell us which community the node is belong to ,not only
community-ids and their sizes,and it is hard to identify which nodes the
community includes,which make it difficult to analysis the feature of the
community due to lake of information about the nodes in it.
2.moreover,the output includes some other files (as attached below,file 0 to
15,here only 0 and 3 for example)which cannot read. what do they really mean?
What version of the product are you using? On what operating system?
graphchi on ubuntu 12.0.4
Original issue reported on code.google.com by [email protected]
on 30 Oct 2013 at 6:27
Seems gzip or bzip2 can compress even a pagerank edge file very significantly
Original issue reported on code.google.com by [email protected]
on 9 Aug 2012 at 10:34
Similar to how ALS works. In the beginning of the app, check if shards have
been created, and if not, create them.
Original issue reported on code.google.com by [email protected]
on 27 Jun 2012 at 4:40
What steps will reproduce the problem?
1. Write a program that uses dynamic vertex data.
2. Run it on a big graph with many iterations (depends on the size of the graph
and the available memory).
3. Observe the segfault that is caused by the memory leak.
What is the expected output? What do you see instead?
Our code ran on a graph with about 5000 vertices. We have discovered two memory
leaks:
- at dynamicblock.hpp:106, which resulted in a loss of 37MB (valgrind.1)
- at graphchi_engine.hpp:992, which leaked about 230kB (valgrind.2)
What version of the product are you using? On what operating system?
Latest trunk.
Please provide any additional information below.
I have attached our fixes (patch).
Original issue reported on code.google.com by [email protected]
on 16 Jul 2013 at 3:05
Attachments:
If dynamic scheduling is disabled, engine should use a mock-scheduler instead
of having a null scheduler.
- Add "selective_scheduling" to graphchi_context
Original issue reported on code.google.com by [email protected]
on 3 Jul 2012 at 7:06
Requested by two users..
Original issue reported on code.google.com by [email protected]
on 18 Nov 2012 at 8:40
What steps will reproduce the problem?
1. bin/exampleapps/pagerank file pagerank2.txt
2.
3.
What is the expected output? What do you see instead?
top vertices
What version of the product are you using? On what operating system?
Using 0.1b of graphchi on Mac OSX 10.5.6
Please provide any additional information below.
Original issue reported on code.google.com by [email protected]
on 2 Aug 2012 at 1:01
Attachments:
We should convert static allocation to dynamic using command line argument
specification of feature width
Original issue reported on code.google.com by [email protected]
on 9 Nov 2012 at 11:02
Make smoketest for the dynamic graph
Original issue reported on code.google.com by [email protected]
on 30 Jun 2012 at 7:16
do you have plan to develop a version for windows?
Original issue reported on code.google.com by [email protected]
on 28 Aug 2012 at 11:20
What steps will reproduce the problem?
1. using sparse matrix available at
https://raw.github.com/gist/3422269/e0a585749a3a9ae84003fc368e80b69398a30d22/gis
tfile1.txt
2. ./bin/als training lsa_test.mm
What is the expected output? What do you see instead?
expected decomposition, instead got assertion failure.
for full output see https://gist.github.com/3422275
What version of the product are you using? On what operating system?
setup as described
http://bickson.blogspot.co.at/2012/08/collaborative-filtering-with-graphchi.html
?m=1
Original issue reported on code.google.com by [email protected]
on 22 Aug 2012 at 4:27
In some cases we assume that vertex-ids can be converted to 32-bit signed
integers. At least in the sliding-shards jump-index.
Fix and test with 4B vertices!
Original issue reported on code.google.com by [email protected]
on 2 Jul 2012 at 2:59
It should be easy to write code to aggregate vertex values efficiently.
Original issue reported on code.google.com by [email protected]
on 26 Jun 2012 at 10:48
Html-based admin is nice.
Original issue reported on code.google.com by [email protected]
on 27 Jun 2012 at 4:32
What is the expected output? What do you see instead?
1.the output should tell us which community the node is belong to ,not only
community-ids and their sizes,and it is hard to identify which nodes the
community includes,which make it difficult to analysis the feature of the
community due to lake of information about the nodes in it.
2.moreover,the output includes some other files (as attached below,file 0 to
15,here only 0 and 3 for example)which cannot read. what do they really mean?
What version of the product are you using? On what operating system?
graphchi on ubuntu 12.0.4
Original issue reported on code.google.com by [email protected]
on 30 Oct 2013 at 6:27
Port GaBP code to graphchi linear solvers toolkit. Requested by Ori Shental.
Original issue reported on code.google.com by [email protected]
on 9 Nov 2012 at 11:20
Create a wrapper/API to run Graphlab v2.1 vertex programs.
Assume that vertices are stored in memory, not replicated to edges. This will
enable most graphlab apps to run without modification, although the memory
consumption will be higher than on normal GraphChi applications.
Original issue reported on code.google.com by [email protected]
on 27 Jun 2012 at 4:38
I think we can avoid initialization on first iteration by being smarter when
reading the edges.
Original issue reported on code.google.com by [email protected]
on 29 Jun 2012 at 10:26
If user has plenty of memory available, it is good idea to pin some shards to
memory, so they need not to be reprocessed from disk.
Original issue reported on code.google.com by [email protected]
on 27 Jun 2012 at 4:33
... which builds all example apps.
Original issue reported on code.google.com by [email protected]
on 27 Jun 2012 at 4:36
I tried to build the sharder_basic program with the latest download and it
failed with this error:
g++ -g -O3 -I/usr/local/include/ -I./src/ -fopenmp -Wall -Wno-strict-aliasing
src/preprocessing/sharder_basic.cpp -o bin/sharder_basic
In file included from ./src/preprocessing/conversions.hpp:36,
from src/preprocessing/sharder_basic.cpp:35:
./src/preprocessing/sharder.hpp: In member function ‘virtual void
graphchi::sharder<EdgeDataType>::write_shards()’:
./src/preprocessing/sharder.hpp:465: error: ‘degree’ was not declared in
this scope
./src/preprocessing/sharder.hpp:467: error: ‘degrees’ was not declared in
this scope
./src/preprocessing/sharder.hpp:469: error: expected primary-expression before
‘)’ token
./src/preprocessing/sharder.hpp:469: error: expected `;' before ‘calloc’
make: *** [sharder_basic] Error 1
Including the degree_data header seemed to fix this and I was able to build and
run basic_sharder after this
#include "engine/auxdata/degree_data.hpp"
Original issue reported on code.google.com by [email protected]
on 13 Jan 2013 at 3:16
Requested by a few users..
Original issue reported on code.google.com by [email protected]
on 18 Nov 2012 at 8:41
Looking at this code snippet from example_apps/pagerank.cpp
-- -- >8 -- -- >8 -- -- >8 -- -- >8 -- -- >8 -- -- >8 -- -- >8
#define RANDOMRESETPROB 0.15
// ...
struct PagerankProgram :
public GraphChiProgram<VertexDataType,
EdgeDataType> {
// ...
void update(graphchi_vertex<VertexDataType, EdgeDataType> &v,
graphchi_context &ginfo) {
float sum=0;
// ...
for(int i=0; i < v.num_inedges(); i++) {
float val = v.inedge(i)->get_data();
sum += val;
}
/* Compute my pagerank */
float pagerank = RANDOMRESETPROB + (1 - RANDOMRESETPROB) * sum;
// ...
}
}
-- -- >8 -- -- >8 -- -- >8 -- -- >8 -- -- >8 -- -- >8 -- -- >8
looks like that the current pagerank implementation doesn't
allow you to set the "personalisation vector" to anything different
than a uniform probability vector. I mean, if the pagerank equation
in matrix form is
p = (1-c) * A * p + c * V
where:
p is the pagerank vector, N compontents (N is the size of the web)
c is the probability of jumping to a random page no matter the outlinks
from current location
A is the transition matrix, N-by-N, if you see a random walk on the web
as a Markov chain
V is a N-vector, where V_i is the probability of random-jumping to page i
(side note: I am not normalizing by N, i.e. all probabilities sum up to N
and not to 1)
well, given all of this, in the current implementation of GraphChi pagerank
V is a uniform probability vectory = [1, 1, 1, ..., 1].
A jump to every page is equally likely to happen, no matter the page.
After this wall of text I come to my point:
could a non trivial "personalisation vector" be implemented?
I'd like to be able to set V myself.
Is this in the priorities of the GraphChi team?
Cheers,
Original issue reported on code.google.com by [email protected]
on 12 Feb 2013 at 10:20
Currently deleted edges are not reflected until the window has passed.
Original issue reported on code.google.com by [email protected]
on 2 Jul 2012 at 3:45
What steps will reproduce the problem?
bin/example_apps/pagerank file GRAPH-NAME
What is the expected output? What do you see instead?
What version of the product are you using? On what operating system?
linux
Please provide any additional information below.
my graph:
1 2
1 3
1 4
2 4
3 4
3 5
4 5
5 4
top 20 vertices:
1. 5 0.604059
2. 4 0.437937
3. 2 0.1925
4. 3 0.1925
5. 0 0.15
6. 1 0.15
7. 6 0.15
Original issue reported on code.google.com by [email protected]
on 8 Aug 2012 at 5:45
If file was adjacency, but try to read with edgelist format -> segfault.
Original issue reported on code.google.com by [email protected]
on 28 Jun 2012 at 5:08
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