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be needed. Arriving at the answer through experimentation
isn’t a good approach, because that assumes -- chicken-and-egg problem -- that
we have already arrived at an optimal configuration.
-- Does GraphX connected-components performance degrade slowly or
catastrophically when that memory limit
t 00:13, John Lilley <john.lil...@redpoint.net> wrote:
> Greetings,
>
> We are looking into using the GraphX connected-components algorithm on
> Hadoop for grouping operations. Our typical data is on the order of
> 50-200M vertices with an edge:vertex ratio between 2 and 30. Whi
Greetings,
We are looking into using the GraphX connected-components algorithm on Hadoop
for grouping operations. Our typical data is on the order of 50-200M vertices
with an edge:vertex ratio between 2 and 30. While there are pathological cases
of very large groups, they tend to be small. I
respectively.
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been 7,3
(5,3)-OK
(2,0)-OK
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on how to get
stronglyconnected nodes .Pls help in completing this code/
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Manning Publications Co.
http://www.manning.com/malak/ http://www.manning.com/malak/
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Hey all,
I’m trying to run connected components in graphx on about 400GB of data on 50
m3.xlarge nodes on emr. I keep getting java.nio.channels.CancelledKeyException
when it gets to mapPartitions at VertexRDD.scala:347”. I haven’t been able to
find much about this online, and nothing that
Hey all,
I’m currently trying to run connected components using GraphX on a large graph
(~1.8b vertices and ~3b edges, most of them are self edges where the only edge
that exists for vertex v is v-v) on emr using 50 m3.xlarge nodes. As the
program runs I’m seeing each iteration take longer and
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