Hi Heather,
Please check this issue https://issues.apache.org/jira/browse/SPARK-4672. I
think you can solve this problem by checkpointing your data every several
iterations.
Hope that helps.
Best regards,
Baoxu(Dash) Shi
Computer Science and Engineering Department
University of Notre Dame
Problem solved. A simple join will do the work
val prefix = new PairRDDFunctions[Int, Set[Int]](sc.parallelize(List((9,
Set(4)), (1,Set(3)), (2,Set(5)), (2,Set(4)
val suffix = sc.parallelize(List((1, Set(1)), (2, Set(6)), (2, Set(5)), (2,
Set(7
prefix.join(suffix).collect().foreach(print
Hey Spark gurus! Sorry for the confusing title. I do not know the exactly
description of my problem, if you know please tell me so I can change it :-)
Say I have two RDDs right now, and they are
val rdd1 = sc.parallelize(List((1,(3)), (2,(5)), (3,(6
val rdd2 = sc.parallelize(List((2,(1)), (2,
Hello everyone,
I am trying out Spark for the first time, and after a month of work - I am
stuck with an issue. I have a very simple program that, given a directed
Graph with nodes/edges parameters and a particular node, tries to figure out
all the siblings(in the traditional sense) of the given n
Don’t know why the setting does not appear in the last mail:
.set("spark.serializer", "org.apache.spark.serializer.KryoSerializer")
.set("spark.kryo.registrator", new HDTMKryoRegistrator().getClass.getName)
On Jul 2, 2014, at 1:03 PM, dash wrote
Hi, I'm using Spark 1.1.0 standalone with 5 workers and 1 driver, and Kryo
settings are
When I submit this job, the driver works fine but workers will throw
ClassNotFoundException saying they can not found HDTMKryoRegistrator.
Any idea about this problem? I googled this but there is only one p
Hi Bin,
VD and ED are ClassTags, you could treat them as placeholder, or template T in
C (not 100% clear).
You do not need convert graph[String, Double] to Graph[VD,ED].
Check ClassTag’s definition in Scala could help.
Best,
On Jul 1, 2014, at 4:49 AM, Bin WU wrote:
> Hi all,
>
> I am a ne
I’m facing the same situation. It would be great if someone could provide a
code snippet as example.
On Jun 28, 2014, at 12:36 PM, Nilesh Chakraborty wrote:
> Hello,
>
> In a thread about "java.lang.StackOverflowError when calling count()" [1] I
> saw Tathagata Das share an interesting approac
Hi Pei-Lun,
I have the same problem there. The Issue is SPARK-2228, there also someone
posted a pull request on that, but he only eliminate this exception but not the
side effects.
I think the problem may due to the hard-coded private val
EVENT_QUEUE_CAPACITY = 1
in core/src/main/scala/
I'm trying to workaround the StackOverflowError when an object have a long
dependency chain, someone said I should use checkpoint to cuts off
dependencies. I write a sample code to test it, but I can only checkpoint
edges but not vertices. I think I do materialize vertices and edges after
calling c
= false)
currentGraph.edges.unpersist(blocking = false)
currentGraph = g
println(" iter "+i+" finished")
}
}
Baoxu Shi(Dash)
Computer Science and Engineering Department
University of Notre Dame
b...@nd.edu
> On Jun 19, 2014, at 1:47 AM, roy20021 [via Apache Spark U
If a RDD object have non-empty .dependencies, does that means it have
lineage? How could I remove it?
I'm doing iterative computing and each iteration depends on the result
computed in previous iteration. After several iteration, it will throw
StackOverflowError.
At first I'm trying to use cache,
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