Hi,
I am trying to understand what's the intermediate caching support in Flink.
For example, when there's an iterative dataset what's being cached between
iterations. Is there some documentation on this?
Thank you,
Saliya
--
Saliya Ekanayake
Ph.D. Candidate | Research Assistant
School of Inform
Hello Chen,
you can access the set configuration in your rich function like this:
|public static final class Tokenizer extends RichFlatMapFunctionTuple2> { @Override public void flatMap(String value,
Collector> out) { ParameterTool parameters =
(ParameterTool)
getRuntimeContext().getExecution
Hi,
I Need some assistance -
I’m trying to globally register arguments from my main function for further
extraction on stream processing nodes. My code base is Scala:
val env = StreamExecutionEnvironment.getExecutionEnvironment
val parameterTool = ParameterTool.fromArgs(args)
env.getConfig.set
well now i know what the problem could be.
You are trying to execute a job on a cluster (== not local), but have
set the local flag to true.
env.execute(local=True)
Due to this flag the files are only copied into the tmp directory of the
node where you execute the plan, and are thus not a
I haven't yet figured out how to write a Java job to test DistributedCache
functionality between machines; I've only gotten worker nodes to create
caches from local files (on the same worker nodes), rather than on files
from the master node. The DistributedCache test I've been using (based on
the D
Please also post the job you're trying to run.
On 17.07.2016 08:43, Geoffrey Mon wrote:
The Java program I used to test DistributedCache was faulty since it
actually created the cache from files on the machine on which the
program was running (i.e. the worker node).
I tried implementing a clu
Does this mean the revised DistributedCache job run successfully?
On 17.07.2016 08:43, Geoffrey Mon wrote:
The Java program I used to test DistributedCache was faulty since it
actually created the cache from files on the machine on which the
program was running (i.e. the worker node).
I tried
