cluster-computing

问题 I want to build a RabbitMQ system which is able to scale out for the sake of performance. I've gone through the official document of RabbitMQ Clustering. However, its clustering doesn't seem to support scalability. That's because only through master queue we can publish/consume, even though the master queue is reachable from any node of a cluster. Other than the node on which a master queue resides, we can't process any publish/consume. Why do we cluster then? 回答1: Why do we cluster then? To

问题 I am executing the job as: hadoop/bin/./hadoop jar /home/hadoopuser/hadoop/share/hadoop/tools/lib/hadoop-streaming-2.6.0.jar -D mapred.reduce.tasks=2 -file kmeans_mapper.py -mapper kmeans_mapper.py -file kmeans_reducer.py \ -reducer kmeans_reducer.py -input gutenberg/small_train.csv -output gutenberg/out When the two reducers are done, I would like to do something with the results, so ideally I would like to call another file (another mapper?) which would receive the output of the reducers as

问题 I now have a Ray cluster working on EC2 (Ubuntu 16.04) with a c4.8xlarge master node and one identical worker. I wanted to check whether multi-threading was being used, so I ran tests to time increasing numbers (n) of the same 9-second task. Since the instance has 18 CPUs, I expected to see the job taking about 9s for up to n<=35 (assuming one CPU for the cluster management) and then either a fault, or an increase to about 18 sec when switching to 36 vCPUs per node. Instead, the cluster

问题 I tried to deploy a Cassandra Cluster using Google Compute Engine, no success. I tried several times, the error was always the same: module: DEPLOYMENT_FAILED Replica module-1234 failed with status PERMANENTLY_FAILING: Replica State changed to PERMANENTLY_FAILING. Replica was unhealthy 2 consecutive times. After following this short troubleshooting guidelines: https://cloud.google.com/solutions/cassandra/click-to-deploy#troubleshooting, the log is the following: antoniogallo88_gmail_com

问题 A few days ago I opened this thread: Clustering rows by group based on column value In which we obtained this result: df <- data.frame(ID = c(1,1,1,1,1,1,1,1,1,1,1, 1, 1,1,1,1,1), Obs1 = c(1,1,0,1,0,1,1,0,1,0,0,0,1,1,1,1,1), Control = c(0,3,3,1,12,1,1,1,36,13,1,1,2,24,2,2,48), ClusterObs1 = c(1, 1, 1, 2, 2, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5, 5, 5)) With: df <- df %>% group_by(ID) %>% mutate_at(vars(Obs1), funs(ClusterObs1= with(rle(.), rep(cumsum(values == 1), lengths)))) Now I have to make some

问题 I have an .ear file which is composed of multiple EJB's and one of them do use a timer service to create timer and the same ejb has the callback method too. That ear is supposed to be deployed in a clustered environment of 3 servers. The issue now is that i want to know what is the expected behavior if i redeployed/undeployed the ear in the cluster. Will the server cancel all timers and clear the persistent scheduler? Or it will preserve them? What are the work arounds? I have read that in

问题 I am trying to figure out how this will work out: client-server communication via NIO/BIO Server-server communication (replication, membership etc) via JGroups (replication of data can be a pain?) What are your suggestion, pros/cons of using such an architecture, why go for jgroups, any alternatives? Should I go with native NIO or use some libraries like Mina or Netty? Update No REST, it's not a web server. I am building a dynamo like distributed database. activeMQ is like JMS I think, where

问题 I created a cluster according to AWS' tutorials and it supposed to be working just fine but when I try to connect to it, I get the following error java.io.IOException: failed to configure cluster endpoints from hosts: [mydaxcluster.ximfba.clustercfg.dax.use1.cache.amazonaws.com:8111] at com.amazon.dax.client.cluster.Source$AutoconfSource.pull(Source.java:128) ~[DaxJavaClient-latest.jar:1.0.792.0] at com.amazon.dax.client.cluster.Source$AutoconfSource.update(Source.java:60) ~[DaxJavaClient

问题 I'm looking for advise on the 'right way' to authenticate interconnecting node.js applications. The use case is general: to share work tasks, sync data or for a control/monitoring channel. Databases have authentication, but what about the applications themselves? What's the risk of intruders (from outside or on the network) to abuse your internal connections? Does it happen? I find lot of cluster cooperation modules ranging from using raw sockets to like zeromq, but the examples never really

问题 Here is my pbs file: #!/bin/bash #PBS -N myJob #PBS -j oe #PBS -k o #PBS -V #PBS -l nodes=hpg6-15:ppn=12 cd ${PBS_O_WORKDIR} ./mycommand On qsub documentation page, it seems like if I put the line PBS -k o , I should be able to check the real time output in a file named myJob.oJOBID in my home dir. However when I check the output by tail -f or cat or more in runtime, it shows nothing in the file. Only when I terminated the job, then the file would show the output. Is there anything I should