I have a cluster having Cloudera CDH running. I need to connect my R programs (running on my Laptop) to the Spark running in cluster.
However If I try to connect the local R through Sparklyr, it is giving Error. As it is searching the Spark home on the laptop itself means i have to install spark on my laptop but i can't do it.
I googled and found we can install SparkR and use R with Spark. However, for using sparkR what i have to do:
install SparkR on all nodes of cluster?
How to configure to use SparkR?
Related
I am new to cloud computing and GCP. I am trying to create a notebook instance running R with a GPU. I got a basic instance with 1 core and 0 GPUs to start and I was able to execute some code which was cool. When I try to create an instance with a GPU I keep getting all sorts of errors about something called live migration, or that there are no resources available, etc. Can someone tell me how to start an R notebook instance with a GPU? It can't be this difficult.
The CRAN (The Comprehensive R Archive Network) doesn't support GPU. However, you can follow this link might help you to install a Notebook instance running R with a GPU. You need a machine with Nvidia GPU drivers installed then install R and Jupyter Lab. After that compile those R packages which require it for use with GPU's.
How to install cloudera in local system .I'm using centos 6.5.And also I want to do clustering in cloudera .Any one suggest me some documentation to this process properly
You can either use VM or Docker. Please follow the instructions here to get it installed locally.
I know how to access packages in R scripts in Azure machine learning by either using the Azure supported ones or by zipping up the packages.
My problem now is that Azure machine learning does not support the h2o package and when I tried using the zipped file - it gave an error.
Has anyone figured out how to use h2o in R in Azure machine learning?
So since there was no reply to my question, I made some research and came up with the following:
H2O cannot be ran in a straightforward manner in Azure machine learning embedded R scripts. A workaround the problem is to consider using an Azure created environment - specially for H2O. The options available are:
Spinning up an H2O Artificial Intelligence Virtual Machine solution
Using an H2O application for HDInsight
For more reading, you can go to: http://docs.h2o.ai/h2o/latest-stable/h2o-docs/azure.html
I have a use case where I have revolution R on my desktop and want to invoke/talk to spark and spark sql deployed in a hadoop cluster(also have sparkR installed there).Any suggestions on how to proceed on this.I heard it can be done if spark is in stand alone mode.But I want with sparn in yarn mode.
You can checkout the sparkR package. This also helps in connecting to the Spark SQL as you had required
https://spark.apache.org/docs/1.5.1/sparkr.html
I am trying to connect R to a Hadoop cluster using R. The cluster has HDFS, Map Reduce, Hive, Pig and Sqoop installed on it.
R will be running on in the Windows environment. I know that rhdfs, rhadoop and rmr exist for Linuix, but I can't find anything on Windows.
Does anyone know of a library to use?
Thank you
Revolution Analytrics is trying to make a name for themselves in this space. They have a couple of nice packages (some of which are open-source and/or free for non-commercial use) which allow you to interact with Hadoop from R in a Windows environment fluidly.