FAQ / Known issues¶
Does Anaconda for cluster management work with a cluster that already has a managed Spark/Hadoop stack?
Yes, Anaconda for cluster management can be installed alongside enterprise Hadoop distributions such as Cloudera CDH or Hortonworks HDP and can be used to manage Python and R conda packages and environments across a cluster.
Does Anaconda for cluster management offer integration with Anaconda Repository or Anaconda Cloud?
Yes, conda packages can be installed from Anaconda Repository or Anaconda Cloud by using channel specifications. Refer to the documentation regarding Installing packages from channels for more details.
Which cloud providers does Anaconda for cluster management support?
Currently Anaconda for cluster management offers full support for Amazon Elastic Compute Cloud (EC2). Other providers such as Microsoft Azure, Google Cloud Platform, Rackspace, and others are on our roadmap. If you are interested in a cloud provider that is not listed here, please contact us at firstname.lastname@example.org.
Can I use Anaconda for cluster management with a different cloud provider?
Yes, you can manually create instances on another cloud provider, then provision the nodes as if you were using a bare-metal cluster. Refer to the Bare-metal Cluster Setup documentation for more information.
Does Anaconda for cluster management support Amazon EMR?
Anaconda for cluster management does not support Amazon Elastic MapReduce (EMR), which provides a managed Hadoop framework in the cloud. Anaconda for cluster management can be used to manage conda packages and environments across a cluster. Anaconda for cluster management does support Amazon EC2.
Which versions of Python does Anaconda for cluster management support?
Some of the plugins have dependencies that require the use of Python 2. Therefore, by default, Anaconda for cluster management installs Miniconda with Python 2 into the root conda environment.
However, you can easily create a new conda environment on the cluster with Python 3, or you can specify a different root version of Anaconda/Miniconda in the profile.
Which network ports need to be accessible from the client machine and cluster nodes?
From the client machine to the cluster nodes, you will need access to ports 22, 4505, and 4506 to provision the cluster via SSH and Salt. For communication between the cluster nodes, Salt uses ports 4505 and 4506.
Can I use Anaconda for cluster management with iptables and SElinux?
Yes, you can customize the security behavior of Anaconda for cluster management when creating or provisioning a cluster using the Security settings in the profile. Refer to the Profile settings documentation for more information.
Errors when creating or provisioning a cluster
Verify the following:
- The contents of your SSH private key are correct (and set to
600permissions on Mac/Linux)
- The user name in your profile (e.g.,
user: ubuntu) is defined correctly
- Profile settings are defined correctly in
- Provider settings are defined correctly in
No matching SLS error (Salt)
When installing a plugin during cluster creation/provisioning or using the
acluster install command, you might receive an error similar to:
============================= Standard output ============================= ip-10-144-206-102.ec2.internal: - No matching sls found for 'cdh5.hdfs' in env 'base' =========================================================================== Fatal error: One or more hosts failed while executing task 'parallel_sudo' Aborting. One or more hosts failed while executing task 'parallel_sudo'
This is a known issue with Salt that periodically occurs. You can reprovision or reinstall the plugin that failed, and the installation should succeed.
Theading error when creating a cluster
When creating/provisioning a cluster, you might receive an error similar to:
Uploading formulas INFO: Uploading formulas to head Syncing formulas INFO: Syncing formulas across the cluster Done Exception in thread Thread-6 (most likely raised during interpreter shutdown): Exception in thread Thread-8 (most likely raised during interpreter shutdown):
This is a known issue with Paramiko/Fabric. You can safely disregard this message. This issue was resolved in Anaconda for cluster management 1.3.1.