I don't understand the basic mechanism of machine learning and deep learning at all, so I took this opportunity to try to search for relevant information.
This article attempts to analyze how the XGBoost demo is implemented in CDSW from the perspective of CDSW users without ML/DL knowledge.
While searching for related information on Cloudera, I also discovered how ML/DL workloads are handled on Google Cloud DataProc. I will also try to make a comparison with CDSW.
This article attempts to introduce how to forward the Kubernetes Service to the host node, and how to connect to the Cloudera CDSW database and modify the user's password.
This article records a troubleshooting about CDSW unable to start Session. The reason for the problem involved is that the remaining capacity of nodefs and imagefs used by Kubelet has reached the threshold of evicting the node, resulting in the node being labeled as NoSchedule taint by Kubernetes.
Purpose of this artical:
Our purpose is to replace the nodes of Kafka Broker.
We have 2 nodes newly added to the CDP PvC Base cluster.
We will migrate two Kafka Brokers that were originally in use to these two new nodes.
This article uses Cloudera CDP official documentation as a guide.
cdsw logs output If we run cdsw logs on the CDSW Master node, we’ll see output as below:
Generating Cloudera Data Science Workbench diagnostic bundle... Collecting basic system info... Collecting kernel parameters.