Analysis
Kernels
Kernels are the execution environments for your Datazone notebooks.
Overview
A kernel is the computational engine that executes the code contained in a notebook. It acts as an isolated environment that:
- Processes the code you write
- Manages the memory and computations
- Returns the results back to your notebook
Available Kernel Images
Datazone provides two main kernel images:
- Python: Standard Python environment with common data science libraries
- Python Pyspark: Python environment with Apache Spark support for distributed computing
Compute Resources
You can select from different compute sizes based on your workload:
| Size | Resources | Best for |
|---|---|---|
| X-Small | 2 vCPU, 8 GB RAM | Light data processing, simple scripts |
| Small | 4 vCPU, 16 GB RAM | Standard data analysis, medium datasets |
| Medium | 8 vCPU, 32 GB RAM | Heavy computations, large datasets |
| Large | 16 vCPU, 64 GB RAM | Big data processing, complex analytics |
| X-Large | 32 vCPU, 128 GB RAM | Enterprise-level distributed computing |
Environment Variables
Before initializing a kernel, you can set custom environment variables to:
- Configure access credentials
- Set runtime parameters
- Define application-specific settings
- Control library behaviors