Hello everyone,
I am new to the Pangeo community and have been exploring its capabilities for processing large-scale geospatial data. I work in climate modeling and have been trying to use Pangeo’s integration with tools like Dask and Xarray for analyzing climate datasets. My main question is: how do I optimize the performance of these tools when dealing with multi-terabyte datasets: ??
I am particularly interested in understanding how Pangeo handles data chunking, parallel processing and memory management for large climate models. I have read a bit about using Dask to parallelize computations…, but I am unsure about the best practices when scaling up to very large datasets. Any advice on how to improve performance, avoid memory issues, and speed up computation would be greatly appreciated.
Additionally…, if anyone has any example workflows or resources that demonstrate the full potential of Pangeo in large-scale climate data analysis…, I would love to take a look!
Thanks in advance !!