I've done this before using a custom docker image, but even then the runtime itself continues to use the version of python 3 which is installed as part of the OS. The easiest way to get to a newer version is to use a newer runtime. If you're sticking...
So one way of doing this is to simple iterate over the directories at that level and create a table for each. Assuming that the schema is the same in all files you could simple do something likesubjects = dbutils.fs.ls("abfss://landing@account.dfs.co...
With code for anyone facing the same issue, and without moving to a different pathimport requests
CHUNK_SIZE=4096
with requests.get("https://raw.githubusercontent.com/suy1968/Adult.csv-Dataset/main/adult.csv", stream=True) as resp:
if resp.ok:
...
Notebooks really aren't the best method of viewing large files. Two methods you could employ areSave the file to dbfs and then use databricks CLI to download the fileUse the web terminalIn the web terminal option you can do something like "cat my_lar...
