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actually have the same 2.7 kernel, that lacks packages such as numpy, pandas, ...etc.
Even some spark DataFrame functions rely on those, therefore the usability is quite limited at the moment.
A Docker container update might be #necessary.
The text was updated successfully, but these errors were encountered:
Più nel dettaglio:
“Pyspark“ kernel (cosi’ come “Pyspark3”) manca di librerie base (es: numpy) all’interno della session livy.
All’esterno della session (usando “%%local”) numpy e’ presente, ma manca ad esempio seaborn.
Da decidere se prevediamo di fare la maggior parte delle analisi nella session o in %%local; passare variabili da una all’altra non e’ semplicissimo.
Kernel PySpark3 sembra uguale a PySpark (python2) nella session spark:
qui sotto la chiamata per mostrare la versione di python:
import os
os.sys.version
'2.7.5 (default, Nov 6 2016, 00:28:07) \n[GCC 4.8.5 20150623 (Red Hat 4.8.5-11)]'
eseguendo invece in %%local:
%%local
import os
os.sys.version
'3.5.4 | packaged by conda-forge | (default, Aug 10 2017, 01:38:41) \n[GCC 4.8.2 20140120 (Red Hat 4.8.2-15)]'
It looks like the environments:
actually have the same 2.7 kernel, that lacks packages such as numpy, pandas, ...etc.
Even some spark DataFrame functions rely on those, therefore the usability is quite limited at the moment.
A Docker container update might be #necessary.
The text was updated successfully, but these errors were encountered: