Jupyter 笔记本在 Microsoft Azure 中运行缓慢

Question

I am quite new to using Microsoft Azure for running jupyter notebooks. I noticed that it can take 30-45 seconds to polar plot 2 numpy arrays, which is small relatively small (<300 datapoints per array). When I have to execute several of these plots, the time adds up, so I am wondering if this is related to a particular compute instance or network latency? Any insight would be greatly appreciated, thank you!

Answer 1

Notebook will be slow when the data loading limits are high, below is one of the case where I faced similar issue.

• Tried to display some 40000 columns, I faced some serious unresponsive issue and slowness.
• As soon as I changed the code to display only 40 or 80 columns, the response was good.

Below are some root causes for this:

• Clean all the data which is related to dataframes like pandas etc.

• From the below block we can get memory and cpu usage, so that it will help us to clear the unwanted data:

   #./usr/bin/env python import psutil # gives a single float value psutil.cpu_percent() # gives an object with many fields psutil.virtual_memory() # you can convert that object to a dictionary dict(psutil.virtual_memory()._asdict()) # you can have the percentage of used RAM psutil.virtual_memory().percent 79.2 # you can calculate percentage of available memory psutil.virtual_memory().available * 100 / psutil.virtual_memory().total 20.8

• We will have some variable inspectors, if they are enabled the notebook might get slow because of some dataframes like pandas. GIT Issue

  If you want to disable it --> Edit --> nbextensions config.

Refer to these SO ( SO1 , SO2 , SO3 , SO4 ) links for detailed explanations.