Hi All,
I have been using the following Jupyter notebook configuration for less
than couple of months, so I'm relatively new. While my script seems to work
on smaller tables data, when I try to use the same to access a larger table
(with ~10 billion rows), the kernel dies on me. I have searched and
implemented some suggestions mentioned in stack overflow with similar
issues but it didn't help me over the last couple of days. Attaching error
message. I have the following questions. Also Any other suggestions on how
to further debug/fix this issue will be really helpful.
https://stackoverflow.com/questions/47022997/jupyter-the-kernel-appears-to-have-died-it-will-restart-automatically
1. I have updated MKL using "conda update mkl" but it seems to update my
Anaconda2 while I noticed jupyter installation uses python3. When I checked
the jupyter kernel environment , it seems like it is using python2.
*Before MKL update: $ *jupyter-kernelspec list
Available kernels: python2
/home/rpatel/miniconda2/lib/python2.7/site-packages/ipykernel/resources
*After MKL update: $ *jupyter-kernelspec list
Available kernels: python2
/home/rpatel/.local/share/jupyter/kernels/python2
2. Any details on allocating extra RAM to Jupyter will be really
helpful. (Most of the suggestions point to increasing RAM but doesn't
provide details on how exactly it can be achieved).
*Server Information:*
You are using Jupyter notebook.
The version of the notebook server is 5.0.0 and is running on:
Python 3.6.1 |Anaconda custom (64-bit)| (default, May 11 2017, 13:09:58)
[GCC 4.4.7 20120313 (Red Hat 4.4.7-1)]
Current Kernel Information:
Python 3.6.1 |Anaconda custom (64-bit)| (default, May 11 2017, 13:09:58)
Type 'copyright', 'credits' or 'license' for more information
IPython 6.1.0 -- An enhanced Interactive Python. Type '?' for help.
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