I also changed the following in jupyterhub_config.py file. But still seeing the issue.
## Minimum number of bytes a single-user notebook server is guaranteed to have # available. # # Allows the following suffixes: # - K -> Kilobytes # - M -> Megabytes # - G -> Gigabytes # - T -> Terabytes # # This needs to be supported by your spawner for it to work. #c.Spawner.mem_guarantee = 8G ## Maximum number of bytes a single-user notebook server is allowed to use. # # Allows the following suffixes: # - K -> Kilobytes # - M -> Megabytes # - G -> Gigabytes # - T -> Terabytes # # If the single user server tries to allocate more memory than this, it will # fail. There is no guarantee that the single-user notebook server will be able # to allocate this much memory - only that it can not allocate more than this. # # This needs to be supported by your spawner for it to work. #c.Spawner.mem_limit = 10G On Sunday, November 19, 2017 at 12:49:53 PM UTC-8, Karthik Ram wrote: > > 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. > -- You received this message because you are subscribed to the Google Groups "Project Jupyter" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To post to this group, send email to [email protected]. To view this discussion on the web visit https://groups.google.com/d/msgid/jupyter/a63946d4-5c4a-4b71-aebc-33785f0557ed%40googlegroups.com. For more options, visit https://groups.google.com/d/optout.
