Troubleshooting¶

When troubleshooting, you may see unexpected behaviors or receive an error message. This section provide links for identifying the cause of the problem and how to resolve it.

Behavior

• JupyterHub proxy fails to start
• sudospawner fails to run
• What is the default behavior when none of the lists (admin, whitelist, group whitelist) are set?
• JupyterHub Docker container not accessible at localhost

Errors

• 500 error after spawning my single-user server

How do I…?

• Use a chained SSL certificate
• Install JupyterHub without a network connection
• I want access to the whole filesystem, but still default users to their home directory
• How do I increase the number of pySpark executors on YARN?
• How do I use JupyterLab’s prerelease version with JupyterHub?
• How do I set up JupyterHub for a workshop (when users are not known ahead of time)?
• How do I set up rotating daily logs?
• Toree integration with HDFS rack awareness script
• Where do I find Docker images and Dockerfiles related to JupyterHub?

Troubleshooting commands

Behavior¶

JupyterHub proxy fails to start¶

If you have tried to start the JupyterHub proxy and it fails to start:

• check if the JupyterHub IP configuration setting is c.JupyterHub.ip = '*'; if it is, try c.JupyterHub.ip = ''
• Try starting with jupyterhub --ip=0.0.0.0

Note: If this occurs on Ubuntu/Debian, check that the you are using a recent version of node. Some versions of Ubuntu/Debian come with a version of node that is very old, and it is necessary to update node.

sudospawner fails to run¶

If the sudospawner script is not found in the path, sudospawner will not run. To avoid this, specify sudospawner’s absolute path. For example, start jupyterhub with:

jupyterhub --SudoSpawner.sudospawner_path='/absolute/path/to/sudospawner'


c.SudoSpawner.sudospawner_path = '/absolute/path/to/sudospawner'


to the config file, jupyterhub_config.py.

What is the default behavior when none of the lists (admin, whitelist, group whitelist) are set?¶

When nothing is given for these lists, there will be no admins, and all users who can authenticate on the system (i.e. all the unix users on the server with a password) will be allowed to start a server. The whitelist lets you limit this to a particular set of users, and the admin_users lets you specify who among them may use the admin interface (not necessary, unless you need to do things like inspect other users’ servers, or modify the userlist at runtime).

JupyterHub Docker container not accessible at localhost¶

Even though the command to start your Docker container exposes port 8000 (docker run -p 8000:8000 -d --name jupyterhub jupyterhub/jupyterhub jupyterhub), it is possible that the IP address itself is not accessible/visible. As a result when you try http://localhost:8000 in your browser, you are unable to connect even though the container is running properly. One workaround is to explicitly tell Jupyterhub to start at 0.0.0.0 which is visible to everyone. Try this command: docker run -p 8000:8000 -d --name jupyterhub jupyterhub/jupyterhub jupyterhub --ip 0.0.0.0 --port 8000

Errors¶

500 error after spawning my single-user server¶

You receive a 500 error when accessing the URL /user/<your_name>/.... This is often seen when your single-user server cannot verify your user cookie with the Hub.

There are two likely reasons for this:

1. The single-user server cannot connect to the Hub’s API (networking configuration problems)
2. The single-user server cannot authenticate its requests (invalid token)

Symptoms¶

The main symptom is a failure to load any page served by the single-user server, met with a 500 error. This is typically the first page at /user/<your_name> after logging in or clicking “Start my server”. When a single-user notebook server receives a request, the notebook server makes an API request to the Hub to check if the cookie corresponds to the right user. This request is logged.

If everything is working, the response logged will be similar to this:

200 GET /hub/api/authorizations/cookie/jupyterhub-token-name/[secret] (@10.0.1.4) 6.10ms


You should see a similar 200 message, as above, in the Hub log when you first visit your single-user notebook server. If you don’t see this message in the log, it may mean that your single-user notebook server isn’t connecting to your Hub.

If you see 403 (forbidden) like this, it’s a token problem:

403 GET /hub/api/authorizations/cookie/jupyterhub-token-name/[secret] (@10.0.1.4) 4.14ms


Check the logs of the single-user notebook server, which may have more detailed information on the cause.

Causes and resolutions¶

No authorization request¶

If you make an API request and it is not received by the server, you likely have a network configuration issue. Often, this happens when the Hub is only listening on 127.0.0.1 (default) and the single-user servers are not on the same ‘machine’ (can be physically remote, or in a docker container or VM). The fix for this case is to make sure that c.JupyterHub.hub_ip is an address that all single-user servers can connect to, e.g.:

c.JupyterHub.hub_ip = '10.0.0.1'


How do I…?¶

Use a chained SSL certificate¶

Some certificate providers, i.e. Entrust, may provide you with a chained certificate that contains multiple files. If you are using a chained certificate you will need to concatenate the individual files by appending the chain cert and root cert to your host cert:

cat your_host.crt chain.crt root.crt > your_host-chained.crt


You would then set in your jupyterhub_config.py file the ssl_key and ssl_cert as follows:

c.JupyterHub.ssl_cert = your_host-chained.crt
c.JupyterHub.ssl_key = your_host.key


Example¶

Your certificate provider gives you the following files: example_host.crt, Entrust_L1Kroot.txt and Entrust_Root.txt.

Concatenate the files appending the chain cert and root cert to your host cert:

cat example_host.crt Entrust_L1Kroot.txt Entrust_Root.txt > example_host-chained.crt


You would then use the example_host-chained.crt as the value for JupyterHub’s ssl_cert. You may pass this value as a command line option when starting JupyterHub or more conveniently set the ssl_cert variable in JupyterHub’s configuration file, jupyterhub_config.py. In jupyterhub_config.py, set:

c.JupyterHub.ssl_cert = /path/to/example_host-chained.crt
c.JupyterHub.ssl_key = /path/to/example_host.key


where ssl_cert is example-chained.crt and ssl_key to your private key.

Then restart JupyterHub.

Install JupyterHub without a network connection¶

Both conda and pip can be used without a network connection. You can make your own repository (directory) of conda packages and/or wheels, and then install from there instead of the internet.

For instance, you can install JupyterHub with pip and configurable-http-proxy with npmbox:

pip wheel jupyterhub
npmbox configurable-http-proxy


I want access to the whole filesystem, but still default users to their home directory¶

Setting the following in jupyterhub_config.py will configure access to the entire filesystem and set the default to the user’s home directory.

c.Spawner.notebook_dir = '/'
c.Spawner.default_url = '/home/%U' # %U will be replaced with the username


How do I increase the number of pySpark executors on YARN?¶

From the command line, pySpark executors can be configured using a command similar to this one:

pyspark --total-executor-cores 2 --executor-memory 1G


Cloudera documentation for configuring spark on YARN applications provides additional information. The pySpark configuration documentation is also helpful for programmatic configuration examples.

How do I use JupyterLab’s prerelease version with JupyterHub?¶

While JupyterLab is still under active development, we have had users ask about how to try out JupyterLab with JupyterHub.

You need to install and enable the JupyterLab extension system-wide, then you can change the default URL to /lab.

For instance:

pip install jupyterlab
jupyter serverextension enable --py jupyterlab --sys-prefix


The important thing is that jupyterlab is installed and enabled in the single-user notebook server environment. For system users, this means system-wide, as indicated above. For Docker containers, it means inside the single-user docker image, etc.

In jupyterhub_config.py, configure the Spawner to tell the single-user notebook servers to default to JupyterLab:

c.Spawner.default_url = '/lab'


How do I set up JupyterHub for a workshop (when users are not known ahead of time)?¶

1. Set up JupyterHub using OAuthenticator for GitHub authentication
2. Configure whitelist to be an empty list injupyterhub_config.py

Users will need a GitHub account to login and be authenticated by the Hub.

How do I set up rotating daily logs?¶

You can do this with logrotate, or pipe to logger to use syslog instead of directly to a file.

For example, with this logrotate config file:

/var/log/jupyterhub.log {
copytruncate
daily
}


and run this daily by putting a script in /etc/cron.daily/:

logrotate /path/to/above-config


Or use syslog:

jupyterhub | logger -t jupyterhub


Troubleshooting commands¶

The following commands provide additional detail about installed packages, versions, and system information that may be helpful when troubleshooting a JupyterHub deployment. The commands are:

• System and deployment information
jupyter troubleshooting

• Kernel information
jupyter kernelspec list

• Debug logs when running JupyterHub
jupyterhub --debug


Toree integration with HDFS rack awareness script¶

The Apache Toree kernel will an issue, when running with JupyterHub, if the standard HDFS rack awareness script is used. This will materialize in the logs as a repeated WARN:

16/11/29 16:24:20 WARN ScriptBasedMapping: Exception running /etc/hadoop/conf/topology_script.py some.ip.address
ExitCodeException exitCode=1:   File "/etc/hadoop/conf/topology_script.py", line 63
print rack
^
SyntaxError: Missing parentheses in call to 'print'

at org.apache.hadoop.util.Shell.runCommand(Shell.java:576)


In order to resolve this issue, there are two potential options.

1. Update HDFS core-site.xml, so the parameter “net.topology.script.file.name” points to a custom script (e.g. /etc/hadoop/conf/custom_topology_script.py). Copy the original script and change the first line point to a python two installation (e.g. /usr/bin/python).
2. In spark-env.sh add a Python 2 installation to your path (e.g. export PATH=/opt/anaconda2/bin:\$PATH).