Install Cloudera Data Science Workbench on the Master Host
Use the following steps to install Cloudera Data Science Workbench on the master host.
Non-airgapped Installation - Download the Cloudera Data Science Workbench
repo file (cloudera-cdsw.repo) from the following location:
https://username:firstname.lastname@example.org/p/cdsw1/1.10.2/redhat7/yum/cloudera-cdsw.repoAirgapped installation - For airgapped installations, download the Cloudera Data Science Workbench RPM file from the following location:
Skip this step for airgapped installations. Add the Cloudera Public GPG repository
key. This key verifies that you are downloading genuine packages.
sudo rpm --import https://username:email@example.com/p/cdsw1/1.10.2/redhat7/yum/RPM-GPG-KEY-cloudera
Non-airgapped Installation - Install the latest RPM with the following
sudo yum install cloudera-data-science-workbenchAirgapped Installation - Copy the RPM downloaded in the previous step to the appropriate gateway host. Then, use the complete filename to install the package. For example:
sudo yum install cloudera-data-science-workbench-188.8.131.5245.rpmFor guidance on any warnings displayed during the installation process, see Understanding Installation Warnings.
Edit the configuration file at
/etc/cdsw/config/cdsw.conf. The following table lists the configuration properties that can be configured in cdsw.conf.
Properties Description Required Configuration
Wildcard DNS domain configured to point to the master host.
If the wildcard DNS entries are configured as
DOMAINshould be set to
cdsw.<your_domain>.com. Users' browsers should then contact the Cloudera Data Science Workbench web application at
This domain for DNS and is unrelated to Kerberos or LDAP domains.
IPv4 address for the master host that is reachable from the worker hosts.
Within an AWS VPC,
MASTER_IPshould be set to the internal IP address of the master host; for instance, if your hostname is
MASTER_IPto the corresponding IP address,
The Hadoop distribution installed on the cluster. Set this property to
Block device(s) for Docker images (space separated if there are multiple).
Use the full path to specify the image(s), for instance,
Path where Java is installed on the Cloudera Data Science Workbench hosts.
This path must match the
JAVA_HOMEenvironment variable that is configured for your HDP cluster. You can find the value in
hadoop-env.shon any node in the HDP cluster.
Note that Spark 2.3 requires JDK 1.8. For more details on the specific versions of Oracle JDK recommended for HDP clusters, see the Hortonworks Support Matrix - https://supportmatrix.cloudera.com/.
(Master Host Only) Configure a block device for application state.
If this property is left blank, the filesystem mounted at
/var/lib/cdswon the master host will be used to store all user data. For production deployments, Cloudera strongly recommends you use this option with a dedicated SSD block device for the
(Not recommended) If set, Cloudera Data Science Workbench will format the provided block device as
ext4, mount it to
/var/lib/cdsw, and store all user data on it. This option has only been provided for proof-of-concept setups, and Cloudera is not responsible for any data loss.
Use the full path to specify the mount point, for instance,
Set this property to
trueto reserve the master host for Cloudera Data Science Workbench's internal components and services, such as Livelog, the PostgreSQL database, and so on. User workloads will now run exclusively on worker hosts, while the master is reserved for internal application services.
This feature only applies to deployments with more than one Cloudera Data Science Workbench host. Enabling this feature on single-host deployments will leave Cloudera Data Science Workbench incapable of scheduling any workloads.
Path where the Hadoop distribution is installed on the Cloudera Data Science Workbench hosts. For HDP clusters, the default location of the packages is
/usr/hdp. Specify this property only if you are using a non-default location.
Path where Anaconda is installed. Set this property only if you are using Anaconda for package management.
By default, the Anaconda package is installed at:
/home/<your-username>/anaconda<2 or 3>. Refer to the Anaconda FAQs for more details.
If you choose to start using Anaconda anytime post-installation, you must set this property and then restart Cloudera Data Science Workbench to have this change take effect.
Enable and enforce HTTPS (TLS/SSL) for web access.
trueto enable and enforce HTTPS access to the web application.
You can also set this property to
trueto enable external TLS termination. For more details on TLS termination, see Enabling TLS/SSL for Cloudera Data Science Workbench.
Certificate and private key for internal TLS termination.
TLS_KEYwill enable internal TLS termination. You must also set
trueabove to enable and enforce internal termination. Set these only if you are not terminating TLS externally.
Make sure you specify the full path to the certificate and key files, which must be in
For details on certificate requirements and enabling TLS termination, see Enabling TLS/SSL for Cloudera Data Science Workbench.
HTTPS_PROXYIf your deployment is behind an HTTP or HTTPS proxy, set the respective
/etc/cdsw/config/cdsw.confto the hostname of the proxy you are using.
HTTP_PROXY="<http://proxy_host>:<proxy-port>" HTTPS_PROXY="<http://proxy_host>:<proxy_port>"If you are using an intermediate proxy, such as Cntlm, to handle NTLM authentication, add the Cntlm proxy address to the
If the proxy server uses TLS encryption to handle connection requests, you will need to add the proxy's root CA certificate to your host's store of trusted certificates. This is because proxy servers typically sign their server certificate with their own root certificate. Therefore, any connection attempts will fail until the Cloudera Data Science Workbench host trusts the proxy's root CA certificate. If you do not have access to your proxy's root certificate, contact your Network / IT administrator.To enable trust, copy the proxy's root certificate to the trusted CA certificate store (
ca-trust) on the Cloudera Data Science Workbench host.
cp /tmp/<proxy-root-certificate>.crt /etc/pki/ca-trust/source/anchors/Use the following command to rebuild the trusted certificate store.
If a SOCKS proxy is in use, set to
Comma-separated list of hostnames that should be skipped from the proxy.
Starting with version 1.4, if you have defined a proxy in the
ALL_PROXYproperties, Cloudera Data Science Workbench automatically appends the following list of IP addresses to the
NO_PROXYconfiguration. Note that this is the minimum required configuration for this field.
This list includes
localhost, and any private Docker registries and HTTP services inside the firewall that Cloudera Data Science Workbench users might want to access from the engines.
"127.0.0.1,localhost,100.66.0.1,100.66.0.2,100.66.0.3, 100.66.0.4,100.66.0.5,100.66.0.6,100.66.0.7,100.66.0.8,100.66.0.9, 100.66.0.10,100.66.0.11,100.66.0.12,100.66.0.13,100.66.0.14, 100.66.0.15,100.66.0.16,100.66.0.17,100.66.0.18,100.66.0.19, 100.66.0.20,100.66.0.21,100.66.0.22,100.66.0.23,100.66.0.24, 100.66.0.25,100.66.0.26,100.66.0.27,100.66.0.28,100.66.0.29, 100.66.0.30,100.66.0.31,100.66.0.32,100.66.0.33,100.66.0.34, 100.66.0.35,100.66.0.36,100.66.0.37,100.66.0.38,100.66.0.39, 100.66.0.40,100.66.0.41,100.66.0.42,100.66.0.43,100.66.0.44, 100.66.0.45,100.66.0.46,100.66.0.47,100.66.0.48,100.66.0.49, 100.66.0.50,100.77.0.10,100.77.0.128,100.77.0.129,100.77.0.130, 100.77.0.131,100.77.0.132,100.77.0.133,100.77.0.134,100.77.0.135, 100.77.0.136,100.77.0.137,100.77.0.138,100.77.0.139"
Set this property to
trueto enable GPU support for Cloudera Data Science Workbench workloads. When this property is enabled on a host is equipped with GPU hardware, the GPU(s) will be available for use by Cloudera Data Science Workbench hosts.
If this property is set to
trueon a host that does not have GPU support, there will be no effect. By default, this property is set to
For detailed instructions on how to enable GPU-based workloads on Cloudera Data Science Workbench, see Using NVIDIA GPUs for Cloudera Data Science Workbench Projects.
Complete path to the NVIDIA driver libraries.
Initialize and start Cloudera Data Science Workbench.
cdsw startThe application will take a few minutes to bootstrap. You can watch the status of application installation and startup with
watch cdsw status.