Install Cloudera Data Science Workbench on the Master Host

DOMAIN

Wildcard DNS domain configured to point to the master host.

If the wildcard DNS entries are configured as cdsw.<your_domain>.com and *.cdsw.<your_domain>.com, then DOMAIN should be set to cdsw.<your_domain>.com. Users' browsers should then contact the Cloudera Data Science Workbench web application at http://cdsw.<your_domain>.com.

This domain for DNS and is unrelated to Kerberos or LDAP domains.

MASTER_IP

IPv4 address for the master host that is reachable from the worker hosts.

Within an AWS VPC, MASTER_IP should be set to the internal IP address of the master host; for instance, if your hostname is ip-10-251-50-12.ec2.internal, set MASTER_IP to the corresponding IP address, 10.251.50.12.

DISTRO

The Hadoop distribution installed on the cluster. Set this property to HDP.

DOCKER_BLOCK_DEVICES

Block device(s) for Docker images (space separated if there are multiple).

Use the full path to specify the image(s), for instance, /dev/xvde.

JAVA_HOME

Path where Java is installed on the Cloudera Data Science Workbench hosts.

This path must match the JAVA_HOME environment variable that is configured for your HDP cluster. You can find the value in hadoop-env.sh on 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/.

APPLICATION_BLOCK_DEVICE

(Master Host Only) Configure a block device for application state.

If this property is left blank, the filesystem mounted at /var/lib/cdsw on 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 /var/lib/cdsw mount.

(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, /dev/xvdf.

RESERVE_MASTER

Set this property to true to 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.

DISTRO_DIR

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.

ANACONDA_DIR

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.

TLS_ENABLE

Enable and enforce HTTPS (TLS/SSL) for web access.

Set to true to enable and enforce HTTPS access to the web application.

You can also set this property to true to enable external TLS termination. For more details on TLS termination, see Enabling TLS/SSL for Cloudera Data Science Workbench.

TLS_CERT

TLS_KEY

Certificate and private key for internal TLS termination.

Setting TLS_CERT and TLS_KEY will enable internal TLS termination. You must also set TLS_ENABLE to true above 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 PEM format.

For details on certificate requirements and enabling TLS termination, see Enabling TLS/SSL for Cloudera Data Science Workbench.

HTTP_PROXY

HTTPS_PROXY

HTTP_PROXY="<http://proxy_host>:<proxy-port>"
HTTPS_PROXY="<http://proxy_host>:<proxy_port>"

HTTP_PROXY="http://localhost:3128"
HTTPS_PROXY="http://localhost:3128"

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.

cp /tmp/<proxy-root-certificate>.crt /etc/pki/ca-trust/source/anchors/

update-ca-trust extract

ALL_PROXY

If a SOCKS proxy is in use, set to socks5://<host>:<port>/.

NO_PROXY

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 HTTP_PROXY(S) or ALL_PROXY properties, Cloudera Data Science Workbench automatically appends the following list of IP addresses to the NO_PROXY configuration. Note that this is the minimum required configuration for this field.

This list includes 127.0.0.1, 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"

NVIDIA_GPU_ENABLE

Set this property to true to 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 true on a host that does not have GPU support, there will be no effect. By default, this property is set to false.

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.

NVIDIA_LIBRARY_PATH

Complete path to the NVIDIA driver libraries.