# Setup with Cloudera¶

This reference architecture will guide you through deploying on your DSS connected to your Cloudera:

• The fundamental local isolation code layer
• Impersonation for accessing HDFS datasets
• Impersonation for running Spark code over Yarn
• Impersonation for accessing Hive and Impala

In the rest of this document:

• dssuser means the UNIX user which runs the DSS software
• DATADIR means the directory in which DSS is running

## The two modes¶

There are two major ways to deploy UIF on Cloudera. The difference lies in how authorization is propagated on HDFS datasets

• Using Sentry. In this mode, Sentry will manage all authorization on HDFS data, both at the raw HDFS level and Hive/Impala level
• Using “DSS-managed ACL synchronization”. DSS will place HDFS ACLs on the managed datasets that it builds. Note that you will also need to leverage Sentry ACLs for Hive/Impala level.

We recommend that you use Sentry preferably to DSS-managed ACLs. Sentry lives in the NameNode and has more pervasive and flexible access, implying fewer limitations than DSS-managed ACLs. The three main advantages of using Sentry mode are:

• Centralized authorization in Sentry rather than requiring managing Sentry rules in addition to the HDFS ACLs.
• For some customer deployments, working around limitations in number of HDFS ACLs (the default DSS-managed ACLs require a larger number of ACLs per path, which can overflow the limit to 32 ACLs per path in HDFS)
• Appending in HDFS datasets using multiple users becomes possible.

## Prerequisites and required information¶

Please read carefully the Prerequisites and limitations documentation and check that you have all required information.

The most important parts here are:

• Having a keytab for the dssuser
• Having administrator access to the Cloudera cluster
• Having root access to the local machine
• Having an initial list of end-user groups allowed to use the impersonation mechanisms.

## Common setup¶

Initialize UIF (including local code isolation), see Initial Setup

## Sentry-mode¶

### Assumptions¶

In this model (as in the default DSS-managed-ACLs one btw) the security boundary is that of the Hive database. There should be at least one Hive database per security tenant (ie set of different authorization rules). Within a given Hive database, all tables (and thus all DSS datasets) have by default the same authorization rules as the database itself.

In this model, each Hive database maps to a base directory of the HDFS filesystem. All datasets within this database are stored into a subdirectory of this base directory.

Authorization rules are defined in Sentry at the database level, and cover both Hive tablespace access and HDFS access (through Sentry HDFS ACLs synchronization).

DSS HDFS connections can be set up to map DSS projects to these security tenants in several ways, depending on the application constraints, in particular:

• one DSS connection per tenant
• several tenants per connection, multiple projects per security tenant

### Configure your Cloudera cluster¶

Note

This part must be performed by the Hadoop administrator. A restart of your Cloudera cluster may be required.

You now need to allow the dssuser user to impersonate all end-user groups that you have previously identified.

This is done by adding hadoop.proxyuser.dssuser.groups and hadoop.proxyuser.dssuser.hosts configuration keys to your Hadoop configuration (core-site.xml). These respectively specify the list of groups of users which DSS is allowed to impersonate, and the list of hosts from which DSS is allowed to impersonate these users.

The hadoop.proxyuser.dssuser.groups parameter should be set to a comma-separated list containing:

• A list of end-user groups which collectively contain all DSS users
• The group with which the hive user creates its files (generally: hive on Cloudera, hadoop on HDP)
• In addition, on Cloudera, the group with which the impala user creates its files (generally: impala)

Alternatively, this parameter can be set to * to allow DSS to impersonate all cluster users (effectively disabling this extra security check).

The hadoop.proxyuser.dssuser.hosts parameter should be set to the fully-qualified host name of the server on which DSS is running. Alternatively, this parameter can be set to * to allow all hosts (effectively disabling this extra security check).

Make sure Hadoop configuration is properly propagated to all cluster hosts and to the host running DSS. Make sure that all relevant Hadoop services are properly restarted.

#### Do it with Cloudera Manager¶

(NB: This information is given for information purpose only. Please refer to the official Cloudera documentation for your Cloudera version)

• In Cloudera Manager, navigate to HDFS > Configuration and search for “proxyuser”
• Add two new keys in the “Cluster-wide Advanced Configuration Snippet (Safety Valve) for core-site.xml” section.
• Name: hadoop.proxyuser.dssuser.groups
• Value: comma-separated list of Hadoop groups of your end users, plus hive, impala
• Name: hadoop.proxyuser.dssuser.hosts
• Value: fully-qualified DSS host name, or *
• Save changes
• At the top of the HDFS page, click on the “Stale configuration: restart needed” icon and click on “Restart Stale Services” then “Restart now”

#### Setup Sentry¶

• Make sure the cluster is set up for Sentry HDFS ACLs synchronization (refer to Cloudera documentation - this is

normally the default for secure Cloudera clusters with Sentry)

• Create one or several root directories for DSS output directories.

• Add these directories (or a parent of those) to the sentry.hdfs.integration.path.prefixes Hadoop configuration key. Restart HDFS after changes to the latter.

The net effect of this operation is that permissions within these directories will be dynamically overriden by HDFS to match Sentry authorization rules, whenever there is a matching Hive definition (database or table).

• For each Hive database which you want DSS to use:

• Create the database in HiveServer2 with a location inside one of the Sentry-managed directories:

beeline> CREATE DATABASE <db_name> LOCATION 'hdfs://<namenode>/<path_to_dir>';


Note: you will need to either create this dir first and give user “hive” write access to it or to give user “hive” write access to its parent so hive can create it

• Grant access to both database and underlying directory to both the DSS account and those DSS user groups which should be authorized to use it:

beeline> GRANT ALL ON DATABASE <db_name> TO ROLE <dss_service_account_role>;
beeline> GRANT ALL ON DATABASE <db_name> TO ROLE <some_dss_users_role>, ...;
beeline> GRANT ALL ON URI 'hdfs://<namenode>/<path_to_dir>' TO ROLE <dss_service_account_role>;
beeline> GRANT ALL ON URI 'hdfs://<namenode>/<path_to_dir>' TO ROLE <some_dss_users_role>, ...;


#### Additional setup for Impala¶

If you plan on using Impala, you must perform an additional setup because Impala does not use the regular proxyuser mechanism.

• In Cloudera Manager, go to Impala > Configuration
• In the Impala Daemon Command Line Argument Advanced Configuration Snippet (Safety Valve) setting, add: authorized_proxy_user_config=dssuser=enduser_1,enduser_2,..., where enduser_xx is the Hadoop name of a DSS user, or * for all

Note

Contrary to the rest of Hadoop, the Impala impersonation authorization list is user-based, not group-based, which means that in many cases the only practical configuration is to use * and allow DSS to impersonate all Impala users.

#### Additional setup for encrypted HDFS filesystems¶

If DSS should access encrypted HDFS filesystems on behalf of users, you need to add specific Hadoop configuration keys to authorize impersonated access to the associated key management system (KMS):

• hadoop.kms.proxyuser.dssuser.groups : comma-separated list of Hadoop groups of your end users
• hadoop.kms.proxyuser.dssuser.hosts : fully-qualified DSS host name, or *

### Setup driver for Impala¶

If you want to use Impala, you need to install the Cloudera Impala JDBC Driver.

Download the driver from Cloudera Downloads website. You should obtain a Zip file impala_jdbc_VERSION.zip, containing two more Zip files. Unzip the “JDBC 4.1” version of the driver (the “JDBC 4” version will not work).

Copy the ImpalaJDBC41.jar file to the lib/jdbc folder of DSS. Beware, you must not copy other JARs. Restart DSS.

### Setup HDFS connections in DSS¶

Configure DSS managed HDFS connection(s) so that:

• Hive database for datasets map to one of the databases defined above
• HDFS paths for datasets map to the matching location for this database
• Management of HDFS ACLs by DSS is turned off (ACL synchronization mode: None)

### Configure identity mapping¶

If needed, go to Administration > Settings > Security and. update identity mapping.

Note

Due to various issues notably related to Spark, we strongly recommend that your DSS users and Hadoop users have the same name.

### Setup Hive and Impala access¶

• Go to Administration > Settings > Hadoop
• Fill in the HiveServer2 host and principal if needed, as described in Connecting to secure clusters
• Fill in the “Hive user” setting with the name of the user running HiveServer2 (generally: hive)
• Switch “Default execution engine” to “HiveServer2”

If you plan to use Impala:

• Go to Administration > Settings > Hadoop
• Fill in the Impala hosts and principal if needed, as described in Connecting to secure clusters
• Fill in the “Impala user” setting with the name of the user running impalad (generally: impala)
• Check the “Use Cloudera Driver” setting

### Authorization models¶

There are several possible deployments of the above model, depending on the desired authorization and management model:

#### One DSS connection per database¶

• directly configure the database name in “Hive database”
• add the DSS project key to the table names, as in : “Hive table name prefix” = ${projectKey}_ • root path URI : path to database directory • Path prefix: ${projectKey}/
• optionally, you can restrict access to this DSS connection to its authorized DSS users, so the other ones do not see it at all

#### One database per DSS project, multiple databases per DSS connection¶

• Embed the DSS project key the Hive database name, as in: “Hive database” = dataiku_${projectKey} • Hive table name prefix can then be empty • Root path URI must be a common parent to all database directories • Embed the DSS project key in the HDFS path prefix, as in: “Path prefix” = ${projectKey}/
• You need to create each database using the above command sequence from an admin account when creating a DSS project

#### More complex setups¶

More complex setups are possible using per-project variables, typically representing the security tenant to use for a given project, and expanding these variables in the database name or path prefix

## DSS-ACL-synchronization-mode¶

Note

In most cases, we recommend that you preferably use Sentry mode as detailed above

### Configure your Cloudera cluster¶

Note

This part must be performed by the Cloudera administrator. A restart of your Cloudera cluster may be required.

You now need to allow the dssuser user to impersonate all end-user groups that you have previously identified.

This is done by adding hadoop.proxyuser.dssuser.groups and hadoop.proxyuser.dssuser.hosts configuration keys to your Hadoop configuration (core-site.xml). These respectively specify the list of groups of users which DSS is allowed to impersonate, and the list of hosts from which DSS is allowed to impersonate these users.

The hadoop.proxyuser.dssuser.groups parameter should be set to a comma-separated list containing:

• A list of end-user groups which collectively contain all DSS users
• The group with which the hive user creates its files (generally: hive on Cloudera, hadoop on HDP)
• In addition, on Cloudera, the group with which the impala user creates its files (generally: impala)

Alternatively, this parameter can be set to * to allow DSS to impersonate all cluster users (effectively disabling this extra security check).

The hadoop.proxyuser.dssuser.hosts parameter should be set to the fully-qualified host name of the server on which DSS is running. Alternatively, this parameter can be set to * to allow all hosts (effectively disabling this extra security check).

Make sure Hadoop configuration is properly propagated to all cluster hosts and to the host running DSS. Make sure that all relevant Hadoop services are properly restarted.

#### Do it with Cloudera Manager¶

(NB: This information is given for information purpose only. Please refer to the official Cloudera documentation for your Cloudera version)

• In Cloudera Manager, navigate to HDFS > Configuration and search for “proxyuser”
• Add two new keys in the “Cluster-wide Advanced Configuration Snippet (Safety Valve) for core-site.xml” section.
• Name: hadoop.proxyuser.dssuser.groups
• Value: comma-separated list of Hadoop groups of your end users, plus hive, impala
• Name: hadoop.proxyuser.dssuser.hosts
• Value: fully-qualified DSS host name, or *
• Save changes
• At the top of the HDFS page, click on the “Stale configuration: restart needed” icon and click on “Restart Stale Services” then “Restart now”

#### Additional setup for Impala¶

If you plan on using Impala, you must perform an additional setup because Impala does not use the regular proxyuser mechanism.

• In Cloudera Manager, go to Impala > Configuration
• In the Impala Daemon Command Line Argument Advanced Configuration Snippet (Safety Valve) setting, add: authorized_proxy_user_config=dssuser=enduser_1,enduser_2,..., where enduser_xx is the Hadoop name of a DSS user, or * for all

Note

Contrary to the rest of Hadoop, the Impala impersonation authorization list is user-based, not group-based, which means that in many cases the only practical configuration is to use * and allow DSS to impersonate all Impala users.

#### Additional setup for encrypted HDFS filesystems¶

If DSS should access encrypted HDFS filesystems on behalf of users, you need to add specific Hadoop configuration keys to authorize impersonated access to the associated key management system (Hadoop KMS or Ranger KMS):

• hadoop.kms.proxyuser.dssuser.groups : comma-separated list of Hadoop groups of your end users
• hadoop.kms.proxyuser.dssuser.hosts : fully-qualified DSS host name, or *

### Setup driver for Impala¶

If you want to use Impala, you need to install the Cloudera Impala JDBC Driver.

Download the driver from Cloudera Downloads website. You should obtain a Zip file impala_jdbc_VERSION.zip, containing two more Zip files. Unzip the “JDBC 4.1” version of the driver (the “JDBC 4” version will not work).

Copy the ImpalaJDBC41.jar file to the lib/jdbc folder of DSS. Beware, you must not copy other JARs. Restart DSS.

### Configure identity mapping¶

If needed, go to Administration > Settings > Security and update identity mapping.

Note

Due to various issues notably related to Spark, we strongly recommend that your DSS users and Hadoop users have the same name.

### Setup Hive and Impala access¶

• Go to Administration > Settings > Hadoop
• Fill in the HiveServer2 host and principal if needed, as described in Connecting to secure clusters
• Fill in the “Hive user” setting with the name of the user running HiveServer2 (generally: hive)
• Switch “Default execution engine” to “HiveServer2”

If you plan to use Impala:

• Go to Administration > Settings > Hadoop
• Fill in the Impala hosts and principal if needed, as described in Connecting to secure clusters
• Fill in the “Impala user” setting with the name of the user running impalad (generally: impala)
• Check the “Use Cloudera Driver” setting

### Initialize ACLs on HDFS connections¶

Go to the settings of the hdfs_managed connection. Click on Resync Root permissions

If you have other HDFS connections, do the same thing for them.

## Validate behavior¶

• Grant to at least one of your user groups the right to create projects
• Log in as an end user
• Create a project with key PROJECTKEY
• As a Hive administrator, create a database named dataiku_PROJECTKEY and use Sentry to grant to the end-user group the right to use this database. Details on how to do that are in the “Setup Sentry” section above
• As the end user in DSS, check that you can:
• Create external HDFS datasets
• Create prepare recipes writing to HDFS datasets
• Synchronize datasets to the Hive metastore
• Create Hive recipes to write new HDFS datasets
• Use Hive notebooks
• Create Python recipes
• Use Python notebooks
• Create Spark recipes
• If you have Impala, create Impala recipes
• If you have Impala, use Impala notebooks
• Create visual recipes and use all available execution engines

## Operations (Sentry mode)¶

When you follow these setup instructions and use Sentry mode, DSS starts with a configuration that enables a per-project security policy with minimal administrator intervention.

### Overview¶

• The HDFS connections are declared as usable by all users.
• Each project writes to a different HDFS folder.
• Each project writes to a different Hive database.
• Sentry rules define the location for the database
• Permissions are granted at the database and project levels.

The separation of folders and Hive database for each project are ensured by the naming rules defined in the HDFS connection.

Note

This default configuration should be usable by all, we recommend that you keep it.

### Adding a project¶

In that setting, adding a project requires adding a Hive database and granting permissions to the project’s groups on the database.

• Create the project in DSS
• Add the groups who must have access to the project

By default, the new database is called dataiku_PROJECTKEY where PROJECTKEY is the key of the newly created project. You can configure this in the settings of each HDFS connection.

As Hive administrator:

• Using beeline or another Hive client:
• Create the new database
• Create a role
• Add all groups who must have access to the project to the new role
• Grant ALL ON DATABASE to the new role
• Grant ALL ON URI to the new role (URI being by default: root of the connection + project key)

### Adding/Removing a user in a group¶

Grants are group-level, so no intervention is required when a user is added to a group.

### Adding access to a group¶

When you add project access to a group, you need to:

• Do the permission change on the DSS project
• If you have used a role for the project as recommended, you simply need to add the new group to the project’s role.

### Removing access from a group¶

When you remove project access to a group, you need to:

• Do the permission change on the DSS project
• If you have used a role for the project as recommended, you simply need to remove the new group from the project’s role.

### Interaction with externally-managed data¶

In the Sentry setup, DSS does not manage any ACLs. It is the administrator’s responsibility to ensure that read ACLs on these datasets are properly set.

#### Existing Hive table¶

If externally-managed data has an existing Hive table, and no synchronization to the Hive metastore, you need to ensure that Hive-level permissions (Sentry) allow access to all relevant groups.

#### Synchronized Hive table¶

Even on read-only external data, you can ask DSS to synchronize the definition to the Hive metastore. In that case, you need to ensure that the HDFS-level permissions allow the Hive (and maybe Impala) users to access the folder.

## Operations (ACL synchronization mode)¶

First, remember that we recommend that you favor Sentry mode.

DSS starts with a configuration that enables a per-project security policy with minimal administrator intervention.

### Overview¶

• The HDFS connections are declared as usable by all users.
• Each project writes to a different HDFS folder.
• Each project writes to a different Hive database.

The separation of folders and Hive database for each project are ensured by the naming rules defined in the HDFS connection.

Security is thus ensured in two ways:

• DSS automatically adds ACLs on the actual directories corresponding to datasets, which prevents users who are not in the project’s authorized groups from accessing the folder, even in user-controlled code.
• Access through Hive or Impala can be controlled using Sentry rules.

Note

This default configuration should be usable by all, we recommend that you keep it.

### Adding a project¶

In that setting, adding a project requires adding a Hive database and granting permissions to the project’s groups on the database.

• Create the project in DSS
• Add the groups who must have access to the project

By default, the new database is called dataiku_PROJECTKEY where PROJECTKEY is the key of the newly created project. You can configure this in the settings of each HDFS connection.

As Hive administrator:

• Using beeline or another Hive client:
• Create the new database
• Create a role
• Add all groups who must have access to the project to the new role
• Grant ALL ON DATABASE to the new role
• Grant ALL ON URI to the new role (URI being by default: root of the connection + project key)

### Adding a user to a group¶

Read ACLs are group-level, so no intervention is required when a user is added to a group.

### Removing a user from a group¶

The removed user might still have a write ACL if he was the last to modify some datasets. You need to resynchronize the ACLs on all affected datasets in all projects where the user had access.

• Use the Authorization matrix to check where the user had access
• Remove the user
• For each affected project, go to Project > Settings > Config > Security and click “Resync ACLs”.

### Adding access to a group¶

When you add project access to a group, you need to resynchronize the ACLs on the project’s datasets. This will ensure that the new group has access.

• Do the permission change on the DSS project
• Go to Project > Settings > Config > Security and click “Resync ACLs”.

In Sentry, if you have used a role for the project as recommended, you simply need to add the new group to the project’s role.

### Removing access from a group¶

When you remove project access to a group, you need to resynchronize the ACLs on the project’s datasets. This will ensure that the group loses existing access.

• Do the permission change on the DSS project
• Go to Project > Settings > Config > Security and click “Resync ACLs”.

In Sentry, you have used a role for the project as recommended, you simply need to remove the new group from the project’s role.

### Interaction with externally-managed data¶

DSS only manages ACLs on the connections where managed datasets are written. DSS does not manage ACLs on “external” connections (this is controlled by the “Synchronize read ACL” and “Write ACL synchronization” settings in the HDFS connection).

It is the administrator’s responsibility to ensure that read ACLs on these datasets are properly set.

#### Existing Hive table¶

If externally-managed data has an existing Hive table, and no synchronization to the Hive metastore, you need to ensure that Hive-level permissions (Sentry) allow access to all relevant groups.

#### Synchronized Hive table¶

Even on read-only external data, you can ask DSS to synchronize the definition to the Hive metastore. In that case, you need to ensure that the HDFS-level permissions allow the Hive (and maybe Impala) users to access the folder.