> ## Documentation Index
> Fetch the complete documentation index at: https://anaconda.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Configuring Livy server for Hadoop Spark access

noindex: true

Review the [Apache Livy requirements](./livy-server) before you begin the configuration process. There are three main configuration settings you must update on your Apache Livy server to allow Data Science & AI Workbench users access to Hadoop/Spark clusters:

* [Livy impersonation](#configuring-livy-impersonation)
* [Cluster access](#configuring-cluster-access)
* [Project access](#configuring-project-access)

If the Hadoop cluster is configured to use Kerberos authentication, you’ll need to [allow Livy to access the services](#using-livy-with-kerberos-authentication). Additionally, you can configure Livy as a secure endpoint. For more information, see [Configuring Livy to use HTTPS](#configuring-livy-to-use-https) below.

## Configuring Livy impersonation

To enable users to run Spark sessions within Workbench, they need to be able to log in to each machine in the Spark cluster. The easiest way to accomplish this is to configure Livy impersonation as follows:

1. Add `Hadoop.proxyuser.livy` to your authenticated hosts, users, or groups.
2. Check the option to `Allow Livy to impersonate users` and set the value to all (`*`), or a list of specific users or groups.

If impersonation is *not* enabled, the user executing the livy-server (`livy`) must exist on every machine. You can add this user to each machine by running the following command on each node:

```sh theme={null}
sudo useradd -m livy
```

<Note>
  If you have any problems configuring Livy, try setting the log level to `DEBUG` in the `conf/log4j.properties` file.
</Note>

## Configuring cluster access

Livy server enables users to submit jobs from any remote machine or analytics cluster—even where a Spark client is not available—without requiring you to install Jupyter and Anaconda directly on an edge node in the Spark cluster.

To configure Livy server, put the following environment variables into a user’s `.bashrc file`, or the `conf/livy-env.sh` file that’s used to configure the Livy server.

These values are accurate for a Cloudera install of Spark with Java version 1.8:

```sh theme={null}
SPARK_HOME=/opt/cloudera/parcels/CDH-7.1.7-1.cdh7.1.7.p0.15945976/lib/spark
LIVY_LOG_DIR=/var/log/livy2
LIVY_PID_DIR=/var/run/livy2
JAVA_HOME=/usr/java/jdk1.8.0_232-cloudera/
SPARK_CONF_DIR=/etc/spark/conf
HADOOP_HOME=/opt/cloudera/parcels/CDH-7.1.7-1.cdh7.1.7.p0.15945976/lib/hadoop
HADOOP_CONF_DIR=/etc/hadoop/conf
```

Note that the port parameter that’s defined as `livy.server.port` in `conf/livy-env.sh` is the same port that will generally appear in the Sparkmagic user configuration.

The minimum required parameter is `livy.spark.master`. Other possible values include the following:

* `local[*]`—for testing purposes
* `yarn-cluster`—for using with the YARN resource allocation system
* a full spark URI like `spark://masterhost:7077`—if the spark scheduler is on a different host.

Example with YARN:

```sh theme={null}
livy.spark.master = yarn-cluster
```

The YARN deployment mode is set to `cluster` for Livy. The `livy.conf` file, typically located in `$LIVY_HOME/conf/livy.conf`, may include settings similar to the following:

```sh theme={null}
# What host address to start the server on. By default, Livy will bind to all network interfaces.
livy.server.host = 0.0.0.0

# What port to start the server on.
livy.server.port = 8998

# What spark master Livy sessions should use.
livy.spark.master = yarn

# What spark deploy mode Livy sessions should use.
livy.spark.deploy-mode = cluster
```

Restart Livy server once configuration is complete.

Anaconda recommends using a process control mechanism to restart your Livy server to ensure that it’s reliably restarted in the event of a failure.

<Note>
  The above example is to be used as a template only. Anaconda cannot assist with configuring Apache Livy for your organization.
</Note>

## Using Livy with Kerberos authentication

If the Hadoop cluster is configured to use Kerberos authentication, you’ll need to do the following to allow Livy to access the services:

1. Generate two keytabs for Apache Livy using `kadmin.local`.

   <Warning>
     **The keytab principals for Livy must match the hostname that the Livy server is deployed on**, or you’ll see the following exception: `GSSException: No valid credentials provided (Mechanism level: Failed to find any Kerberos credentials)`.
   </Warning>

   These are hostname and domain dependent, so edit the following example according to your Kerberos settings:

   ```sh theme={null}
   $ sudo kadmin.local

   kadmin.local:  addprinc livy/<HOSTNAME>

   kadmin.local:  xst -k livy-<HOSTNAME>.keytab livy/<HOSTNAME>@<REALM>
   ...

   kadmin.local:  addprinc HTTP/<HOSTNAME>

   kadmin.local:  xst -k HTTP-<HOSTNAME>.keytab HTTP/<HOSTNAME>@<REALM>
   ...
   ```

   This will generate two files: `livy-<HOSTNAME>.keytab` and `HTTP-<HOSTNAME>.keytab`.

2. Change the permissions of these two files so they can be read by `livy-server`.

3. Enable Kerberos authentication and reference these two keytab files in the `conf/livy.conf` configuration file, as shown:

   ```sh theme={null}
    # Kerberos settings

    # Authentication support for Livy server
    # Livy has a built-in SPnego authentication support for HTTP requests with below configurations.
    livy.server.auth.type = kerberos
    livy.server.auth.kerberos.principal = HTTP/<HOSTNAME>@<REALM>
    livy.server.auth.kerberos.keytab = <FILEPATH>/<KEYTAB>
    livy.server.auth.kerberos.name-rules = DEFAULT
    livy.server.launch.kerberos.principal = livy/<HOSTNAME>@<REALM>
    livy.server.launch.kerberos.keytab = <FILEPATH>/<KEYTAB>
   ```

<Note>
  The hostname and domain are not the same—verify that they match your Kerberos configuration.
</Note>

<Note>
  The above example is to be used as a template only. Anaconda cannot assist with configuring Kerberos for your organization.
</Note>

## Configuring Livy to use HTTPS

If you want to use Sparkmagic to communicate with Livy via HTTPS, you need to do the following to configure Livy as a secure endpoint:

* Generate a keystore file, certificate, and truststore file for the Livy server—or use a third-party SSL certificate.
* Update Livy with the keystore details.
* Update your Sparkmagic configuration.
* Restart the Livy server.

### If you’re using a self-signed certificate

1. Generate a keystore file for Livy server using the following command:

   ```sh theme={null}
   keytool -genkey -alias <host> -keyalg RSA -keysize 1024 --dname CN=<host>,OU=hw,O=hw,L=paloalto,ST=ca,C=us --keypass <keyPassword> -keystore <keystore_file> -storepass <storePassword>
   ```

2. Create a certificate:

   ```sh theme={null}
   keytool -export -alias <host> -keystore <keystore_file> -rfc --file <cert_file> -storepass <StorePassword>
   ```

3. Create a truststore file:

   ```sh theme={null}
   keytool -import -noprompt -alias <host> -file <cert_file> -keystore <truststore_file> -storepass <truststorePassword>
   ```

4. Update `livy.conf` with the keystore details. For example:

   ```sh theme={null}
   livy.keystore = <FILEPATH>/keystore.jks
   livy.keystore.password = anaconda
   livy.key-password = anaconda
   ```

5. Update `~/.sparkmagic/config.json`. For example:

   ```sh theme={null}
   "kernel_python_credentials" : {
      "username": "",
      "password": "",
      "url": "https://<IP>:8998",
      "auth": "None"
   },
   "ignore_ssl_errors": true,
   ```

   <Note>
     In this example, `ignore_ssl_errors` is set to `true` because this configuration uses self-signed certificates. Your production cluster setup may be different.
   </Note>

   <Warning>
     If you misconfigure a `.json` file, all Sparkmagic kernels will fail to launch. You can test your Sparkmagic configuration by running the following Python command in an interactive shell: `python -m json.tool config.json`.

     If you have formatted the JSON correctly, this command will run without error. Additional edits may be required, depending on your Livy settings.
   </Warning>

6. Restart the Livy server.

   The Livy server should now be accessible over https. For example, `https://<livy host>:<livy port>`.

   To test your SSL-enabled Livy server, run the following Python code in an interactive shell to create a session:

   ```sh theme={null}
   livy_url = "https://<livy host>:<livy port>/sessions"
   data = {'kind': 'spark', 'numExecutors': 1}
   headers = {'Content-Type': 'application/json'}
   r = requests.post(livy_url, data=json.dumps(data), headers=headers, auth=HTTPKerberosAuth(mutual_authentication=REQUIRED,     sanitize_mutual_error_response=False), verify=False)
   r.json()
   ```

   Run the following Python code to verify the status of the session:

   ```sh theme={null}
   session_url = "https://<livy host>:<livy port>/sessions/0"
   headers = {'Content-Type': 'application/json'}
   r = requests.get(session_url, headers=headers, auth=HTTPKerberosAuth(mutual_authentication=REQUIRED,  sanitize_mutual_error_response=False), verify=False)
   r.json()
   ```

   Then submit the following statement:

   ```sh theme={null}
   session_url = "https://<livy host>:<livy port>/sessions/0/statements"
   data ={"code": "sc.parallelize(1 to 10).count()"}
   headers = {'Content-Type': 'application/json'}
   r = requests.get(session_url, headers=headers, auth=HTTPKerberosAuth(mutual_authentication=REQUIRED, sanitize_mutual_error_response=False), verify=False)
   r.json()
   ```

### If you’re using a third-party certificate

<Note>
  Ensure that [Java JDK](https://www.oracle.com/java/technologies/downloads/#java8) is installed on the Livy server.
</Note>

1. Create the `keystore.p12` file using the following command:

   ```sh theme={null}
   openssl pkcs12 -export -in [path to certificate] -inkey [path to private key] -certfile [path to certificate chain] -out keystore.p12
   ```
2. Use the following command to create the `keystore.jks` file:

   ```sh theme={null}
    keytool -importkeystore -srckeystore keystore.p12 -srcstoretype pkcs12 -destkeystore keystore.jks -deststoretype JKS
   ```
3. If you don’t already have the `rootca.crt`, you can run the following command to extract it from your Workbench installation:

   ```sh theme={null}
    kubectl get secrets anaconda-enterprise-certs -o jsonpath="{.data[`rootca\.crt`]}" | base64 -d > /ext/share/rootca.crt
   ```
4. Add the `rootca.crt` to the `keystore.jks` file:

   ```sh theme={null}
    keytool -importcert -keystore keystore.jks -storepass <password> -alias rootCA -file rootca.crt
   ```
5. Add the `keystore.jks` file to the `livy.conf` file. For example:

   ```sh theme={null}
    livy.keystore = <FILEPATH>/keystore.jks
    livy.keystore.password = anaconda
    livy.key-password = anaconda
   ```
6. Restart the Livy server.
7. Run the following command to verify that you can connect to the Livy server (using your actual host and port):

   ```sh theme={null}
   openssl s_client -connect anaconda.example.com:8998 -CAfile rootca.crt
   ```

   If running this command returns `0`, you’ve successfully configured Livy to use HTTPS.

### To add the trusted root certificate to the Workbench server

1. Install the `ca-certificates` package:

   ```
   yum install ca-certificates
   ```
2. Enable dynamic CA configuration:

   ```sh theme={null}
   update-ca-trust force-enable
   ```
3. Add your `rootca.crt` as a new file:

   ```sh theme={null}
   cp rootca.crt /etc/pki/ca-trust/source/anchors
   ```
4. Update the certificate authority trust:

   ```sh theme={null}
   update-ca-trust extract
   ```

### To connect to Livy within a session

Open the project and run the following command in an interactive shell:

```sh theme={null}
import os
os.environ['REQUESTS_CA_BUNDLE'] = /path/to/root.ca
```

You can also edit the `anaconda-project.yml` file for the project and set the environment variable there. See [Hadoop / Spark](../../data-science-workflows/spark-hadoop) for more information.

## Configuring project access

After you’ve configured Livy for cluster access, you must configure your project to connect to the remote Hadoop Spark cluster.

1. Log in to Workbench as an admin user.
2. Open the project you want to connect to the remote cluster.
3. If the Hadoop installation used Kerberos authentication, place the `krb5.conf` file in the `/tools` mounted directory.
4. If you’re using Sparkmagic, include your `config.json` file in the `/tools` mounted directory.
5. Open the project’s `anaconda-project.yml` file.
6. Find the `variables:` section of the file and add the paths to the configuration files you’ve just placed in the `/tools` directory. For example:

   ```yaml theme={null}
   variables:
      KRB5_CONFIG:
         description: Location of config file for Kerberos authentication
         default: /tools/krb5.conf
      SPARKMAGIC_CONF_DIR:
         description: Location of Sparkmagic configuration file
         default: /tools
      SPARKMAGIC_CONF_FILE:
         description: Name of Sparkmagic configuration file
         default: config.json
   ```

<Note>
  If you want users to use this project’s environment as their main method for accessing the Hadoop Spark cluster, consider making it a template. For more information, see [Providing your environment to users](../custom_env_proj).
</Note>