How to ensure security and data privacy in Spark applications?

1. Start with a Secure Foundation: Before diving into Spark specifically, ensure that the environment Spark will be operating in is secure. This includes your physical servers, virtual machines, or cloud services. They should all be up-to-date with the latest security patches and configurations.

2. Configure Spark Properly: When setting up your Spark application, it's critical to go through the configuration options. Disable services that you do not need, limit permissions, and enable encryption features where possible.

3. Manage Access with Authentication: Use Spark’s built-in authentication mechanisms to control who can access the Spark cluster. Configure it to use 'shared secret' authentication or integrate with a more robust authentication provider.

4. Enforce Authorization Rules: Define what users are allowed to do once they have access to Spark. Use Role-Based Access Control (RBAC) to ensure that users can only interact with the data and components necessary for their role.

5. Encrypt Data Transmission: Enable encryption for data being transmitted to and from Spark. This can be done by setting up SSL/TLS for the Spark web UI and encrypting the network traffic between nodes if you're running a distributed cluster.

6. Secure Data Storage: If Spark is reading or writing data from/to persistent storage like HDFS or S3, make sure those stores are secured and encrypted as well. Use Hadoop’s transparent data encryption or S3’s server-side encryption, for example.

7. Utilize Data Masking and Tokenization: When working with sensitive data, consider masking the data within your application to obfuscate any personally identifiable information (PII) before processing it with Spark.

8. Audit Regularly: Configuring logging and auditing within your Spark applications will allow you to monitor and inspect who did what and when. This is key for detecting potential breaches and unauthorized access.

9. Update and Patch: Keep your Spark version up to date with the latest releases which often contain important security fixes. The same goes for any other software used within your Spark ecosystem.

10. Train Your Team: Ensure that everyone working with Spark applications understands best practices for data security and their role in protecting that data. Regular training can help in preventing accidental leaks or incorrect configurations.

By following these steps, you can bolster the security and data privacy of your Spark applications. Remember, security is an ongoing process that extends beyond initial setup — it requires constant vigilance and updates to stay ahead of potential threats.