AuthZ Support For Spark 4.0 Compilation Issues And Solutions

Hey everyone,

I've been diving deep into integrating AuthZ with Spark 4.0, and I wanted to share my findings and kick off a discussion. This is super important for us as we move towards newer Spark versions, ensuring our security and authorization features remain top-notch. I've run into a few snags during the compilation process, and I'm hoping we can brainstorm together to find the best solutions. Let's get into the details!

Understanding AuthZ and Its Importance

Authorization, often abbreviated as AuthZ, is the mechanism that determines what a user is allowed to access. In the context of Spark, this means controlling which data, tables, or even specific rows and columns a user can view or manipulate. Proper AuthZ is crucial for several reasons:

• Data Security: It prevents unauthorized access to sensitive information, ensuring that only the right people can see the right data.
• Compliance: Many regulations, such as GDPR and HIPAA, require strict access controls to protect data privacy. AuthZ helps organizations meet these requirements.
• Data Governance: It enforces policies that govern how data is used and accessed within an organization.
• Collaboration: It enables multiple users to work with the same data without risking accidental or malicious data breaches.

Without effective AuthZ, organizations risk data leaks, compliance violations, and a general lack of control over their data assets. This is why integrating AuthZ seamlessly with Spark is a critical task.

The Significance of Spark 4.0 Support

Spark 4.0 brings a host of new features and improvements, including enhanced performance, better support for SQL standards, and new APIs. As organizations upgrade to Spark 4.0 to take advantage of these benefits, it’s essential that AuthZ mechanisms keep pace. This means ensuring that AuthZ solutions are compatible with the new Spark version and can leverage its features to provide even more granular and efficient access control.

Supporting Spark 4.0 for AuthZ is not just about maintaining compatibility; it’s about enhancing the overall security posture of Spark deployments. By integrating AuthZ tightly with Spark 4.0, we can ensure that data access policies are enforced consistently and effectively, regardless of the Spark version in use.

The Challenge: Compiling Kyuubi with Spark 4.0

Recently, I tried to compile Kyuubi, which is a fantastic project for providing a unified interface to Spark, with Spark 4.0 support. For those who aren't familiar, Kyuubi acts as a bridge, making it easier to interact with Spark in a secure and governed way. It's a tool that many of us rely on, so keeping it up-to-date is super important. When attempting the compilation, I ran into a few errors that I think are worth discussing. I used the following command:

./build/dist --name custom-name --tgz --flink-provided --hive-provided -Pspark-4.0 -Pscala-2.13

This command is designed to build a distribution of Kyuubi with specific configurations, including Spark 4.0 support and Scala 2.13. However, the compilation process hit a snag, and here are the errors I encountered:

[INFO] compiling 57 Scala sources and 1 Java source to /home/xxx/work.d/yyy/kyuubi/extensions/spark/kyuubi-spark-authz/target/scala-2.13/classes ...
[ERROR] [Error] /home/xxx/work.d/yyy/kyuubi/extensions/spark/kyuubi-spark-authz/src/main/scala/org/apache/kyuubi/plugin/spark/authz/rule/rowfilter/FilterDataSourceV2Strategy.scala:19: object Strategy is not a member of package org.apache.spark.sql
[ERROR] [Error] /home/xxx/work.d/yyy/kyuubi/extensions/spark/kyuubi-spark-authz/src/main/scala/org/apache/kyuubi/plugin/spark/authz/rule/rowfilter/FilterDataSourceV2Strategy.scala:23: not found: type Strategy
[ERROR] [Error] /home/xxx/work.d/yyy/kyuubi/extensions/spark/kyuubi-spark-authz/src/main/scala/org/apache/kyuubi/plugin/spark/authz/ranger/RangerSparkExtension.scala:58: type mismatch;
 found   : org.apache.kyuubi.plugin.spark.authz.rule.rowfilter.FilterDataSourceV2Strategy.type
 required: v1.StrategyBuilder
    (which expands to)  org.apache.spark.sql.SparkSession => org.apache.spark.sql.execution.SparkStrategy
[ERROR] three errors found

These errors indicate that there are issues with the AuthZ components in Kyuubi when compiling with Spark 4.0. Specifically, the Strategy object seems to be missing from the org.apache.spark.sql package, and there's a type mismatch in the RangerSparkExtension. This is where I think we need to dig deeper and understand what changes in Spark 4.0 might be causing these issues.

Analyzing the Errors

Let’s break down these errors to get a clearer picture of what’s going on. The first error message, "object Strategy is not a member of package org.apache.spark.sql", suggests that the Strategy object, which is crucial for Spark's query planning and execution, is either moved or removed in Spark 4.0. This is a significant change that would definitely impact any AuthZ extensions that rely on it.

Similarly, the second error, "not found: type Strategy", reinforces the idea that the Strategy type is no longer available in the same location or form in Spark 4.0. This means that the Kyuubi AuthZ code needs to be adapted to the new Spark API.

The third error, a type mismatch in RangerSparkExtension, is particularly interesting. It indicates that the FilterDataSourceV2Strategy, which is responsible for filtering data sources in Spark, doesn’t align with the expected StrategyBuilder type in Spark 4.0. This could be due to changes in how Spark strategies are defined or how they interact with extensions.

These errors collectively point to the fact that Spark 4.0 has introduced breaking changes in its internal APIs, particularly around query planning and extension mechanisms. This is not uncommon in major version upgrades, but it does require careful attention and code adjustments to ensure compatibility.

Potential Causes and Solutions

So, what could be causing these errors, and how can we fix them? Here are a few potential causes and some initial ideas for solutions:

1. API Changes in Spark 4.0:

   • Cause: As mentioned earlier, Spark 4.0 might have moved or renamed the Strategy object and related types. The interfaces for creating and registering Spark strategies might also have changed.
   • Solution: We need to dive into the Spark 4.0 API documentation and identify where the Strategy object and related types have moved. We might need to update the Kyuubi AuthZ code to use the new API and adjust how strategies are registered.

2. Incompatible Extension Mechanisms:

   • Cause: Spark 4.0 might have introduced changes in how extensions are registered and interact with the Spark engine. The StrategyBuilder interface, which is used to register custom strategies, might have been modified.
   • Solution: We need to understand the new extension mechanisms in Spark 4.0 and update the RangerSparkExtension to comply with the new requirements. This might involve changing how the FilterDataSourceV2Strategy is registered or how it interacts with the Spark query planner.

3. Dependency Conflicts:

   • Cause: Although less likely, there could be dependency conflicts between Kyuubi and Spark 4.0. Certain libraries or components might be incompatible, leading to compilation errors.
   • Solution: We should review the dependencies of Kyuubi and ensure they are compatible with Spark 4.0. This might involve updating library versions or making other adjustments to the project’s build configuration.

Diving Deeper into Specific Errors

Let’s focus on the error related to FilterDataSourceV2Strategy and the StrategyBuilder. The error message indicates a type mismatch, suggesting that the way strategies are built and registered has changed in Spark 4.0. In Spark, strategies are crucial components of the query planner, responsible for transforming a logical plan into a physical plan. If the mechanism for registering these strategies has changed, it would directly impact extensions like Kyuubi AuthZ.

To address this, we need to investigate how Spark 4.0 handles strategy registration. This might involve:

• Examining Spark 4.0’s source code: Looking at the relevant parts of Spark’s codebase can give us insights into the new strategy registration process.
• Reviewing Spark 4.0 documentation: Official documentation and release notes might provide details on API changes and migration guides.
• Consulting Spark community: Engaging with the Spark community can provide valuable perspectives and solutions.

Once we understand the new strategy registration mechanism, we can adapt the RangerSparkExtension accordingly. This might involve creating a new strategy builder or adjusting the existing one to fit the Spark 4.0 requirements.

Next Steps and Call for Collaboration

So, where do we go from here? I think the next steps should involve:

1. In-depth API Review: We need to thoroughly review the Spark 4.0 API, focusing on changes related to query planning, extension mechanisms, and strategy registration. This will help us pinpoint the exact causes of the errors.
2. Code Adaptation: Based on the API review, we need to adapt the Kyuubi AuthZ code to align with the new Spark 4.0 APIs. This might involve modifying existing classes, creating new ones, or adjusting the build configuration.
3. Testing and Validation: Once the code is adapted, we need to perform rigorous testing to ensure that AuthZ works correctly with Spark 4.0. This should include unit tests, integration tests, and end-to-end tests.

I believe that tackling this challenge requires a collaborative effort. I'm reaching out to the community to see if anyone has already encountered these issues or has insights into the Spark 4.0 API changes. If you’re willing to contribute, please feel free to share your thoughts, ideas, and solutions. Together, we can ensure that Kyuubi and AuthZ seamlessly support Spark 4.0.

Call to Action

• Share Your Insights: Have you worked with Spark 4.0 and AuthZ? Do you have any insights into the API changes or potential solutions? Please share your thoughts!
• Join the Discussion: Let’s discuss the potential causes and solutions in detail. Your input can help us move forward.
• Contribute Code: If you’re willing to contribute code, we’d love to have your help. Let’s work together to adapt Kyuubi AuthZ for Spark 4.0.

I'm also willing to submit a PR with guidance from the Kyuubi community to fix this issue. Let's make this happen!

Thanks, everyone, for your time and collaboration. I'm looking forward to hearing your thoughts and working together to resolve this issue.

Conclusion

In conclusion, supporting AuthZ in Spark 4.0 is a critical step for ensuring data security and compliance in modern data processing environments. The compilation errors encountered while building Kyuubi with Spark 4.0 highlight the API changes and extension mechanism updates in the new Spark version. Addressing these issues requires a thorough review of the Spark 4.0 API, adaptation of the Kyuubi AuthZ code, and rigorous testing.

This is where the community’s collective expertise comes into play. By collaborating, sharing insights, and contributing code, we can overcome these challenges and ensure that AuthZ works seamlessly with Spark 4.0. Let’s work together to build a secure and efficient data processing ecosystem!

I encourage everyone to join the discussion, share their experiences, and contribute to the solution. Together, we can make Kyuubi AuthZ fully compatible with Spark 4.0 and beyond. Thanks for being a part of this journey!