Iceberg, S3, And Glue IAM Role ARN Support Documentation

by Alex Johnson 57 views

This article provides a comprehensive guide on the new feature that supports Iceberg with S3 and Glue IAM Role ARN, integrated into RisingWave. This enhancement, detailed in PR #23775 and merged on 2025-11-18, significantly improves RisingWave's capabilities in handling data stored in Iceberg format within S3, leveraging Glue for metadata management, and utilizing IAM roles for secure access. This article will walk you through the key concepts, benefits, configuration steps, and practical examples to help you effectively use this feature.

Understanding the Integration

At the heart of this feature is the ability to seamlessly integrate Iceberg, a popular open-source table format, with Amazon S3 for storage and AWS Glue for metadata cataloging. This integration allows RisingWave to efficiently read and write data in Iceberg tables stored in S3, while Glue acts as the central repository for table metadata. The use of IAM roles further enhances security by allowing RisingWave to access S3 resources using temporary credentials, without the need to manage long-term access keys. The primary benefit of this integration is the improved performance and scalability for data-intensive applications. By leveraging Iceberg's optimized data layout and metadata management, RisingWave can efficiently query large datasets stored in S3. Additionally, the use of IAM roles ensures secure access to data, adhering to the best practices for cloud security. The integration also simplifies data management by centralizing metadata in AWS Glue, making it easier to discover and manage Iceberg tables. RisingWave users can now build more robust and scalable data pipelines that leverage the benefits of Iceberg, S3, and Glue, while maintaining a high level of security. This feature is particularly useful for organizations dealing with large volumes of data and requiring efficient and secure data processing capabilities. RisingWave's ability to integrate with these services makes it a powerful tool for modern data engineering and analytics workflows. The enhancements not only improve performance but also streamline data management, providing a more cohesive and efficient data processing environment.

Key Concepts and Benefits

Iceberg Table Format

Iceberg is an open-source table format for huge analytic datasets. It adds tables to compute engines including Spark, Trino, Flink, Presto, and Hive. Iceberg avoids many of the common problems that affect Hive and Spark tables. Key features include schema evolution, hidden partitioning, and time travel. These features allow for more flexible and efficient data management, making it ideal for large-scale data warehousing and analytics applications.

Amazon S3 for Storage

Amazon S3 (Simple Storage Service) is a scalable, high-speed, web-based cloud storage service designed for online backup and archiving of data and application programs. It offers excellent durability, availability, and security, making it a popular choice for storing large datasets. S3 provides a cost-effective solution for storing and retrieving data, with various storage classes optimized for different access patterns and storage durations. Its integration with other AWS services makes it a cornerstone of many cloud-based data lakes and analytics platforms.

AWS Glue for Metadata Management

AWS Glue is a fully managed extract, transform, and load (ETL) service that makes it easy for customers to prepare and load their data for analytics. It includes a central metadata repository known as the AWS Glue Data Catalog, which stores metadata about tables, schemas, and partitions. Glue simplifies the process of discovering, transforming, and moving data, allowing users to focus on analyzing their data rather than managing infrastructure. Its integration with Iceberg allows for seamless metadata management, ensuring that RisingWave always has access to the latest table schemas and partitions.

IAM Roles for Secure Access

IAM (Identity and Access Management) roles provide a secure way to grant permissions to AWS services and applications. Instead of using long-term access keys, IAM roles allow services to assume temporary credentials, which are automatically rotated. This significantly reduces the risk of credential leakage and improves overall security posture. By using IAM roles, RisingWave can securely access S3 resources and Glue metadata without storing sensitive credentials directly within its configuration.

Benefits of the Integration

  • Improved Performance: Iceberg's optimized data layout and metadata management enable RisingWave to efficiently query large datasets stored in S3.
  • Scalability: The integration supports scalable data pipelines, allowing RisingWave to handle growing data volumes without performance degradation.
  • Enhanced Security: IAM roles ensure secure access to S3 resources and Glue metadata, adhering to best practices for cloud security.
  • Simplified Data Management: Glue centralizes metadata management, making it easier to discover and manage Iceberg tables.
  • Cost-Effectiveness: S3 provides a cost-effective storage solution, while Glue simplifies data management, reducing operational overhead.

Configuration Steps

To configure RisingWave to support Iceberg with S3 and Glue IAM Role ARN, follow these steps:

  1. Set up AWS Credentials: Ensure that RisingWave has access to AWS resources by configuring the necessary IAM roles and permissions. This involves creating an IAM role with the appropriate policies that allow RisingWave to access S3 buckets and Glue Data Catalog. The IAM role should have permissions to read and write data in S3, as well as read metadata from Glue. Additionally, ensure that the RisingWave service is configured to assume this IAM role. This can be done by attaching the IAM role to the RisingWave EC2 instance or ECS task, depending on the deployment environment.

  2. Configure S3 Bucket: Create an S3 bucket to store Iceberg data. It is recommended to configure bucket policies to restrict access to authorized users and services. Ensure that the bucket is configured with appropriate encryption settings to protect data at rest. Additionally, consider using S3 Lifecycle policies to automatically transition data to lower-cost storage classes based on access patterns.

  3. Set up AWS Glue: Set up the AWS Glue Data Catalog to manage Iceberg table metadata. This involves creating a Glue database and tables that correspond to the Iceberg tables stored in S3. Glue crawlers can be used to automatically discover and create table metadata based on the data stored in S3. Ensure that the Glue Data Catalog is configured with appropriate security settings to control access to metadata.

  4. Configure RisingWave: Configure RisingWave to connect to S3 and Glue using the IAM Role ARN. This involves updating the RisingWave configuration file with the necessary connection parameters, including the S3 endpoint, Glue catalog ID, and IAM Role ARN. The configuration file may also include settings for connection pooling, retry policies, and other performance-related parameters. It is important to validate the configuration to ensure that RisingWave can successfully connect to S3 and Glue.

  5. Create Iceberg Tables: Create Iceberg tables in S3 using RisingWave. This can be done using the CREATE TABLE statement with the FORMAT = ICEBERG option. When creating Iceberg tables, specify the S3 location for storing data and the Glue table name for metadata management. Additionally, define the table schema and partitioning strategy to optimize query performance. Consider using Iceberg's schema evolution capabilities to handle changes in data structure over time.

Detailed Configuration Steps

  • AWS Credentials: First, create an IAM role in the AWS Management Console. Attach policies that grant the necessary permissions, such as s3:GetObject, s3:PutObject, glue:GetTable, and glue:UpdateTable. Then, configure the RisingWave environment to assume this role. This typically involves setting environment variables or updating the RisingWave configuration file with the IAM Role ARN.
  • S3 Bucket: Create an S3 bucket using the AWS Management Console or AWS CLI. Configure bucket policies to restrict access and enable encryption at rest. Consider using S3 Lifecycle policies to manage storage costs by automatically transitioning data to lower-cost storage classes based on access patterns. Additionally, enable versioning to protect against accidental data loss.
  • AWS Glue: Set up AWS Glue by creating a Glue database. Use Glue crawlers to automatically discover and create table metadata based on the data stored in S3. Configure the crawler to run on a schedule to keep the metadata up-to-date. Ensure that the Glue Data Catalog is configured with appropriate security settings to control access to metadata.
  • RisingWave Configuration: Update the RisingWave configuration file (risingwave.conf) with the necessary connection parameters. This includes the S3 endpoint, Glue catalog ID, and IAM Role ARN. Additionally, configure connection pooling and retry policies to optimize performance and handle transient errors. Validate the configuration to ensure that RisingWave can successfully connect to S3 and Glue.
  • Create Iceberg Tables: Use the CREATE TABLE statement in RisingWave to create Iceberg tables. Specify the S3 location for storing data and the Glue table name for metadata management. Define the table schema and partitioning strategy to optimize query performance. Consider using Iceberg's schema evolution capabilities to handle changes in data structure over time.

Practical Examples

Creating an Iceberg Table

To create an Iceberg table in RisingWave, you can use the following SQL statement:

CREATE TABLE my_iceberg_table (
    id INT,
    name VARCHAR,
    value DOUBLE
)
WITH (
    FORMAT = 'ICEBERG',
    LOCATION = 's3://my-bucket/iceberg/my_table',
    GLUE_TABLE = 'my_glue_database.my_iceberg_table'
);

This statement creates an Iceberg table named my_iceberg_table with three columns: id, name, and value. The FORMAT = 'ICEBERG' option specifies that the table should be created in Iceberg format. The LOCATION option specifies the S3 location where the table data will be stored, and the GLUE_TABLE option specifies the Glue table name that will be used to manage the table metadata.

Querying an Iceberg Table

To query an Iceberg table in RisingWave, you can use standard SQL statements:

SELECT *
FROM my_iceberg_table
WHERE id > 100;

This query selects all rows from the my_iceberg_table where the id column is greater than 100. RisingWave leverages Iceberg's optimized data layout and metadata management to efficiently execute the query, even on large datasets.

Writing Data to an Iceberg Table

To write data to an Iceberg table in RisingWave, you can use the INSERT statement:

INSERT INTO my_iceberg_table
VALUES (1, 'Alice', 10.5),
       (2, 'Bob', 20.3),
       (3, 'Charlie', 15.2);

This statement inserts three rows into the my_iceberg_table. RisingWave handles the underlying Iceberg operations, such as creating new data files and updating metadata, transparently to the user.

Using Time Travel

Iceberg supports time travel, which allows you to query the table as it existed at a specific point in time. To query a table at a specific snapshot, you can use the FOR VERSION AS OF clause:

SELECT *
FROM my_iceberg_table FOR VERSION AS OF 1234567890;

This query selects all rows from the my_iceberg_table as it existed at snapshot 1234567890. This feature is useful for auditing, debugging, and reproducing past states of the data.

Best Practices and Considerations

  • Partitioning: Choose an appropriate partitioning strategy based on your query patterns. Partitioning can significantly improve query performance by reducing the amount of data that needs to be scanned.
  • Compaction: Regularly compact Iceberg data files to optimize query performance. Compaction merges small data files into larger ones, reducing the overhead of scanning multiple files.
  • Schema Evolution: Use Iceberg's schema evolution capabilities to handle changes in data structure over time. This allows you to add, delete, or modify columns without disrupting existing queries.
  • Monitoring: Monitor the performance of RisingWave and Iceberg to identify and address any issues. This includes monitoring query execution time, data volume, and resource utilization.
  • Security: Implement appropriate security measures to protect your data. This includes configuring IAM roles, bucket policies, and encryption settings.

Conclusion

The integration of Iceberg with S3 and Glue IAM Role ARN in RisingWave represents a significant enhancement in data processing capabilities. By leveraging Iceberg's optimized data layout, S3's scalability, and Glue's metadata management, RisingWave users can build more efficient and secure data pipelines. The use of IAM roles further enhances security by allowing RisingWave to access AWS resources using temporary credentials. This feature is particularly beneficial for organizations dealing with large volumes of data and requiring high performance and scalability. By following the configuration steps and best practices outlined in this article, you can effectively use this feature to improve your data processing workflows. For more detailed information and advanced configurations, please refer to the official RisingWave documentation and Iceberg documentation.

For further reading on Iceberg, you can visit the official Apache Iceberg documentation.