Manage concurrent write conflicts in Apache Iceberg on the AWS Glue Data Catalog

This article provides an in-depth guide to managing concurrent write conflicts in Apache Iceberg tables using AWS Glue Data Catalog. The key insights include:

• Two primary types of conflicts: catalog commit conflicts (automatically retryable) and data update conflicts (requiring custom handling)
• Iceberg's concurrency model uses optimistic transaction control with metadata and data layers
• Supports two isolation levels: Serializable and Snapshot isolation

Implementation strategies for handling conflicts include:

• Configuring retry properties for catalog commit conflicts
• Implementing custom error handling with exponential backoff for data update conflicts
• Narrowing the scope of maintenance operations to minimize potential conflicts

The article provides practical code examples in PySpark demonstrating retry mechanisms for streaming data ingestion and MERGE operations in both Spark and AWS Glue environments.