@kapa.ai Detail: I'm using SQL Server as a Source & Snowflake as a Destination Issue: I have done the sync for 1 table which has a size of 5 GB & that table is successfully migrated via Airbyte But for 1 table which have a size of 3.2 GB still i am getting this error: "Terminating due to java.lang.OutOfMemoryError: Java heap space" at the source. Even though i think sufficient memory is free

It seems like you are encountering a

java.lang.OutOfMemoryError: Java heap space

error during the sync process from SQL Server to Snowflake. This issue is often related to the memory allocation for the Java process handling the sync. Here are some steps and considerations to help you resolve this issue: ### 1. Understanding Memory Allocation Airbyte's Java connectors, including the source connectors, follow Java's default behavior with container memory. By default, they will only use up to 1/4 of the host's allocated memory. For example, on a Docker agent with 8GB of RAM configured, a Java connector limits itself to 2GB of RAM and will see Out-of-Memory exceptions if this goes higher. The same applies to Kubernetes pods. ### 2. Adjusting Memory Limits You can customize the memory allocation by setting the

JOB_MAIN_CONTAINER_MEMORY_REQUEST

and

JOB_MAIN_CONTAINER_MEMORY_LIMIT

environment variables to higher values. This can help prevent the Out-of-Memory errors by allowing the Java process to use more memory. ### Steps to Adjust Memory Limits 1. Set Environment Variables: Adjust the memory limits by setting the following environment variables in your Docker or Kubernetes configuration:

bash    export JOB_MAIN_CONTAINER_MEMORY_REQUEST=4g    export JOB_MAIN_CONTAINER_MEMORY_LIMIT=8g

2. Restart Airbyte: After setting these environment variables, restart your Airbyte instance to apply the changes. ### 3. Monitor Memory Usage Ensure that your host machine has sufficient memory to accommodate the increased limits. You can monitor the memory usage of the source and destination containers to ensure they are within the expected range. ### Example from Documentation The Airbyte documentation provides an example of how memory usage can be calculated and adjusted: > "The Source worker reads up to 10,000 records in memory. This can present problems for database sources with tables that have large row sizes. e.g., a table with an average row size of 0.5MBs will require 0.5 * 10000 / 1000 = 5GBs of RAM." ### Relevant Links - [Scaling Airbyte Documentation](https://docs.airbyte.com/operator-guides/scaling-airbyte#memory) - [GitHub Issue on Memory Scaling](https://github.com/airbytehq/airbyte/issues/3439) By following these steps, you should be able to resolve the

OutOfMemoryError

and successfully sync your 3.2 GB table from SQL Server to Snowflake. If the issue persists, consider further increasing the memory limits or optimizing the data being processed. If you need more detailed guidance, please refer to the [Scaling Airbyte Documentation](https://docs.airbyte.com/operator-guides/scaling-airbyte#memory).