RVR-OOM-500

Updated 9 November 2026

Issue summary

The error code RVR-OOM-500 indicates that a Data Flow run was terminated before it could complete. This typically occurs when the task process exceeds its memory limit. For example, a source task might extract or process more data at once than the run environment can hold in memory.

The run shows the failure in the Activities drawer, in the warning or error box and in the failed task's log.

Error message

The error message reads as follows:

[RVR-OOM-500]: The data flow run was terminated, possibly because the worker process exceeded its memory limit. Try to reduce the data volume of the task (for example, {remediation}), or contact Boomi support for assistance.

The {remediation} placeholder changes based on the source type of the failed task:

• Generic (load and target tasks): filter rows or columns, or load the data in smaller batches
• Database (RDBMS) sources: reduce the Exporter Chunk Size setting in the source table settings, filter the query, or use incremental loading to load fewer rows per run
• REST and API sources: reduce the amount of data returned per request by adjusting the pagination settings or adding filters, or use incremental loading
• MongoDB sources: in the Max Rows In Batch source table setting, lower the value if using Manual Batch Size, or switch to Dynamic Batch Size (recommended) if not already selected, or use incremental loading if already on Dynamic Batch Size

Action steps

To resolve the error, reduce the amount of data the failing task handles at once:

1. Reduce the batch or chunk size. In the source table settings, lower the batch or chunk size. For database sources, change Exporter Chunk Size. For MongoDB sources, change Max Rows In Batch, or switch to Dynamic Batch Size.
2. Filter the data. Filter rows or columns, add filters to the query, or adjust the API request (pagination settings or filters) so that each run returns less data.
3. Use incremental loading. Load the data in smaller portions across multiple runs instead of in one full load.

note

If the issue persists or you need help, open a support case with Data Integration Support. In the console sidebar, select Help > Contact Us and follow the instructions.