andormarkus commented on issue #2325: URL: https://github.com/apache/iceberg-python/issues/2325#issuecomment-3214254167
We're experiencing this exact same memory leak in production AWS Lambda functions using pyiceberg. Our data shows the same avro/reader.py line growth: **Memory progression across Lambda invocations (same 50MB file):** - 1st run: `reader.py:330: 52.8 MiB` - 2nd run: `reader.py:330: 88.0 MiB` - 3rd run: `reader.py:330: 106 MiB` Memory grows from 1.4GB to 2GB+ after just 5 invocations processing identical files. Despite aggressive cleanup attempts with `gc.collect()` and `libc.malloc_trim(0)`, the avro reader allocations persist between Lambda executions. Our logs confirm @Declow's findings. This is causing production Lambda functions to hit memory limits and crash. Happy to test any proposed fixes in our production environment with concurrent Lambda executions. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: issues-unsubscr...@iceberg.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@iceberg.apache.org For additional commands, e-mail: issues-h...@iceberg.apache.org
