The java.lang.OutOfMemoryError: Java heap space error actually tells you that your Talend job that you have explained is trying to use more memory than the JVM heap can provide even though you have set higher value, -Xms4096m and -Xmx8192m. This often happens in data integration jobs processing large datasets, like your case with 6 million+ records, that also if components like tMap are configured to load entire datasets into memory.
I have provided you a few tuning and steps to follow that might help you resolve the OutOf MemoryError you are facing,
Try enabling row-by-row processing. Wherever possible try to enable it instead of loading all data at once. In tMap, disable the option “Load lookup flow before starting” unless necessary.
If possible, process data in smaller chunks using limit and offset queries in your tPostgresqlInput.
Review the buffer size and memory settings in Talend Studio preferences. Increase the JVM memory there too if required.
Ensure unnecessary columns are not selected or carried through your flow — only fetch and map what’s strictly needed.
If you’re using lookup tables, switch from load once to reload at each row if lookup size is large.
Lastly, monitor the job execution via a memory profiler or Talend’s built-in monitoring tools to pinpoint any component causing excessive memory use.
Implementing these few changes might help you prevent the OutOfMemoryError. Hope this also will allow your job to run smoothly with large datasets.
