Heap Space issue in flow

[ARAVINDA11]

@Ankur Bawiskar  @Community Alums  @Sohail Khilji  @Maik Skoddow  or anyone please help

How can I solve the Heap size issue 

what is the maximum memory size is allowed in MID SERVER

[sanketgoyal]

The “java.lang.OutOfMemoryError: Java heap space” error occurs when your program attempts to add more data into the heap space area, but there isn’t enough room for it. Here are some ways to address this issue:

Increase Heap Space:
You can increase the memory allocated to the Java Virtual Machine (JVM) heap space using the -Xmx option. For example:
java -Xmx2g YourProgram
This allocates 2 gigabytes of RAM as the maximum heap size for your application.

Profiling:
Profiling tools like NetBeans’ profiler or jvisualvm can help identify memory leaks and inefficient memory usage patterns in your application.
Investigate where many objects are being created and when objects get garbage collected.

Split Flows:
If you encounter this error in a flow, consider splitting it into smaller, separate flows. This can help manage memory usage3.
Remember that increasing heap size doesn’t guarantee solving all errors, so profiling and optimizing memory usage are essential steps to address this issue.

[Sohail Khilji]

HI @ARAVINDA11 ,

• 32-bit JVMs which expect to have a single large chunk of memory cannot use more than 2 Gb heap memory.

Refer > https://support.servicenow.com/kb?id=kb_article_view&sysparm_article=KB0750475

I hope this helps...

[jackj8171259805]

A Java heap space issue occurs when the application tries to use more memory than the JVM’s allocated maximum heap size. To solve this, you can first review your process or data flow to ensure it is optimized — for example, limit the amount of data loaded at once, avoid holding large datasets in memory unnecessarily, and break large tasks into smaller chunks. Suppose if you feel the optimization isn’t solving the issue you are facing, then you can try to increase the JVM heap size for the MID Server by adjusting the wrapper.java.maxmemory setting in the wrapper-override.conf file.

See if you can optimize your flow and scripts to process smaller data chunks, close unused connections, or clear large objects from memory sooner. Sometimes, breaking a large job into smaller steps drastically reduces memory needs.

Another suggestion would be to try increasing the JVM heap size. Though basic steps, its always advised to know you max and min JVM limit that you have. 32-bit Java: Limited to ~1.5–2 GB max heap and 64-bit Java: Can go much higher, but you should stay within the available physical memory. After any change you implement, kindly monitor the changes to know if the OutOfMemoryError still occurs and whether garbage collection is behaving normally.

Note: Increasing heap size should be the last step after optimizing flows and queries, otherwise you risk just delaying the problem instead of solving it.

You can check out this blog https://blog.heaphero.io/java-outofmemoryerror-heap-space/  to understand more about this Java Heap Space error.

[jackj8171259805]

A Java heap space issue occurs when the application tries to use more memory than the JVM’s allocated maximum heap size. To solve this, you can first review your process or data flow to ensure it is optimized — for example, limit the amount of data loaded at once, avoid holding large datasets in memory unnecessarily, and break large tasks into smaller chunks. Suppose if you feel the optimization isn’t solving the issue you are facing, then you can try to increase the JVM heap size for the MID Server by adjusting the wrapper.java.maxmemory setting in the wrapper-override.conf file.
See if you can optimize your flow and scripts to process smaller data chunks, close unused connections, or clear large objects from memory sooner. Sometimes, breaking a large job into smaller steps drastically reduces memory needs.
Another suggestion would be to try increasing the JVM heap size. Though basic steps, its always advised to know you max and min JVM limit that you have. 32-bit Java: Limited to ~1.5–2 GB max heap and 64-bit Java: Can go much higher, but you should stay within the available physical memory. After any change you implement, kindly monitor the changes to know if the OutOfMemoryError still occurs and whether garbage collection is behaving normally.
Note: Increasing heap size should be the last step after optimizing flows and queries, otherwise you risk just delaying the problem instead of solving it.
You can check out this blog How to Solve OutOfMemoryError: Java heap space to understand more about this Java Heap Space error.