06-12-2015 11:22 AM - edited 03-01-2019 09:15 AM
Couldn't access tidal via web or java client, happened last two days and we have been runing 6.2 for months with no issue? If we recycle master agent resolves issue but not what we want to do doing daily. Please advise. Running 64 bit and 8 GB memory.
06-15-2015 04:56 AM
What o/s are you running on?
Have you tried something like adding -DXX:MaxPermSize=512m to JvmOptions?
Cheers
06-15-2015 09:41 AM
Windows 2008
07-07-2015 10:39 AM
We added more memeory to server
08-12-2015 11:06 AM
adding sp2 to master
09-05-2015 01:43 AM
Paul,
Did you solve your problem?: Most of the "out of heap errors" you get are, as you have already addressed, memory exhaustion. How many jobs do you execute per day? How many jobs at any given moment are you running? do you utilize any adapter connections? These are the questions you ask to appropriately size the amount of memory you dedicate to your server.
Also, when this problem recurs, it's helpful to fail over to backup and then back again. This is a less painful option than doing a full master restart.
Hope this helps,
-Dwayne
01-05-2026 12:37 AM
This error actually notifies us that the Tidal Master process is exhausting its Java heap memory. Even though the server has sufficient physical RAM, and the application has been running without issues for months, it has still ended up with a Java heap memory error. If you try to recycle the Master agent, this should be a temporary fix, as it will clear the heap. However, after clearing the heap memory usage will continue to build up until it reaches the configured limit. When it reaches the limit, of course, this will cause the Java clients to become unresponsive or inaccessible. This type of problem typically arises when the workload is heavy or if there is a memory leak. This usually causes objects to hold onto other objects in the heap than the expected time frame.
The issue is not related to the operating system or the JVM itself. It's mainly because of how much heap the Master JVM is configured to use and how memory is being consumed over time. It’s better to increase the JVM heap size, enable GC logging to observe memory behavior, and capture thread or heap dumps before restarting the service. Doing this will help you identify and permanently resolve the root cause, instead of relying on daily restarts. To learn more interesting details about the OutOfMemoryError: Java heap space error, you can check out this blog, How to Solve OutOfMemoryError: Java heap space. This will give you more insights about this Java heap space error.
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