Tried to update server.xml, deleted dumps and temporary cache files from C:\Users\username\AppData\Local\javasharedresources
And still not able to start the server.
This is the following error message I get:
JVMDUMP010I Java dump written to C:\WAS8\profiles\AppSrv02\bin\javacore.20150210.094417.6468.0009.txt
JVMDUMP013I Processed dump event "systhrow", detail "java/lang/OutOfMemoryError".
There could be multiple causes for the OutOfMemoryError exceptions. It could be that there is a memory leak in one of the applications that is loaded on startup, or the maximum heap size is not set high enough to support all of the components loaded on startup.
It is best to go through a troubleshooting exercise. I suggest you download heap analyzer tool from here and analyze the javacore file to see where the potential leak, if any, could be.
If you can't find a memory leak, try increasing the JVM maximum heap size. Check that your host system has enough RAM to support the chosen maximum JVM heap size.
Earlier I didn't update the server.xml with correct arguments and once I updated server.xml with genericJvmArguments="-Xms1024M -Xmx2048M" and InitialHeapSize="1024" maximumHeapSize="2048", I was able to start the server.
Related
After upgrading from PostgreSQL 9.6 to 10 and also updating the overlying application (Trend Micro Deep Security), we see an increase in the overall shared memory utilization by more than 300%.
Currently the shared memory is around 3GB, which aligns with the shared_buffer parameter, set to 3072MB. Using ps, top and pmap I was able to tell that almost the entire shared memory is used by postgres-related processes.
However, I would like to know what's the actual cause of that increase. Is there anyway to identify the real root cause?
We're running our application in Wildfly 14.0.1, with a -Xmx of 4096, running with OpenJDK 11.0.2. I've been using VisualVM 1.4.2 to monitor our heap since we previously were having OOM exceptions (because our -Xmx was only 512 which was incredibly bad).
While we are well within our memory allocation now, we have no more OOM exceptions happening, and even with a good amount of clients and processing happening we're nowhere near the -Xmx4096 (the servers have 16GB so memory isn't an issue), I'm seeing some strange heap behavior that I can't figure out where it's coming from.
Using VisualVM, Eclipse MemoryAnalyzer, as well as heaphero.io, I get summaries like the following:
Total Bytes: 460,447,623
Total Classes: 35,708
Total Instances: 2,660,155
Classloaders: 1,087
GC Roots: 4,200
Number of Objects Pending for Finalization: 0
However, in watching the Heap Monitor, I see the Used Heap over a 4 minute time period increase by about 450MB before the GC runs and drops back down only to spike again. Here's an image:
This is when no clients are connected and nothing is actively happening in our application. We do use Apache File IO to monitor remote directories, we have JMS topics, etc. so it's not like the application is completely idle, but there's zero logging and all that.
My largest objects are the well-known io.netty.buffer.PoolChunk, which in the heap dumps are about 60% of my memory usage, the total is still around 460MB so I'm confused why the heap monitor is going from ~425MB to ~900MB repeatedly, and no matter where I take my snapshots, I can't see any large increase of object counts or memory usage.
I'm just seeing a disconnect between the heap monitor, and .hprof analysis. So there doesn't see a way to tell what's causing the heap to hit that 900MB peak.
My question is if these heap spikes are totally expected when running within Wildfly, or is there something within our application that is spinning up a bunch of objects that then get GC'd? In doing a Component report, objects in our application's package structure make up an extremely small amount of the dump. Which doesn't clear us, we easily could be calling things without closing appropriately, etc.
I have a question based on my experience trying to implement memory requests/limits correctly in an OpenShift OKD cluster. I started by setting no request, then watching to see what cluster metrics reported for memory use, then setting something close to that as a request. I ended up with high-memory-pressure nodes, thrashing, and oom kills. I have found I need to set the requests to something closer to the VIRT size in ‘top’ (include the program binary size) to keep performance up. Does this make sense? I'm confused by the asymmetry between request (and apparent need) and reported use in metrics.
You always need to leave a bit of memory headroom for overhead an memory spills. If for some reason the container exceeds the memory, either from your application, from your binary of some garbage collection system it will get killed. For example, this is common in Java apps, where you specify a heap and you need an extra overhead for the garbage collector and other things such as:
Native JRE
Perm / metaspace
JIT bytecode
JNI
NIO
Threads
This blog explains some of them.
I have a Streams application with a GlobalKtable backed by RocksDB that’s failing. I was originally getting the error described in https://issues.apache.org/jira/browse/KAFKA-6327, so I upgraded RocksDB to v5.14.2, which now gives a more explicit error: org.rocksdb.RocksDBException: While open a file for appending: /kafka_streams/...snip.../000295.sst: No space left on device
The directory in which the RocksDB spills to disk (a file mount on RHEL) seems to have ample space (Size: 5.4G Used: 2.8G Available: 2.6G Use%: 52%). I'm assuming that it's actually trying to allocate more than the remaining 2.6G, but that seems unlikely; there isn't that much data in the topic.
I found details on configuring RocksDB away from the defaults at https://docs.confluent.io/current/streams/developer-guide/config-streams.html#rocksdb-config-setter, but I don't see anything obvious that could potentially resolve the issue.
I haven't found any bug reports related to an issue like this, and I'm at a loss for troubleshooting next steps.
Edited to add:
I just ran the streams application on my local development machine against the same Kafka environment having the problem above. While the state stores were being loaded, the state store directory drifted up to a high of 3.1G and then settled at around 2.1G. It never got close to the 5G available on our development server. I haven't gotten any closer to finding an answer.
I never found an answer to why the disk usage in the deployed environment was behaving this way, but I eventually got more space allocated out of desperation; as the stream was processing, it consumed as much as 14GB of space before settling down around 3-4GB. I assume the disk space error was because RocksDB was trying to allocate space, not that it had written to it.
I've added a 'rule of thumb' that I should allocate 4x the disk space I expect for streaming applications.
i am getting below error when i am trying to fetch more then 300000 records.
m using link to fetch records and using muiltiple classes.
Error: java.lang.OutOfMemoryError: GC overhead limit exceeded
please let me know solution for this.
Thnaks
In your case, memory allocated to JVM is not sufficient.
You can try by allocating more memory as follows :
Run --> Run Configurations --> select the "JRE" tab --> then enter -Xmx2048m
I believe you are running program with default VM arguments.
You can also figure out memory requirement by performing heap dump analysis or memory analyzer.
Even though this may resolve your issue temporarily (depending upon how much memory is required for 300000 records), I would suggest to do changes in your program, such as fetching records in batches.
I would suggest to refer to this post.
How to deal with "java.lang.OutOfMemoryError: Java heap space" error (64MB heap size)