I have been attempting to find some suspected memory errors using valgrind.
Before the program being profiled even reaches the point I wish to profile, it bails as calls to mmap start failing. These calls succeed when it is not under valgrind.
Is there some kind of limit on the number of file mappings / mapped memory that is possible under valgrind ?
The size of files being mapped is large (around 600Gb total)
By default, valgrind does not support so much memory.
On linux, the default (hardcoded in the sources) is 128 GB.
Note that the memory was increased from 64GB to 128 GB in commit
e706fbfa9fa563e81d6dc09de2bf785b2c34e84e.
The changes in this commit will point at the needed changes to further
increase the max memory supported by valgrind.
The file coregrind/m_aspacemgr/aspacemgr-linux.c contains comments explaining
the strategy to manage the memory and the mappings.
This indicates that possibly a fixed mapping of a size bigger that 128GB
might be accepted, if you mmap it above the (current linux) 128 GB limit.
(I have not tried this so this needs confirmation).
There are also other hardcoded maxima, e.g. the max nr of segments
is defined (on linux) to be 30000 in aspacemgr-linux.c.
The current limits (Dec 2022) for 64 bit systems are:
macOS
aspacem_maxAddr = (Addr) 0x7fffffffffff;
That's 128TB though I rather doubt it works
FreeBSD
aspacem_maxAddr = (Addr) (Addr)0x800000000UL - 1; // 32G
Solaris and Linux
aspacem_maxAddr = (Addr)0x2000000000ULL - 1; // 128G
The limits are lower, obviously, for 32bit versions and also for special builds for running Valgrind in Valgrind.
I'll see if increasing the FreeBSD limit to also be 128GB causes any problems.
EDIT:
The limit for FreeBSD amd64 is now also 128GB.
Related
Which is the maximum amount of memory one can achieve in .NET managed code? Does it depend on the actual architecture (32/64 bits)?
There are no hard, exact figure for .NET code.
If you run on 32 bit Windows; your process can address up to 2 GB, 3 GB if the /3GB switch is used on Windows Server 2003.
If you run a 64 bit process on a 64 bit box your process can address up to 8 TB of address space, if that much RAM is present.
This is not the whole story however, since the CLR takes some overhead for each process. At the same time, .NET will try to allocate new memory in chunks; and if the address space is fragmented, that might mean that you cannot allocate more memory, even though some are available.
In C# 2.0 and 3.0 there is also a 2G limit on the size of a single object in managed code.
The amount of memory your .NET process can address depends both on whether it is running on a 32/64 bit machine and whether or not it it running as a CPU agnostic or CPU specific process.
By default a .NET process is CPU agnostic so it will run with the process type that is natural to the version of Windows. In 64 bit it will be a 64 bit process, and in 32 bit it will be a 32 bit process. You can force a .NET process though to target a particular CPU and say make it run as a 32 bit process on a 64 bit machine.
If you exclude the large address aware setting, the following are the various breakdowns
32 bit process can address 2GB
64 bit process can address 8TB
Here is a link to the full breakdown of addressable space based on the various options Windows provides.
http://msdn.microsoft.com/en-us/library/aa366778.aspx
For 64 bit Windows the virtual memory size is 16 TB divided equally between user and kernel mode, so user processes can address 8 TB (8192 GB). That is less than the entire 16 EB space addressable by 64 bits, but it is still a whole lot more than what we're used to with 32 bits.
I have recently been doing extensive profiling around memory limits in .NET on a 32bit process. We all get bombarded by the idea that we can allocate up to 2.4GB (2^31) in a .NET application but unfortuneately this is not true :(. The application process has that much space to use and the operating system does a great job managing it for us, however, .NET itself seems to have its own overhead which accounts for aproximately 600-800MB for typical real world applications that push the memory limit. This means that as soon as you allocate an array of integers that takes about 1.4GB, you should expect to see an OutOfMemoryException().
Obviously in 64bit, this limit occurs way later (let's chat in 5 years :)), but the general size of everything in memory also grows (I am finding it's ~1.7 to ~2 times) because of the increased word size.
What I know for sure is that the Virtual Memory idea from the operating system definitely does NOT give you virtually endless allocation space within one process. It is only there so that the full 2.4GB is addressable to all the (many) applications running at one time.
I hope this insight helps somewhat.
I originally answered something related here (I am still a newby so am not sure how I am supposed to do these links):
Is there a memory limit for a single .NET process
The .NET runtime can allocate all the free memory available for user-mode programs in its host. Mind that it doesn't mean that all of that memory will be dedicated to your program, as some (relatively small) portions will be dedicated to internal CLR data structures.
In 32 bit systems, assuming a 4GB or more setup (even if PAE is enabled), you should be able to get at the very most roughly 2GB allocated to your application. On 64 bit systems you should be able to get 1TB. For more information concerning windows memory limits, please review this page.
Every figure mentioned there has to be divided by 2, as windows reserves the higher half of the address space for usage by code running in kernel mode (ring 0).
Also, please mind that whenever for a 32 bit system the limit exceeds 4GB, use of PAE is implied, and thus you still can't really exceed the 2GB limit unless the OS supports 4gt, in which case you can reach up to 3GB.
Yes, in a 32 bits environment you are limited to a 4GB address-space but Windows claims about half. On a 64 bits architecture it is, well, a lot bigger. I believe it's 4G * 4G
And on the Compact Framework it usually is in the order of a few hundred MB
I think other answers being quite naive, in real world after 2GB of memory consumption your application will behave really badly. In my experience GUIs generally go massively clunky, unsusable after lots of memory consumptions.
This was my experience, obviously actual cause of this can be objects grows too big so all operations on those objects takes too much time.
The following blog post has detailed findings on x86 and x64 max memory. It also has a small tool (source available) which allows easy easting of the different memory options:
http://www.guylangston.net/blog/Article/MaxMemory.
For my application, the memory used by the Java process is much more than the heap size.
The system where the containers are running starts to have memory problem because the container is taking much more memory than the heap size.
The heap size is set to 128 MB (-Xmx128m -Xms128m) while the container takes up to 1GB of memory. Under normal condition, it needs 500MB. If the docker container has a limit below (e.g. mem_limit=mem_limit=400MB) the process gets killed by the out of memory killer of the OS.
Could you explain why the Java process is using much more memory than the heap? How to size correctly the Docker memory limit? Is there a way to reduce the off-heap memory footprint of the Java process?
I gather some details about the issue using command from Native memory tracking in JVM.
From the host system, I get the memory used by the container.
$ docker stats --no-stream 9afcb62a26c8
CONTAINER ID NAME CPU % MEM USAGE / LIMIT MEM % NET I/O BLOCK I/O PIDS
9afcb62a26c8 xx-xxxxxxxxxxxxx-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx.0acbb46bb6fe3ae1b1c99aff3a6073bb7b7ecf85 0.93% 461MiB / 9.744GiB 4.62% 286MB / 7.92MB 157MB / 2.66GB 57
From inside the container, I get the memory used by the process.
$ ps -p 71 -o pcpu,rss,size,vsize
%CPU RSS SIZE VSZ
11.2 486040 580860 3814600
$ jcmd 71 VM.native_memory
71:
Native Memory Tracking:
Total: reserved=1631932KB, committed=367400KB
- Java Heap (reserved=131072KB, committed=131072KB)
(mmap: reserved=131072KB, committed=131072KB)
- Class (reserved=1120142KB, committed=79830KB)
(classes #15267)
( instance classes #14230, array classes #1037)
(malloc=1934KB #32977)
(mmap: reserved=1118208KB, committed=77896KB)
( Metadata: )
( reserved=69632KB, committed=68272KB)
( used=66725KB)
( free=1547KB)
( waste=0KB =0.00%)
( Class space:)
( reserved=1048576KB, committed=9624KB)
( used=8939KB)
( free=685KB)
( waste=0KB =0.00%)
- Thread (reserved=24786KB, committed=5294KB)
(thread #56)
(stack: reserved=24500KB, committed=5008KB)
(malloc=198KB #293)
(arena=88KB #110)
- Code (reserved=250635KB, committed=45907KB)
(malloc=2947KB #13459)
(mmap: reserved=247688KB, committed=42960KB)
- GC (reserved=48091KB, committed=48091KB)
(malloc=10439KB #18634)
(mmap: reserved=37652KB, committed=37652KB)
- Compiler (reserved=358KB, committed=358KB)
(malloc=249KB #1450)
(arena=109KB #5)
- Internal (reserved=1165KB, committed=1165KB)
(malloc=1125KB #3363)
(mmap: reserved=40KB, committed=40KB)
- Other (reserved=16696KB, committed=16696KB)
(malloc=16696KB #35)
- Symbol (reserved=15277KB, committed=15277KB)
(malloc=13543KB #180850)
(arena=1734KB #1)
- Native Memory Tracking (reserved=4436KB, committed=4436KB)
(malloc=378KB #5359)
(tracking overhead=4058KB)
- Shared class space (reserved=17144KB, committed=17144KB)
(mmap: reserved=17144KB, committed=17144KB)
- Arena Chunk (reserved=1850KB, committed=1850KB)
(malloc=1850KB)
- Logging (reserved=4KB, committed=4KB)
(malloc=4KB #179)
- Arguments (reserved=19KB, committed=19KB)
(malloc=19KB #512)
- Module (reserved=258KB, committed=258KB)
(malloc=258KB #2356)
$ cat /proc/71/smaps | grep Rss | cut -d: -f2 | tr -d " " | cut -f1 -dk | sort -n | awk '{ sum += $1 } END { print sum }'
491080
The application is a web server using Jetty/Jersey/CDI bundled inside a fat far of 36 MB.
The following version of OS and Java are used (inside the container). The Docker image is based on openjdk:11-jre-slim.
$ java -version
openjdk version "11" 2018-09-25
OpenJDK Runtime Environment (build 11+28-Debian-1)
OpenJDK 64-Bit Server VM (build 11+28-Debian-1, mixed mode, sharing)
$ uname -a
Linux service1 4.9.125-linuxkit #1 SMP Fri Sep 7 08:20:28 UTC 2018 x86_64 GNU/Linux
https://gist.github.com/prasanthj/48e7063cac88eb396bc9961fb3149b58
Virtual memory used by a Java process extends far beyond just Java Heap. You know, JVM includes many subsytems: Garbage Collector, Class Loading, JIT compilers etc., and all these subsystems require certain amount of RAM to function.
JVM is not the only consumer of RAM. Native libraries (including standard Java Class Library) may also allocate native memory. And this won't be even visible to Native Memory Tracking. Java application itself can also use off-heap memory by means of direct ByteBuffers.
So what takes memory in a Java process?
JVM parts (mostly shown by Native Memory Tracking)
1. Java Heap
The most obvious part. This is where Java objects live. Heap takes up to -Xmx amount of memory.
2. Garbage Collector
GC structures and algorithms require additional memory for heap management. These structures are Mark Bitmap, Mark Stack (for traversing object graph), Remembered Sets (for recording inter-region references) and others. Some of them are directly tunable, e.g. -XX:MarkStackSizeMax, others depend on heap layout, e.g. the larger are G1 regions (-XX:G1HeapRegionSize), the smaller are remembered sets.
GC memory overhead varies between GC algorithms. -XX:+UseSerialGC and -XX:+UseShenandoahGC have the smallest overhead. G1 or CMS may easily use around 10% of total heap size.
3. Code Cache
Contains dynamically generated code: JIT-compiled methods, interpreter and run-time stubs. Its size is limited by -XX:ReservedCodeCacheSize (240M by default). Turn off -XX:-TieredCompilation to reduce the amount of compiled code and thus the Code Cache usage.
4. Compiler
JIT compiler itself also requires memory to do its job. This can be reduced again by switching off Tiered Compilation or by reducing the number of compiler threads: -XX:CICompilerCount.
5. Class loading
Class metadata (method bytecodes, symbols, constant pools, annotations etc.) is stored in off-heap area called Metaspace. The more classes are loaded - the more metaspace is used. Total usage can be limited by -XX:MaxMetaspaceSize (unlimited by default) and -XX:CompressedClassSpaceSize (1G by default).
6. Symbol tables
Two main hashtables of the JVM: the Symbol table contains names, signatures, identifiers etc. and the String table contains references to interned strings. If Native Memory Tracking indicates significant memory usage by a String table, it probably means the application excessively calls String.intern.
7. Threads
Thread stacks are also responsible for taking RAM. The stack size is controlled by -Xss. The default is 1M per thread, but fortunately things are not so bad. The OS allocates memory pages lazily, i.e. on the first use, so the actual memory usage will be much lower (typically 80-200 KB per thread stack). I wrote a script to estimate how much of RSS belongs to Java thread stacks.
There are other JVM parts that allocate native memory, but they do not usually play a big role in total memory consumption.
Direct buffers
An application may explicitly request off-heap memory by calling ByteBuffer.allocateDirect. The default off-heap limit is equal to -Xmx, but it can be overridden with -XX:MaxDirectMemorySize. Direct ByteBuffers are included in Other section of NMT output (or Internal before JDK 11).
The amount of direct memory in use is visible through JMX, e.g. in JConsole or Java Mission Control:
Besides direct ByteBuffers there can be MappedByteBuffers - the files mapped to virtual memory of a process. NMT does not track them, however, MappedByteBuffers can also take physical memory. And there is no a simple way to limit how much they can take. You can just see the actual usage by looking at process memory map: pmap -x <pid>
Address Kbytes RSS Dirty Mode Mapping
...
00007f2b3e557000 39592 32956 0 r--s- some-file-17405-Index.db
00007f2b40c01000 39600 33092 0 r--s- some-file-17404-Index.db
^^^^^ ^^^^^^^^^^^^^^^^^^^^^^^^
Native libraries
JNI code loaded by System.loadLibrary can allocate as much off-heap memory as it wants with no control from JVM side. This also concerns standard Java Class Library. In particular, unclosed Java resources may become a source of native memory leak. Typical examples are ZipInputStream or DirectoryStream.
JVMTI agents, in particular, jdwp debugging agent - can also cause excessive memory consumption.
This answer describes how to profile native memory allocations with async-profiler.
Allocator issues
A process typically requests native memory either directly from OS (by mmap system call) or by using malloc - standard libc allocator. In turn, malloc requests big chunks of memory from OS using mmap, and then manages these chunks according to its own allocation algorithm. The problem is - this algorithm can lead to fragmentation and excessive virtual memory usage.
jemalloc, an alternative allocator, often appears smarter than regular libc malloc, so switching to jemalloc may result in a smaller footprint for free.
Conclusion
There is no guaranteed way to estimate full memory usage of a Java process, because there are too many factors to consider.
Total memory = Heap + Code Cache + Metaspace + Symbol tables +
Other JVM structures + Thread stacks +
Direct buffers + Mapped files +
Native Libraries + Malloc overhead + ...
It is possible to shrink or limit certain memory areas (like Code Cache) by JVM flags, but many others are out of JVM control at all.
One possible approach to setting Docker limits would be to watch the actual memory usage in a "normal" state of the process. There are tools and techniques for investigating issues with Java memory consumption: Native Memory Tracking, pmap, jemalloc, async-profiler.
Update
Here is a recording of my presentation Memory Footprint of a Java Process.
In this video, I discuss what may consume memory in a Java process, how to monitor and restrain the size of certain memory areas, and how to profile native memory leaks in a Java application.
https://developers.redhat.com/blog/2017/04/04/openjdk-and-containers/:
Why is it when I specify -Xmx=1g my JVM uses up more memory than 1gb
of memory?
Specifying -Xmx=1g is telling the JVM to allocate a 1gb heap. It’s not
telling the JVM to limit its entire memory usage to 1gb. There are
card tables, code caches, and all sorts of other off heap data
structures. The parameter you use to specify total memory usage is
-XX:MaxRAM. Be aware that with -XX:MaxRam=500m your heap will be approximately 250mb.
Java sees host memory size and it is not aware of any container memory limitations. It doesn't create memory pressure, so GC also doesn't need to release used memory. I hope XX:MaxRAM will help you to reduce memory footprint. Eventually, you can tweak GC configuration (-XX:MinHeapFreeRatio,-XX:MaxHeapFreeRatio, ...)
There is many types of memory metrics. Docker seems to be reporting RSS memory size, that can be different than "committed" memory reported by jcmd (older versions of Docker report RSS+cache as memory usage).
Good discussion and links: Difference between Resident Set Size (RSS) and Java total committed memory (NMT) for a JVM running in Docker container
(RSS) memory can be eaten also by some other utilities in the container - shell, process manager, ... We don't know what else is running in the container and how do you start processes in container.
TL;DR
The detail usage of the memory is provided by Native Memory Tracking (NMT) details (mainly code metadata and garbage collector). In addition to that, the Java compiler and optimizer C1/C2 consume the memory not reported in the summary.
The memory footprint can be reduced using JVM flags (but there is impacts).
The Docker container sizing must be done through testing with the expected load the application.
Detail for each components
The shared class space can be disabled inside a container since the classes won't be shared by another JVM process. The following flag can be used. It will remove the shared class space (17MB).
-Xshare:off
The garbage collector serial has a minimal memory footprint at the cost of longer pause time during garbage collect processing (see Aleksey Shipilëv comparison between GC in one picture). It can be enabled with the following flag. It can save up to the GC space used (48MB).
-XX:+UseSerialGC
The C2 compiler can be disabled with the following flag to reduce profiling data used to decide whether to optimize or not a method.
-XX:+TieredCompilation -XX:TieredStopAtLevel=1
The code space is reduced by 20MB. Moreover, the memory outside JVM is reduced by 80MB (difference between NMT space and RSS space). The optimizing compiler C2 needs 100MB.
The C1 and C2 compilers can be disabled with the following flag.
-Xint
The memory outside the JVM is now lower than the total committed space. The code space is reduced by 43MB. Beware, this has a major impact on the performance of the application. Disabling C1 and C2 compiler reduces the memory used by 170 MB.
Using Graal VM compiler (replacement of C2) leads to a bit smaller memory footprint. It increases of 20MB the code memory space and decreases of 60MB from outside JVM memory.
The article Java Memory Management for JVM provides some relevant information the different memory spaces.
Oracle provides some details in Native Memory Tracking documentation. More details about compilation level in advanced compilation policy and in disable C2 reduce code cache size by a factor 5. Some details on Why does a JVM report more committed memory than the Linux process resident set size? when both compilers are disabled.
Java needs a lot a memory. JVM itself needs a lot of memory to run. The heap is the memory which is available inside the virtual machine, available to your application. Because JVM is a big bundle packed with all goodies possible it takes a lot of memory just to load.
Starting with java 9 you have something called project Jigsaw, which might reduce the memory used when you start a java app(along with start time). Project jigsaw and a new module system were not necessarily created to reduce the necessary memory, but if it's important you can give a try.
You can take a look at this example: https://steveperkins.com/using-java-9-modularization-to-ship-zero-dependency-native-apps/. By using the module system it resulted in CLI application of 21MB(with JRE embeded). JRE takes more than 200mb. That should translate to less allocated memory when the application is up(a lot of unused JRE classes will no longer be loaded).
Here is another nice tutorial: https://www.baeldung.com/project-jigsaw-java-modularity
If you don't want to spend time with this you can simply get allocate more memory. Sometimes it's the best.
How to size correctly the Docker memory limit?
Check the application by monitoring it for some-time. To restrict container's memory try using -m, --memory bytes option for docker run command - or something equivalant if you are running it otherwise
like
docker run -d --name my-container --memory 500m <iamge-name>
can't answer other questions.
I am working on a REST API that has an endpoint to download a file that could be > 2 GB in size. I have read that Java's FileChannel.transferTo(...) will use zero-copy if the OS supports it. My server is running on localhost during development on my MacBook Pro OS 10.11.6.
I compared the following two methods of writing file to response stream:
Copying a fixed number of bytes from FileChannel to WritableByteChannel using transferTo
Reading a fixed number of bytes from FileInputStream into a byte array (size 4096) and writing to OutputStream in a loop.
The time taken for a 5.2GB file is between 20 and 23 seconds with both methods. I tried transferTo with the fixed number of bytes in single transfer set to following values: 4KB (i.e. 4 * 1024), 1MB and 50MB. The time taken to write is in the same range in all the 3 cases.
Time taken is measured from before entering the while-loop to after exiting the while-loop, in which bytes are read from the file. This is all on the server side. The network hop time does not figure into this.
Any ideas on what the reason could be? I am quite sure MacOS 10.11.6 should support zero-copy (i.e. sendfile system call).
EDIT (6/18/2018):
I found the following blog post from 2015, saying that sendfile on MacOS X is broken. Could it be that this problem still exists?
https://blog.phusion.nl/2015/06/04/the-brokenness-of-the-sendfile-system-call/
The (high) transfer rate that you are quoting is likely close to or at the limit of what a SATA device can do anyway. If my guess is right, you will not see a performance gain reflected in the time it takes to run your test - however there will likely be a change in the CPU load during the test. Given that you have a relatively powerful machine, your CPU and memory are fast enough. Any method (zero-copy or not) will work at the same speed - which is the speed of your disk. However, zero-copy will cause a lot less CPU load and will not grab unnecessary bandwidth from your memory, either. Therefore, you should test different methods and see which one ends up using the least amount of CPU and choose that method for your application.
I have a Java service that currently runs with a 14GB heap. I am keen to try out the -XX:+UseLargePages option to see how this might affect the performance of the system. I have configured the OS as described by Oracle using appropriate shared memory and page values (these can also be calculated with an online tool).
Once the OS is configured, I can see that it allocates the expected amount of memory as huge-pages. However, starting the VM with the -XX:+UseLargePages option set always results in one of the following errors:
When -Xms / -Xmx is almost equal to the huge page allocation:
Failed to reserve shared memory (errno = 28). // 'No space left on device'
When -Xms / -Xmx is less than the huge page allocation:
Failed to reserve shared memory (errno = 12). // 'Out of memory'
I did try introducing some leeway - so on a 32GB system I allocated 24GB of shared memory and hugepages to use with a JVM configured with a 20GB heap, of which only 14GB is currently utilized. I also verified that the user executing the JVM did have group rights consistent with /proc/sys/vm/hugetlb_shm_group.
Can anyone give me some pointers on where I might be going wrong and what I could try next?
Allocations/utilization:
-Xms / -Xmx - 20GB
Utilized heap - 14GB
/proc/sys/kernel/shmmax - 25769803776 (24GB)
/proc/sys/vm/nr_hugepages - 12288
Environment:
System memory - 32GB
System page size - 2048KB
debian 2.6.26-2-amd64
Sun JVM 1.6.0_20-b02
Solution
Thanks to #jfgagne for providing an answer that lead to a solution. In addition to the /proc/sys/kernel/shmall setting (specified as 4KB pages), I had to add entries to /etc/security/limits.conf as described on Thomas' blog. However, as my application is started using jsvc I also had to duplicate the settings for the root user (note that the limits are specified in KB):
root soft memlock 25165824
root hard memlock 25165824
pellegrino soft memlock 25165824
pellegrino hard memlock 25165824
It's also worth mentioning that settings could be tested quickly by starting the JVM with the -version argument:
java -XX:+UseLargePages -Xmx20g -version
When you use huge pages with Java, there is not only the heap using huge pages, but there is also the PermGen: do not forget to allocate space for it. It seems this is why you have a different errno message when you set Xmx near the amount of huge pages.
There is also the shmall kernel parameter that needs to be set which you did not mention, maybe it is what is blocking you. In your case, you should set it to 6291456.
The last thing to say: when using huge pages, the Xms parameter is not used anymore: Java reserves all Xmx in shared memory using huge pages.
I'm currently using sun's java 1.6 on a SL4 cluster.
For some reason, the 1.6 JVM is starting up with an impossibly large heap, and cannot start:
java -version
Error occurred during initialization of VM
Could not reserve enough space for object heap
Could not create the Java virtual machine.
If I start it with e.g. -Xmx1800M, then it works OK. So, I'm wondering where the default heap size is set, and more importantly how to change it?
The machine has 8GB of physical memory, and I believe that sun's server JVM is supposed to start with a default of half the memory up to 512M, but this is clearly not the case, as it's trying to allocate over 1800M.
EDIT: I realise that it's possible to use _JAVA_OPTIONS, but this feels a bit clunky; I was expecting a properties file somewhere, but so far I've been unable to find it.
There is no properties file for this. According to Garbage Collector Ergonomics:
initial heap size:
Larger of 1/64th of the machine's
physical memory on the machine or some
reasonable minimum. Before J2SE 5.0,
the default initial heap size was a
reasonable minimum, which varies by
platform. You can override this
default using the -Xms command-line
option.
maximum heap size:
Smaller of 1/4th of the physical
memory or 1GB. Before J2SE 5.0, the
default maximum heap size was 64MB.
You can override this default using
the -Xmx command-line option.
Note: The boundaries and fractions given for the heap size are correct
for J2SE 5.0. They are likely to be
different in subsequent releases as
computers get more powerful.
Given you have 8GB of RAM, default maximum heap size should be 1GB assuming you're using Java 6.
There's no standard properties file. The (Sun) JVM has the default values hardcoded in it.