JVM memory tuning for eXist - memory-management

Suppose you had a server with 24G RAM at your disposal, how much memory would you allocate to (Tomcat to run) eXist?
I'm setting up our new webserver, with an Intel Xeon E5649 (2.53GHz) processor, running Ubuntu 12.04 64-bit. eXist is running as a webapp inside Tomcat, and the db is only used for querying 'stable' collections --that is, no updates are being executed to the resources inside eXist.
I've been experimenting with different heap sizes (via -Xms and -Xmx settings when starting the Tomcat process), and so far haven't noticed much difference in response time for queries against eXist. In other words, it doesn't seem to matter much whether the JVM is allocated 4G or 16G. I have also upped the #cachesize and #collectionCache in eXist's WEB-INF/conf.xml file to e.g. 8192M, but this doesn't seem to have much effect. I suppose these settings /do/ have an influence when eXist is running inside Tomcat?
I know each situation is different (and I know there's a Tomcat server involved), but are there some rules of thumb for eXist performance w.r.t. the memory it is allocated? I'd like to get at a sensible memory configuration for a setup with a larger amount of RAM available.

This question was asked and answered on the exist-open mailing list. The answer from wolfgang#exist-db.org was:
Giving more memory to eXist will not necessarily improve response times. "Bad"
queries may consume lots of RAM, but the better your queries are optimized, the
less RAM they need: most of the heavy processing will be done using index
lookups and the optimizer will try to reduce the size of the node sets to be
passed around. Caching memory thus has to be large enough to hold the most
relevant index pages. If this is already the case, increasing the caching space
will not improve performance anymore. On the other hand, a too small cacheSize
of collectionCache will result in a recognizable bottleneck. For example, a
batch upload of resources or creating a backup can take several hours (instead
of e.g. minutes) if #collectionCache is too small.
If most of your queries are optimized to use indexes, 8gb RAM for eXist does
usually give you enough room to handle the occasional high load. Ideally you
could run some load tests to see what the maximum memory use actually is. For
#cacheSize, I rarely have to go beyond 512m. The setting for #collectionCache
depends on the number of collections and documents in the database. If you have
tens or hundreds of thousands of collections, you may have to increase it up to
768m or more. As I said above, you will recognize a sudden breakdown in
performance during uploads or backups if the collectionCache becomes too small.
So to summarize, a reasonable setting for me would be: -Xmx8192m,
#cacheSize="512m", #collectionCache="768m". If you can afford giving 16G main
memory it certainly won’t hurt. Also, if you are using the lucene index or the
new range index, you should consider increasing the #buffer setting in the
corresponding index module configurations in conf.xml as well:
<module id="lucene-index" buffer="256" class="org.exist.indexing.lucene.LuceneIndex" />
<module id="range-index" buffer="256" class="org.exist.indexing.range.RangeIndex"/>

Related

Spring Data JPA Meta JpaMetamodelMappingContext Memory Consumption

My Spring Data JPA/Hibernate Application consumes over 2GB of memory at start without a single user hitting it. I am using Hazelcast as the second level cache but I had the same issue when I used ehCache as well so that is probably not the cause of the issue.
I ran a profile with a Heap Dump in Visual VM and I see where the bulk of the memory is being consumed by JpaMetamodelMappingContext and secondary a ton of Map objects. I just need help in deciphering what I am seeing and if this is actually a problem. I do have a hundred classes in the model so this may be normal but I have no point of reference. It just seems a bit excessive.
Once I get a load of 100 concurrent users, my memory consumption increases to 6-7 GB. That is quite normal for the amount of data I push around and cache, but I feel like if I could reduce the initial memory, I'd have a lot more room for growth.
I don't think you have a problem here.
Instead, I think you are misinterpreting the data you are looking at.
Note that the heap space diagram displays two numbers: Heap size and Used heap
Heap size (orange) is the amount of memory available to the JVM for the heap.
This means it is the amount that the JVM requested at some point from the OS.
Used heap is the part of the Heap size that is actually used.
Ignoring the startup phase, it grows linear and then drops repeatedly over time.
This is typical behavior of an idling application.
Some part of the application generates a moderate amount of garbage (rising part of the curve) which from time to time gets collected.
The low points of that curve are the amount of memory you are actually really using.
It seems to be about 250MB which doesn't sound very much to me, especially when you say that the total consumption of 6-7GB when actually working sounds reasonable to you.
Some other observations:
Both CPU load and heap grows fast/fluctuates a lot at start time.
This is to be expected because the analysis of repositories and entities happen at that time.
JpaMetamodelMappingContext s retained size is about 23MB.
Again, a good chunk of memory, but not that huge.
This includes the stuff it references, which is almost exclusively metadata from the JPA implementation as you can easily see when you take a look at its source.

neo4j getting slow & stuck on amazon ec2

I have a neo4j running on an ec2 instance (large, ubuntu) and I'm running some scripts on it that do lots of writings.
I noticed that after a while that those scripts run (after they wrote couple of thousand nodes) the server starting to run very slow, sometimes to the point it get absolutely stuck. another weird part - resetting the instance from this situation usually ends up in the server taking much longer than usual to init.
first I suspected that neo4j uses up all the RAM and this is a paging problem, but I've read that neo4j calculates dynamically the heap size and stack size limits. also I checked memory usage with top and it looked like most of the RAM was unused, except for Java process occasionally popping up, taking few GBs and then disappear quickly, which I assumed was neo4j.
anyway here's my question(s): do I need to config neo4j server and/or wrapper, or should I let neo4j calculate it dynamically on its own? and did someone encountered something like I described and have any idea what could cause it?
thanks!
It's been my experience that you definitely need to tweak the memory settings to your needs. The neo4j manual has a whole section on it:
http://neo4j.com/docs/stable/configuration.html
I've not really heard of neo4j automatically adjusting to your server's memory capabilities, though just last night I did run across what seemed like a new configuration variable in conf/neo4j.properties:
# The amount of memory to use for mapping the store files, either in bytes or
# as a percentage of available memory. This will be clipped at the amount of
# free memory observed when the database starts, and automatically be rounded
# down to the nearest whole page. For example, if "500MB" is configured, but
# only 450MB of memory is free when the database starts, then the database will
# map at most 450MB. If "50%" is configured, and the system has a capacity of
# 4GB, then at most 2GB of memory will be mapped, unless the database observes
# that less than 2GB of memory is free when it starts.
#mapped_memory_total_size=50%

How much memory should a caching system use on Windows?

I'm developing a client/server application where the server holds large pieces of data such as big images or video files which are requested by the client and I need to create an in-memory client caching system to hold a few of those large data to speed up the process. Just to be clear, each individual image or video is not that big but the overall size of all of them can be really big.
But I'm faced with the "how much data should I cache" problem and was wondering if there are some kind of golden rules on Windows about what strategy I should adopt. The caching is done on the client, I do not need caching on the server.
Should I stay under x% of global memory usage at all time ? And how much would that be ? What will happen if another program is launched and takes up a lot of memory, should I empty the cache ?
Should I request how much free memory is available prior to caching and use a fixed percentage of that memory for my needs ?
I hope I do not have to go there but should I ask the user how much memory he is willing to allocate to my application ? If so, how can I calculate the default value for that property and for those who will never use that setting ?
Rather than create your own caching algorithms why don't you write the data to a file with the FILE_ATTRIBUTE_TEMPORARY attribute and make use of the client machine's own cache.
Although this approach appears to imply that you use a file, if there is memory available in the system then the file will never leave the cache and will remain in memory the whole time.
Some advantages:
You don't need to write any code.
The system cache takes account of all the other processes running. It would not be practical for you to take that on yourself.
On 64 bit Windows the system can use all the memory available to it for the cache. In a 32 bit Delphi process you are limited to the 32 bit address space.
Even if your cache is full and your files to get flushed to disk, local disk access is much faster than querying the database and then transmitting the files over the network.
It depends on what other software runs on the server. I would make it possible to configure it manually at first. Develop a system that can use a specific amount of memory. If you can, build it so that you can change that value while it is running.
If you got those possibilities, you can try some tweaking to see what works best. I don't know any golden rules, but I'd figure you should be able to set a percentage of total memory or total available memory with a specific minimum amount of memory to be free for the system at all times. If you save a miminum of say 500 MB for the server OS, you can use the rest, or 90% of the rest for your cache. But those numbers depend on the version of the OS and the other applications running on the server.
I think it's best to make the numbers configurable from the outside and create a management tool that lets you set the values manually first. Then, if you found out what works best, you can deduct formulas to calculate those values, and integrate them in your management tool. This tool should not be an integral part of the cache program itself (which will probably be a service without GUI anyway).
Questions:
One image can be requested by multiple clients? Or, one image can be requested by multiple times in a short interval?
How short is the interval?
The speed of the network is really high? Higher than the speed of the hard drive?? If you have a normal network, then the harddrive will be able to read the files from disk and deliver them over network in real time. Especially that Windows is already doing some good caching so the most recent files are already in cache.
The main purpose of the computer that is running the server app is to run the server? Or is just a normal computer used also for other tasks? In other words is it a dedicated server or a normal workstation/desktop?
but should I ask the user how much
memory he is willing to allocate to my
application ?
I would definitively go there!!!
If the user thinks that the server application is not a important application it will probably give it low priority (low cache). Else, it it thinks it is the most important running app, it will allow the app to allocate all RAM it needs in detriment of other less important applications.
Just deliver the application with that setting set by default to a acceptable value (which will be something like x% of the total amount of RAM). I will use like 70% of total RAM if the main purpose of the computer to hold this server application and about 40-50% if its purpose is 'general use' computer.
A server application usually needs resources set aside for its own use by its administrator. I would not care about others application behaviour, I would care about being a "polite" application, thereby it should allow memory cache size and so on to be configurable by the administator, which is the only one who knows how to configure his systems properly (usually...)
Defaults values should anyway take into consideration how much memory is available overall, especially on 32 bit systems with less than 4GB of memory (as long as Delphi delivers only 32 bit apps), to leave something free to the operating systems and avoids too frequent swapping. Asking the user to select it at setup is also advisable.
If the application is the only one running on a server, a value between 40 to 75% of available memory could be ok (depending on how much memory is needed beyond the cache), but again, ask the user because it's almost impossible to know what other applications running may need. You can also have a min cache size and a max cache size, start by allocating the lower value, and then grow it when and if needed, and shrink it if necessary.
On a 32 bit system this is a kind of memory usage that could benefit from using PAE/AWE to access more than 3GB of memory.
Update: you can also perform a monitoring of cache hits/misses and calculate which cache size would fit the user needs best (it could be too small but too large as well), and the advise the user about that.
To be honest, the questions you ask would not be my main concern. I would be more concerned with how effective my cache would be. If your files are really that big, how many can you hold in the cache? And if your client server app has many users, what are the chances that your cache will actually cache something someone else will use?
It might be worth doing an analysis before you burn too much time on the fine details.

Memory mapped files causes low physical memory

I have a 2GB RAM and running a memory intensive application and going to low available physical memory state and system is not responding to user actions, like opening any application or menu invocation etc.
How do I trigger or tell the system to swap the memory to pagefile and free physical memory?
I'm using Windows XP.
If I run the same application on 4GB RAM machine it is not the case, system response is good. After getting choked of available physical memory system automatically swaps to pagefile and free physical memory, not that bad as 2GB system.
To overcome this problem (on 2GB machine) attempted to use memory mapped files for large dataset which are allocated by application. In this case virtual memory of the application(process) is fine but system cache is high and same problem as above that physical memory is less.
Even though memory mapped file is not mapped to process virtual memory system cache is high. why???!!! :(
Any help is appreciated.
Thanks.
If your data access pattern for using the memory mapped file is sequential, you might get slightly better page recycling by specifying the FILE_FLAG_SEQUENTIAL_SCAN flag when opening the underlying file. If your data pattern accesses the mapped file in random order, this won't help.
You should consider decreasing the size of your map view. That's where all the memory is actually consumed and cached. Since it appears that you need to handle files that are larger than available contiguous free physical memory, you can probably do a better job of memory management than the virtual memory page swapper since you know more about how you're using the memory than the virtual memory manager does. If at all possible, try to adjust your design so that you can operate on portions of the large file using a smaller view.
Even if you can't get rid of the need for full random access across the entire range of the underlying file, it might still be beneficial to tear down and recreate the view as needed to move the view to the section of the file that the next operation needs to access. If your data access patterns tend to cluster around parts of the file before moving on, then you won't need to move the view as often. You'll take a hit to tear down and recreate the view object, but since tearing down the view also releases all the cached pages associated with the view, it seems likely you'd see a net gain in performance because the smaller view significantly reduces memory pressure and page swapping system wide. Try setting the size of the view based on a portion of the installed system RAM and move the view around as needed by your file processing. The larger the view, the less you'll need to move it around, but the more RAM it will consume potentially impacting system responsiveness.
As I think you are hinting in your post, the slow response time is probably at least partially due to delays in the system while the OS writes the contents of memory to the pagefile to make room for other processes in physical memory.
The obvious solution (and possibly not practical) is to use less memory in your application. I'll assume that is not an option or at least not a simple option. The alternative is to try to proactively flush data to disk to continually keep available physical memory for other applications to run. You can find the total memory on the machine with GlobalMemoryStatusEx. And GetProcessMemoryInfo will return current information about your own application's memory usage. Since you say you are using a memory mapped file, you may need to account for that in addition. For example, I believe the PageFileUsage information returned from that API will not include information about your own memory mapped file.
If your application is monitoring the usage, you may be able to use FlushViewOfFile to proactively force data to disk from memory. There is also an API (EmptyWorkingSet) that I think attempts to write as many dirty pages to disk as possible, but that seems like it would very likely hurt performance of your own application significantly. Although, it could be useful in a situation where you know your application is going into some kind of idle state.
And, finally, one other API that might be useful is SetProcessWorkingSetSizeEx. You might consider using this API to give a hint on an upper limit for your application's working set size. This might help preserve more memory for other applications.
Edit: This is another obvious statement, but I forgot to mention it earlier. It also may not be practical for you, but it sounds like one of the best things you might do considering that you are running into 32-bit limitations is to build your application as 64-bit and run it on a 64-bit OS (and throw a little bit more memory at the machine).
Well, it sounds like your program needs more than 2GB of working set.
Modern operating systems are designed to use most of the RAM for something at all times, only keeping a fairly small amount free so that it can be immediately handed out to processes that need more. The rest is used to hold memory pages and cached disk blocks that have been used recently; whatever hasn't been used recently is flushed back to disk to replenish the pool of free pages. In short, there isn't supposed to be much free physical memory.
The principle difference between using a normal memory allocation and memory mapped a files is where the data gets stored when it must be paged out of memory. It doesn't necessarily have any effect on when the memory will be paged out, and will have little effect on the time it takes to page it out.
The real problem you are seeing is probably not that you have too little free physical memory, but that the paging rate is too high.
My suggestion would be to attempt to reduce the amount of storage needed by your program, and see if you can increase the locality of reference to reduce the amount of paging needed.

Is it reasonable for modern applications to consume large amounts of memory?

Applications like Microsoft Outlook and the Eclipse IDE consume RAM, as much as 200MB. Is it OK for a modern application to consume that much memory, given that few years back we had only 256MB of RAM? Also, why this is happening? Are we taking the resources for granted?
Is it acceptable when most people have 1 or 2 gigabytes of RAM on their PCS?
Think of this - although your 200mb is small and nothing to worry about given a 2Gb limit, everyone else also has apps that take masses of RAM. Add them together and you find that the 2Gb I have very quickly gets all used up. End result - your app appears slow, resource hungry and takes a long time to startup.
I think people will start to rebel against resource-hungry applications unless they get 'value for ram'. you can see this starting to happen on servers, as virtualised systems gain popularity - people are complaining about resource requirements and corresponding server costs.
As a real-world example, I used to code with VC6 on my old 512Mb 1.7GHz machine, and things were fine - I could open 4 or 5 copies along with Outlook, Word and a web browser and my machine was responsive.
Today I have a dual-processor 2.8Ghz server box with 3Gb RAM, but I cannot realistically run more than 2 copies of Visual Studio 2008, they both take ages to start up (as all that RAM still has to be copied in and set up, along with all the other startup costs we now have), and even Word take ages to load a document.
So if you can reduce memory usage you should. Don't think that you can just use whatever bloated framework/library/practice you want with impunity.
http://en.wikipedia.org/wiki/Moore%27s_law
also:
http://en.wikipedia.org/wiki/Wirth%27s_law
There's a couple of things you need to think about.
1/ Do you have 256M now? I wouldn't think so - my smallest memory machine is 2G so a 200M application is not much of a problem.
2a/ That 200M you talk about might not be "real" memory. It may just be address space in which case it might not all be in physical memory at once. Some bits may only be pulled in to physical memory when you choose to do esoteric things.
2b/ It may also be shared between other processes (such as a DLL). This means it could be only held in physical memory as one copy but be present in the address space of many processes. That way, the usage is amortized over those many processes. Both 2a and 2b depend on where your figure of 200M actually came from (which I don't know and, running Linux, I'm unlikel to find out without you telling me :-).
3/ Even if it is physical memory, modern operating systems aren't like the old DOS or Windows 3.1 - they have virtual memory where bits of applications can be paged out (data) or thrown away completely (code, since it can always reload from the executable). Virtual memory gives you the ability to use far more memory than your actual physical memory.
Many modern apps will take advantage of the existance of more memory to cache more. Some like firefox and SQL server have explicit settings for how much memory they will use. In my opinion, it's foolish to not use available memory - what's the point of having 2GB of RAM if your apps all sit around at 10MB leaving 90% of your physical memory unused. Of course, if your app does use caching like this, it better be good at releasing that memory if page file thrashing starts, or allow the user to limit the cache size manually.
You can see the advantage of this by running a decent-sized query against SQL server. The first time you run the query, it may take 10 seconds. But when you run that exact query again, it takes less than a second - why? The query plan was only compiled the first time and cached for use later. The database pages that needed to be read were only loaded from disk the first time - the second time, they were still cached in RAM. If done right, the more memory you use for caching (until you run into paging) the faster you can re-access data. You'll see the same thing in large documents (e.g. in Word and Acrobat) - when you scroll to new areas of a document, things are slow, but once it's been rendered and cached, things speed up. If you don't have enough memory, that cache starts to get overwritten and going to the old parts of the document gets slow again.
If you can make good use of the RAM, it is your responsability to use it.
Yes, it is perfectly normal. Also something big was changed since 256MB were normal... and do not forget that before that 640Kb were supposed to be enough for everybody!
Now most software solutions are build with a garbage collector: C#, Java, Ruby, Python... everybody love them because certainly development can be faster, however there is one glitch.
The same program can be memory leak free with either manual or automatic memory deallocation. However in the second case it is likely for the memory consumption to grow. Why? In the first case memory is deallocated and kept clean immediately after something becomes useless (garbage). However it takes time and computing power to detect that automatically, hence most collectors (except for reference counting) wait for garbage to accumulate in order to make worth the cost of the exploration. The more you wait the more garbage you can sweep with the cost of one blow, but more memory is needed to accumulate that garbage. If you try to force the collector constantly, your program would spend more time exploring memory than working on your problems.
You can be completely sure than as long as programmers get more resources, they will sacrifice them using heavier tools in exchange for more freedom, abstraction and faster development.
A few years ago 256 MB was the norm for a PC, then Outlook consumed about 30 - 35 MB or so of memory, that's around 10% of the available memory, Now PC's have 2 GB or more as a norm, and outlook consumes 200 MB of memory, that's about 10% also.
The 1st conclusion: as more memory is available applications use more of it.
The 2nd conclusion: no matter what time frame you pick there are applications that are true memory hogs (like Outlook) and applications that are very efficient memory wise.
The 3rd conclusion: memory consumption of a app can't go down with time, else 640K would have been enough even today.
It completely depends on the application.

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