why mongodb on 32-bit machine has limitation of datasize to 2GB , not 4GB? - mongodb

as here mention, mongodb has limitation of datasize to 2GB in 32-bit machine with one single mongod instance. But I wonder 32-bit machine has 4GB addressable space in theory, and mongod can use this 4GB instead of 2GB for virtual memory usage. So why the answer is 2GB, not 4GB?

4Gb of addressable space is not the same as the memory space available for memory-mapped files opened by user applications. Some of the addressable space is reserved for the O/S kernel and memory-mapped devices such as video cards.
For example, 32-bit Windows limits user mode (and thus memory-mapped files) to ~2Gb RAM and total system RAM to ~3.5Gb.
For more reading, see:
Coding Horror: Dude, Where's My 4 Gigabytes of RAM?
MSDN: Managing Memory-Mapped Files
MSDN: Memory-Mapped Files
The majority of modern desktop and server environments starting moving to 64-bit almost a decade ago (see 64-bit operating system timeline on Wikipedia) so this isn't a limit that practically affects deployment.
You would only want to use 32-bit MongoDB in a development environment with limited data.

32-bit MongoDB processes are limited to about 2 gb of data. This has come as a surprise to a lot of people who are used to not having to worry about that. The reason for this is that the MongoDB storage engine uses memory-mapped files for performance.
By not supporting more than 2gb on 32-bit, we’ve been able to keep our code much simpler and cleaner. This greatly reduces the number of bugs, and reduces the time that we need to release a 1.0 product.
http://blog.mongodb.org/post/137788967/32-bit-limitations

Related

Jenkins and PostgreSQL is consuming a lot of memory

We have a Data ware house server running on Debian linux ,We are using PostgreSQL , Jenkins and Python.
It's been few day the memory of the CPU is consuming a lot by jenkins and Postgres.tried to find and check all the ways from google but the issue is still there.
Anyone can give me a lead on how to reduce this memory consumption,It will be very helpful.
below is the output from free -m
total used free shared buff/cache available
Mem: 63805 9152 429 16780 54223 37166
Swap: 0 0 0
below is the postgresql.conf file
Below is the System configurations,
Results from htop
Please don't post text as images. It is hard to read and process.
I don't see your problem.
Your machine has 64 GB RAM, 16 GB are used for PostgreSQL shared memory like you configured, 9 GB are private memory used by processes, and 37 GB are free (the available entry).
Linux uses available memory for the file system cache, which boosts PostgreSQL performance. The low value for free just means that the cache is in use.
For Jenkins, run it with these JAVA Options
JAVA_OPTS=-Xms200m -Xmx300m -XX:PermSize=68m -XX:MaxPermSize=100m
For postgres, start it with option
-c shared_buffers=256MB
These values are the one I use on a small homelab of 8GB memory, you might want to increase these to match your hardware

postgresql ram setting for 16gb macbook

I'm in the development stage of an application and happened that I have to use Postgresql. In the README file are the following instructions...
On a MacBook Pro with 2GB of RAM, the author's sysctl.conf contains:
kern.sysv.shmmax=1610612736
kern.sysv.shmall=393216
kern.sysv.shmmin=1
kern.sysv.shmmni=32
kern.sysv.shmseg=8
kern.maxprocperuid=512
kern.maxproc=2048
Note that (kern.sysv.shmall * 4096) should be greater than or equal to
kern.sysv.shmmax. kern.sysv.shmmax must also be a multiple of 4096.
I'm guessing that for development I wouldn't have problem leaving the default setting for my Mac, however, there are occasions where I'm running some python script to do data science and I would like to take advantage all the resources available (RAM). What would be the correct configuration for 16GB of RAM.

Reserving RAM for OS on a CentOS server running MongoDB

Given that a mongod process will consume quite a bit of the available RAM, is there a method to 'protect' a certain amount of RAM for the CentOS OS's use?
Or is this really even necessary from the OS's perspective...I assume like most operating systems, CentOS will take what it needs regardless.
I understand that if you are seeing this in practice, it's time to scale out/up...this is a purely theoretical question at this point as I am learning CentOS.
MongoDB doesn't manage memory. It delegates the responsibility to OS. It's beautifully explained in the below link.
MongoDB Memory Management

Setting up the optimal number of processors/cores per processor virtual machine (VMware)

I was looking for an answear but didn't find one.
I'm trying to create a new VM to develop a web application. What would be the optimal processor settings?
I have i7 (6th gen) with hyperthreading.
Host OS: Windows 10. Guest OS: CentOS.
Off topic: RAM that should I give to VM should be 50% of my memory? Would it be ok? (I have 16GB RAM)
Thanks!
This is referred to as 'right-sizing' a vm, and it is dependent on the application workload that will run inside it. Ideally, you want to provide the VM with the minimum amount of resources the app requires to run correctly. "Correctly" is subjective based upon your expectations.
Inside your VM (CentOS) you can run top to see how much memory and cpu % is being used. You can also install htop which you may find friendlier than top.
RAM
If you see a low % of RAM being used, you can probably reduce what you're giving the VM. If you are seeing any swap memory used (paging to disk), you may want to increase the RAM. Start with 2GB and see how the app behaves.
CPU
You'll may want to start with no more than 2vCPUs, checkout top to see how utilized the application is under load, and then make an assessment for more/less vCPUs.
The way a hosted hypervisor (VMware Workstation) handles guest CPU usage is through a CPU scheduler. When you give a vm x number of vCPUs, the VM will need to wait till that many cores are free on the CPU to do 'work'. The more vCPUs you give it, the more difficult (slower) it will be to schedule. It's more complicated than this, but I'm trying to keep it high level. CPU scheduling deep dive.

mongodb flushing mmap takes around 20 secs with no updates being required

Hi One of our customers is running mongodb V2.2.3 on a 64 bit windows server 2008 R2 Enterprise.
We're currently seeing mmap flush times of over 20 seconds every minute.
What is confusing me is that it isn't doing any writes to the disk. (Disk write bytes is next to 0)
Our programme which access the data has been temporary turned off.
so all that is connected is a mongo shell.
Mongostat and mongotop aresn't showing anything
The database has 130 million records. There are 356 files for mmap.
Any sugestions on what could be causing this?
Thanks
If your working set is significantly larger than memory, and MongoDB is constantly going to disk for reads (and not just the normal spikes when syncing writes to disk), then you really should be sharding to spread the data across multiple machines/instances.
Given the behaviour you have described and that you have a large number of files for mmap, I suspect the underlying performance issue is SERVER-12401 in the MongoDB Jira issue tracker:
On Windows, Memory Mapped File flushes are synchronous operations. When the OS Virtual Memory Manager is asked to flush a memory mapped file, it makes a synchronous write request to the file cache manager in the OS. This causes large I/O stalls on Windows systems with high Disk IO latency, while on Linux the same writes are asynchronous.
There are a few possible ways to improve the flush performance on Windows, including code changes in both the MongoDB server and the Windows O/S. There is some ongoing work to address these issues, now that the synchronous flushing behaviour on Windows has been confirmed.
If you are using higher latency local storage (for example, spinning disks) you may be able to mitigate the issue by upgrading to SSD or better spec'd drives.
I would suggest upvoting/watching SERVER-12401 and the related Jira issues for updates.
It would also be worth upgrading from MongoDB 2.2 to a newer version as 2.2 is now past end-of-life for updates. There have been two major production release branches since then, including significant improvements in general performance/features as well as Windows support.