Anyone know how much disk space and ram a standard ubuntu install on mongo needs? trying to map out my VPS needs ...
There are no minimum requirements as such, but I wouldn't recomend running Mongo on the same box as your webserver.
MongoDB automatically uses all free memory on the machine as its cache
(http://docs.mongodb.org/manual/faq/fundamentals/#does-mongodb-require-a-lot-of-ram)
This, along with the reasons mentioned in this answer (albeit for RDBMS) makes running mongodb on a separate box (even a small one) a much better idea.
Related
I did an experiment by running a python app that is writing 2000 records into mongoDB.
The details of my setup of the experiment as follows:
Test 1: Local PC - Python App running on Local PC with mongoDB on Local PC (baseline)
Test 2: Docker - Python App on Linux Container with mongoDB on Linux Container with persist volume
Test 3: Docker - Python App on Linux Container with mongoDB on Linux Container without persist volume
I’ve generated the result in chart - on average writing data on local PC is about 30 secs. Where else on Docker, it takes about 80plus secs. Hence it seems like writing on Docker is almost 3 times slower than writing on local PC itself.
Should I want to improve the write speed or performance of the mongoDB in docker container, what is the recommended practice? Or should I put the mongoDB as a external volume without docker?
Thank you!
graph
Your system is not consistent in many ways - dynamic storage and CPU performance, other processes, dynamic system settings etc. There are a LOT of underlying things under storage only.
60 sec tests are not enough for anything
Simple operations are not good enough for baseline comparisons
There is ZERO performance impact with storage and CPU in case of containers, there is an impact in networking, but i assume, this is not applicable here
Databases and database management systems must be optimized in special ways, there is no "install and run" approach. We, sysadmins/db admins usually need days to have it running smoothly. Also, performance changes over time.
After couple of weeks of testing and troubleshooting. I finally got the answer and I shall share my findings with the rest of the DevOps or anyone who facing the same issue as me
Correct this statement if needed, Docker Container was started off with Linux, Microsoft join the container bandwagon late and in order to for the container works (with Linux), the DevOps team need to install Linux WSL2 in Windows. And that cost extra overheads which resultant in the process speed.
So to improve the performance speed with containers, the setup should be in Linux OS instead of Windows OS. (and yes the speed reduce drastically)
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
How can i run mongo 2.6 and mongo 3.0 at the same time on my linux system ?
I need this because i have 2 projects one is working on mongo 2.6 and one is working on mongo 3.0
Any help is appreciated !!
If you really wan to do this, and I recommend you DO NOT, then the best way is to use a container tech, docker can work quite well or LXC or one of the others.
However, do note that there is a high chance that if your sever is in the "cloud" it is already vitualised as it is as such you will constantly be losing power and resources due to sub virtualising everything over and over.
DO NOT put them on the same host without some kind of separation there will be a high chance of resource contention and conflict that tools like ulimit just cannot solve (well, technically it could but it will be a hairball).
I have an account with MongoLab for MongoDB and the constant calls to this remote server from my app slow it down quite a lot. When I run the app locally on my computer with a local version of Mongod and MongoDB it's far, far faster, as would be expected.
When I deploy my app (running on Node/Express) it will be run from a VPS on CentOS. I have plenty of storage space available on my VPS, are there any major downsides to running MongoDB locally rather than remotely on Mongolab?
Specs of the VPS:
1024MB RAM
1024MB VSwap
4 CPU Cores # 3.3GHz+
60GB SSD space
1Gbps Port
3000GB Bandwidth
Nothing apart from the obvious:
You will have to worry about storage yourself. MongoDB does tend to take a lot of disk space. upgrading storage will probably be harder to manage than letting Mongolab take care of it.
You will have to worry about making sure the Mongo server doesn't crash and it's running fine.
You will have scaling issues in the future once the load on your application and your database increases.
Using a "database-as-a-service" like Mongolab frees you from worrying about a lot of hardware/OS/system level requirements and configuration. Memory optimization? Which file system? Connection limits? Visualization and IO ops issues? (thanks to Nikolay for pointing that one out)
If your VPS provider doesn't account for local traffic in your bandwidth, then you can set up another VPS for MongoDB. That way, the server will be closer so the requests will be faster, and also, it will have the benefits of being an independent server. It still won't be fully managed like MongoLab though.
[ Edit: As Chris pointed out, MongoLab also helps you with your database schema design and bundles MongoDB support with their plans, so that's also nice. ]
Also, this is a good question, but probably not appropriate for StackOverflow. dba.stackexchange.com and serverfault.com are good places for this question.
In relational databases I would just pop in W3Schools tutorial, install mysql in my machine and start practicing! How can I learn non relational databases in a similar way? In most tutorials I read that these databases work with multiple nodes and data centers.
Does this mean that I will be unable to learn and practice, say Cassandra, using my own single pc?
You do it just like you do it with mySQL: You set up a database on your local machine and start experimenting.
Most database systems which focus on sharding and clustering also work as a stand-alone instance. But when you want to test these features specifically, you can often run multiple instances on the same machine. When you also want to try how they behave when they run on different machines, you can use a virtualization software like VMWare or VirtualBox to set up a bunch of virtual machines and build your virtual datacenter on your desktop.
(I would recommend VMWare for business use and VirtualBox for home use)
I'm a big fan of MongoDB. It's the NoSQL equivalent of MySQL.
Go to the Try It Out link on their home page and you can actually use it in a live session on their website - no download, no configuration, no hassle! Just use it and learn the basics.
Here's the quick start for Cassandra. http://wiki.apache.org/cassandra/GettingStarted
I don't see any reason you couldnt run that from local host. I think the point is that you Can scale these nosql solutions. Might want to check out mongodb or couchdb as well. Easy set up and both are great nosql solutions in my experience.
I would strongly suggest using something like Amazon EC2 for testing NoSQL solutions. You can definitely install a technology like MongoDB locally and create a replica set, but you should definitely put these on different physical machines if you can.
I have installed things like AppFabric, Couchbase and Mongo locally and created clusters and they always work really well locally. It's very easy because the networking part of it always goes smoothly.
Once you introduce two physical machines and a stronger network partition things get difficult.
You can create instances on EC2 for free last I checked if you use their Micro instances. You'll learn a lot.