I'm using MongoDB on Ubuntu 14.04 and I need to test CPU/Memory usage of different types of queries.
I'm wondering weather there is a script I can write or method I can use. I have tried using iotop however it doesn't to be useful. some guidance will be appreciated
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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'm testing the performance of MongoDB on a single system using YCSB. I'd like to get a sense of the performance using SSDs compared to spinning disks.
I have CentOS, MongoDB, and YCSB installed. I have stumbled around a bit with basic examples, but have yet to see a step by step of starting from this setup to loading to running to reviewing. I keep seeing bits and pieces, but not enough to get me up and running.
If anyone could please provide a command line for these steps, it would be most appreciated!
Thanks
Here's a guide on how to run Yahoo! Cloud System Benchmark (YCSB) using Mongodb.
https://github.com/samanca/YCSB/tree/master/mongodb
https://github.com/brianfrankcooper/YCSB/wiki
Working example using Python and Java to test Mongodb:
https://github.com/richcar58/MongoDBTools/blob/master/RunYcsb/runycsb/fabfile.py
My Mongo database is hosted at MongoLab. I'd like to use ElasticSearch as a full text search engine on top of my DB.
As I understand MongoDB needs to run as a replica-set, but I don't have any control on how the database run. I'm currently using the 500mb free plan.
On the top of that, I'm using the scala playframework.
Was anyone successful with those technologies and services?
Update:
Finally I'm not using MongoDB anymore, and went straight for a ElasticSearch solution.
I found this nice cloud host providing a 500MB free plan http://facetflow.com/
It was very useful for my development.
I didn't find any satisfying Scala library for ES, therefore I'm using Dispatch and make direct http requests to the ES instance.
I hope that someone will find this useful.
Just a quick note ... MongoHQ has oplog support with their MongoDB Elastic Deployments ... those could help you with using Elastic Search and River.
http://blog.mongohq.com/elastic-deployments-now-with-oplog-access/
I haven't looked into this too deeply, but you might want to check out Searchly http://www.searchly.com/features/ . The features mention
Built-in crawler for crawling web pages and databases. (Currently MongoDB)
If you try this out, please let me know how it goes. I will do the same.
Update:
I haven't tried searchly, but I was able to start a MongoDB instance in replica mode on OpenShift.
I have also an Elastic Search server running on the same OpenShift "gear".
Now I need time to try connecting those two together, and then the fun will start :-)
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.
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.