cross-compile for amazon ec2 micro - amazon-ec2

I'm trying to install latest wt on amazon ec2 micro (free tier). it runs out of memory during the compilation.
How can I compile the wt on another system (i have i7 laptop with 8gb of ram)?
I was hoping that I can run cmake with some option and would get a Makefile that I need with all the gcc options but I can't find how to do that. both of my systems are 64bit.

Run a temporary m1.small, c1.medium, or larger EC2 instance, do the compilation there, then terminate the instance.
The systems will match and and it will only cost a dime or two.
Alternatively, you can switch your t1.micro to a larger size temporarily, do the compilation, then switch it back.

Related

Too little RAM in Kaa Server

I want to run a test with KAA, so I was trying to install the sandbox in my laptop but it has only 4GB in RAM, so when I try to set up the Virtual Machine the system won't let me set up over 1,6GB and the VM won't start.
So I was trying to install in other old laptop so I installed Ubuntu 16,04 and I followed all the step by step instructions in Kaaproyect's WEB. I could do it, but when I try to start the server can't do it. I was checking the Log error and say me that the problem is in the Java's Virtual machine, can't start because only have 2GB in RAM. I need to test a Little application so is it possible change this requirement in the Java machine and start the system?
PS: I can't buy more Ram.
I recommend you to use amazon AWS. The basic installation where you can run Kaa is free for one year, and it runs quite well there.

Hadoop installation using Cloudera VMware

Can anyone please let me know the minimum RAM required (of the host machine) for running Cloudera's hadoop on VMware workstation?
I have 6GB of RAM. The documentation says that the RAM required by the VM is 4 GB.
Still, when I run it, the CentOS is loaded and the VM crashes. I have no other active application running at the time.
Are there any other options apart from installing hadoop manually?
You may be running into your localhost running out or memory or some other issue preventing the machine from booting completely. There are a couple of other options if you don’t want to deal with a manual install:
If you have access to a docker environment try the the docker image they provide.
Run it in the cloud with AWS, GCE, Azure, they usually have a small allotment of personal/student credits available.
For AWS, EMR also makes it easy for you to run something repeatedly.
For really short durations, you could try the demo from Bitnami (https://bitnami.com/stack/hadoop) and just run whatever you need to there.

How to install pyspark & spark for learning purpose on a laptop with limited resources?

I have a windows 7 laptop with 6GB RAM . What is the most RAM/resource efficient way to install pyspark & spark on this laptop just for learning purpose. I don't want to work on actual big data but small dataset is ideal since this is just for learning pyspark & spark in general. I would prefer the latest version of Spark.
FYI: I don't have hadoop installed.
Thanks
You've basically got three options:
Build everything from source
Install Virtualbox and use a pre-built VM like Cloudera Quickstart
Install Docker and find a suitable container
Getting everything up and running when you choose to build from source can be a pain. You've got to install the JDK, build hadoop and spark (both of which require you to install additional software to build them), set up a bunch of environment variables and then pray that didn't mess anything up.
VMs are nice, particularly the one from Cloudera, but you'll often be stuck with an older version of Spark and it might be tight with the resources you described.
I'd go with Docker.
Once you've got docker installed, it becomes very easy to try Spark (and lots of other technologies). My favorite containers for playing around use ipython or jupyter notebooks.
Install Docker:
https://docs.docker.com/installation/windows/
Jupyter Notebook Python, Spark, Mesos Stack
https://github.com/jupyter/docker-stacks/tree/master/pyspark-notebook
One thing to keep in mind is that you are going to have to allocate a certain amount of memory for the VM and the remaining memory still has to operate Windows. Windows 7 requires a minimum of 1 GB for a 32-bit OS or 2 GB for a 64-bit OS. So likely you are only going to wind up with around 4 GB of RAM for running the VM, which is not much.
Assuming you are 64-bit, note that Cloudera requires a minimum of 4 GB RAM to run CDH 5, but if you want to run Cloudera Express, you need 8 GB.
Running Docker from Windows will require you to use boot2docker, which keeps the entire VM in memory. It uses minimal memory (like around 27 MB) to run, so you should be fine there. A MUCH better solution than running VirtualBox!
Another option to consider would be to spin up a free machine on something like Amazon Web Services (http://aws.amazon.com) or Google Cloud (http://cloud.google.com). Particularly with the later, you can get a free trial amount of credits, which you could use to spin up a machine with more RAM than you would typically get with AWS.

Better performance from windows virtualboxes on ubuntu or from ubuntu virtualboxes on windows

I am planning to develop an automated test solution with multiple windows machines and multiple ubuntu machines that perform related/interdependent tasks. To start the project, I'd like to have one or two windows machines (virtual) and a few ubuntu machines (virtual) running on a single desktop. It seems likely that I will be pushing a single desktop to the limit here so I am trying to guess if I will have better luck if my host OS is ubuntu or if it is Windows 7. I would be able to use the host OS as one of the machines in my environment. The desktop is some sort of above average Dell, but nothing really impressive.
Does anyone have any insight here? I've worked mostly with VMWare in the past and my host was windows along with my VMs.
Note: VirtualBox is a type-2 hypervisor (it runs on the host OS, not on the hardware like a type-1 hypervisor) and tends to offer weaker performance than, for example, Hyper-V, ESX or XEN (type-1 hypervisors).
Therefore, if performance is a considerable concern, you may squeeze more juice out of Win8 or Windows Server 2012 box running, for example, Hyper-V. Further reading on this here and here (YMMV).
How your environment will run when hosted by a Windows vs. a Linux box is, frankly impossible to tell. I suggest you build your VM's and try dual-booting your machine in Windows and Linux and measuring your scenario. Be sure to have enough RAM in the host to allocate enough working RAM to each VM and enough IO throughput that your host doesn't end up dragging the perf of all VM's down if one VM saturates the machine's IO.
One last note of caution though: Don't completely trust fine-grained perf results measured on VM's - even the best hypervisors cannot truly replicate the perf' characteristics of code running on bare-metal. Treat your measurements as a guideline only.
Measure, then measure again. Measure again just to be sure ... and THEN tweak your config and re-measure, measure, measure ;)
My $0.02:
If its VirtualBox you are using I would go with Ubuntu for certain. I have an AMD 945 Phenom with 16GB of Ram with 12.04LTS 64bit . I can usually have 2 VM's running Windows and / or Ubuntu guests and never consume more than 7 GBs of RAM . If your running them in a testing solution you could expect to probably see 12 maybe 13 GBs of RAM, but the CPU might be your problem. My AMD Phenom runs great, but would be maxed out for sure. I use VMWare at work and on my Laptop and would recommend that if you were running a Windows Host. I also have VMWare on my Ubuntu host, but it just does not run as well as it does on Windows., at least for me.

amazon ec2 small instance 32bit , are we able to scale up without OS upgrade?

The standard instance of EC2 is 1.7GB Memory default 32bit Linux OS for example,
My question is if one day i want to upgrade or "scale-up" to 7.5GB memory server without reinstalling the OS. To better utilise more than 3GB memory, we definitely need a 64 bit server ? But if i would like to start from a small instance, will it create a lot of trouble if were to upgrade it in the future?
You can move an EBS boot instance from a 32-bit m1.small to a 32-bit c1.medium without reinstalling.
Above that you have to start over with a 64-bit AMI.
Update: EC2 now supports 64 bit on all instance sizes. You life will be much easier if you only use 64 bit across the board.
If you need more than 3GB of RAM you need 64bit server. I think there can be some problems in switching from 32bit to 64bit because even compiled binaries by you are different from system arch (in 64b linux uses ELF64 format for binaries). I don\t know what are your needs but i will choose microinstances (they support 64bit) and get 2 of them to make "balanced" architecture.
I think you should consider RackSpace services:
http://www.rackspace.com/cloud/cloud_hosting_products/servers/pricing/
Price/Performance ratio is same but you will get 64bit from the start, so I don't expect so much trouble with upgrade.

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