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Home built Hadoop analytics cluster: Part 5 Got the mysql database installed and configured on my secondary node.  Installed the driver on the primary node.  Set up a few users and a database.  Tested the connections. Now hopefully all goes well with the install!

Home built Hadoop analytics cluster: Part 4 So yay!  As mentioned for my next goals in my previous post , I finally got the remaining two boxes built out and added into my home network.  I opted to put the Hadoop cluster on it's own subnet with a dedicated unmanaged switch only for the cluster (primary and nodes). I added the agent and metrics to all of the nodes and rebooted the servers. Then I followed the instructions to set up the cluster, naming it "ds730" after the class that I'm currently taking - DS730: Big Data - High Performance Computing. I also made sure I had DNS setup correctly by modifying /etc/systemd/resolved.conf and fixed my name resolution issues. Removed firewall rules. Removed timedatectl by doing: sudo timedatectl set-ntp no Then installed ntp: sudo apt install ntp Now I need to look at installing some database drivers, however I think I'm going to call it a night.  

Home built Hadoop analytics cluster: Part 3 In my previous post I covered Bill of Materials (BOM), hardware assembly, and installing Linux (Ubuntu).  In this post I will cover how I installed Ambari. Installing Ambari Rather than build from source, I opted to use the distribution from Cloudera (formerly HortonWorks). Ambari 2.7.5 requires official support from Cloudera, so I went down to 2.7.3 which doesn't require a support agreement with Cloudera. Install some pre-requisites sudo apt install python-dev sudo apt install gcc Add Cloudera as a distribution sudo wget -O /etc/apt/sources.list.d/ambari.list http://public-repo-1.hortonworks.com/ambari/ubuntu18/2.x/updates/2.7.3.0/ambari.list sudo apt-key adv --recv-keys --keyserver keyserver.ubuntu.com B9733A7A07513CAD sudo apt-get update Verify packages show up apt-cache showpkg ambari-server apt-cache showpkg ambari-agent apt-cache showpkg ambari-metrics-assembly Install and setup the server on primary sudo apt-get install ambari-se...

Home built Hadoop analytics cluster: Part 2 In my previous post , I went through my overall plan that I will be following, along with goals and topics that I will be covering.  In this post, I will cover the initial building out of the cluster. [ Bill of Materials - BOM ] [ Hardware assembly ] [ Installing and configuring Linux ] Bill of Materials - BOM Item Price Link CPU $139.99 Amazon Motherboard $71.99 Amazon Memory (32 GB) $109.99 Amazon Storage (500 GB) $57.99 Amazon Power Supply (600W) $62.99 Amazon Case $68.99 Amazon Total $511.94 *** Total estimated price as of 10/12/2020 Does not include shipping/taxes Obviously, you can swap out components as you see your needs fit.  I did not want to make a high end workstation with GPU, opting to use a CPU that had graphics built in.  I did opt to get 32 GB memory and 500 GB storage - I could have gone down to 16 GB for memory and 250 GB for storage, but I feel that memory and storage is something that ...

Hadoop Reading Material I'm starting to really get into my DS730 - Big Data: High Performance Computing class. I wanted to go beyond the instructors material and picked up some additional reading material. Hoping this will help me be successful in the weeks to come.

Linux Version lsb_release -a I determined I'm running Ubuntu 18.04. Docker I took the time to download Docker for Ubuntu and followed the instructions here: https://docs.docker.com/engine/install/ubuntu/ ROS Download / Setup Based on the fact that I'm running Ubuntu 18.04, I will be using the Melodic version of ROS http://wiki.ros.org/melodic/Installation Managed to get it working under python 2.7.  I really want to make sure however that I'm going to be compatible in the future, so I want to get this working under python 3.x but that will come later.  

 I've been meaning to install my Titan RTX for a while now... Finally got around to it! brianchilders@education:~$ nvidia-smi --query-gpu=name --format=csv,noheader TITAN RTX GeForce RTX 2080 Ti Will be putting the card through some TensorFlow exercises in the near future.

I managed to get Oracle VirtualBox installed successfully and the Debian Linux distribution as well.  I had to do some additional work, like install pip, sudo, git and update my user id, but the installation was relatively smooth. Based on what I've read, it seems like the python libraries that data scientists use tend to work with python 2.7 - so while inclination might say go with the latest and greatest - do stick with python 2.7 - it may change in the future, but for now this seems like the version to go with. Next up - going to start organizing my projects and start using git.