Predictive Analytics Framework R Hadoop

HADOOPHDFSRStudioHbaseR
Launch Now Write a Review

Please feel free to contact us

Go
img

About

MIRI Infotech brings Predictive analytics framework environment in R, Java and Hadoop. Specially optimized R version 3.3.3 (2017-03-06) with Ubuntu 16.04 OS. This includes RStudio Version 0.98.1091 & RServer 1.0.36 and Hadoop 2.7.3 with HDFS, HBase Version 1.3.0.

Miri Infotech is launching a product which will configure and publish Predictive Analytics Framework with R & Java and Hadoop, to a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering) and graphical techniques which is embedded pre-configured tool with Ubuntu 16.04 and ready-to-launch AMI on Amazon EC2 that contains Hadoop, R, RStudio, HDFS, Hbase and Shiny server.

R is a language and environment for statistical computing and graphics. R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering) and graphical techniques, and is highly extensible. The capabilities of R are extended through user-created packages, which allow specialized statistical techniques, graphical devices.

A core set of packages is included with the installation of R, with more than 10,331 additional packages.

Currently, the CRAN package repository features 10331 available packages. To see the list of all available packages from CRAN, Click Link.

RStudio includes other open source software components. The following is a list of these components (full copies of the license agreements used by these components are included below):

  • Qt (LGPL v2.1)
  • QtSingleApplication
  • Ace (LGPL v2.1)
  • Boost
  • RapidXml
  • JSON Spirit
  • Google Web Toolkit
  • Guice
  • GIN
  • AOP Alliance
  • RSA-JS
  • tree.hh
  • Hunspell (MPL)
  • Chromium Hunspell Dictionaries (MPL)
  • pdf.js
  • SyncTeX
  • ZLib
  • Sundown
  • highlight.js
  • MathJax
  • reveal.js
  • node-webkit
  • JSCustomBadge

RStudio Server enables you to provide a browser-based interface (the RStudio IDE) to a version of R running on a remote Linux server. Deploying R and RStudio on a server has a number of benefits, including:

  • The ability to access your R workspace from any computer in any location
  • Easy sharing of code, data, and other files with colleagues
  • Allowing multiple users to share access to the more powerful computer resources (memory, processors, etc.) available on a well-equipped server
  • Centralized installation and configuration of R, R packages, TeX, and other supporting libraries

You can subscribe RHadoop to an AWS Marketplace product and launch an instance from the RHadoop product’s AMI using the Amazon EC2 launch wizard.

To launch an instance from the AWS Marketplace using the launch wizard

  • Open the Amazon EC2 console at https://console.aws.amazon.com/ec2/
  • From the Amazon EC2 dashboard, choose Launch Instance. On the Choose an Amazon Machine Image (AMI) page, choose the AWS Marketplace category on the left. Find a suitable AMI by browsing the categories, or using the search functionality. Choose Select to choose your product.
  • A dialog displays an overview of the product you’ve selected. You can view the pricing information, as well as any other information that the vendor has provided. When you’re ready, choose Continue.
  • On the Choose an Instance Type page, select the hardware configuration and size of the instance to launch. When you’re done, choose Next: Configure Instance Details.
  • On the next pages of the wizard, you can configure your instance, add storage, and add tags. For more information about the different options you can configure, see Launching an Instance. Choose Next until you reach the Configure Security Group page.
  • The wizard creates a new security group according to the vendor’s specifications for the product. The security group may include rules that allow all IP addresses (0.0.0.0/0) access on SSH (port 22) on Linux or RDP (port 3389) on Windows. We recommend that you adjust these rules to allow only a specific address or range of addresses to access your instance over those ports
  • When you are ready, choose Review and Launch.
  • On the Review Instance Launch page, check the details of the AMI from which you’re about to launch the instance, as well as the other configuration details you set up in the wizard. When you’re ready, choose Launch to select or create a key pair, and launch your instance.
  • Depending on the product you’ve subscribed to, the instance may take a few minutes or more to launch. You are first subscribed to the product before your instance can launch. If there are any problems with your credit card details, you will be asked to update your account details. When the launch confirmation page displays.

Usage/Deployment Instruction

Step 1: Open Putty for SSH

Step 2: Open Putty and Type <instance public IP> at “Host Name”

Step 3: Open Connection->SSH->Auth tab from Left Side Area

Step 4: Click on browse button and select ppk file for Instance and then click on Open

Step 5: Type “ubuntu” as user name Password auto taken from PPK file

Step 5.1: if you get any update option from Ubuntu then follow these steps:

Then follow these commands

$ apt-get update

$ apt-get upgrade

Step 6: Use following Linux command to start Hadoop

Step 6.1: $ sudo vi /etc/hosts

Take the Private Ip address from your machine as per the below screenshot and then replace the second line of your command screen with that Private ip address

Step 6.2: $ ssh-keygen -t rsa -P ""

This command is used to generate the ssh key.

Step 6.3: $ cat $HOME/.ssh/id_rsa.pub >> $HOME/.ssh/authorized_keys

This command is used to move the generated ssh key to the desired location

Step 6.4: ssh localhost

Step 6.5: hdfs namenode –format

You have to write “yes” when it prompts you – Are you sure you want to continue?

Step 6.6: start-all.sh

Step 6.7: After the above command executes successfully, you should check the below urls in the browser –

http://<instance-public-ip>:8088

http://<instance-public-ip>:50070

http://<instance-public-ip>:50090

Step 7: Start Hbase

$ cd /usr/local/hbase/bin

$ start-hbase.sh

Step 8: Start R console

$ R

Step 9: Start RStudio Server

$ cd ~

$ sudo gdebi rstudio-server-0.98.1028-amd64.deb

$ sudo rstudio-server start

Step 10: Update user rstudio password

$ sudo passwd rstudio

Step 10.1: Configure r-hadoop

Open rstudio in browser

http://<instance-public-ip>:8787/

Example:

http://54.237.233.225:8787/

Enter rstudio user and its newly generated password

After login screen look like this:

For install r-hadoop packages:

Select à Tools à Install packages à Install from : Package Archive File(.tr.gz)

Select Browse button

Open new file explorer window and select all available packages for r-hadoop service. Available packages are:

rhdfs_1.0.8.tar.gz

rhbase_1.2.1.tar.gz

plyrmr_0.6.0.tar.gz

ravro_1.0.4.tar.gz

rmr2_3.3.1.tar.gz

After that you will enjoy with Predictive Analytics Framework R Hadoop  with your own commands, Environment Ready for use.

All your queries are important to us. Please feel free to connect.

24X7 support provided for all the customers.

We are happy to help you.

Submit your Query: https://miritech.com/contact-us/

Contact Numbers:

Contact E-mail:

Submit Your Request





    Input this code: captcha

    The Apache Hadoop software library allows for the distributed processing of large data sets across clusters of computers using a simple programming model. The software library is designed to scale from single servers to thousands of machines; each server using local computation and storage. Instead of relying on hardware to deliver high-availability, the library itself handles failures at the application layer. As a result, the impact of failures is minimized by delivering a highly-available service on top of a cluster of computers.

    Hadoop, as a scalable system for parallel data processing, is useful for analyzing large data sets. Examples are search algorithms, market risk analysis, data mining on online retail data, and analytics on user behavior data.

    Add the words “information security” (or “cybersecurity” if you like) before the term “data sets” in the definition above. Security and IT operations tools spit out an avalanche of data like logs, events, packets, flow data, asset data, configuration data, and assortment of other things on a daily basis. Security professionals need to be able to access and analyze this data in real-time in order to mitigate risk, detect incidents, and respond to breaches. These tasks have come to the point where they are “difficult to process using on-hand data management tools or traditional (security) data processing applications.”

    The Hadoop JDBC driver can be used to pull data out of Hadoop and then use the DataDirect JDBC Driver to bulk load the data into Oracle, DB2, SQL Server, Sybase, and other relational databases.

    Front-end use of AI technologies to enable Intelligent Assistants for customer care is certainly key, but there are many other applications. One that I think is particularly interesting is the application of AI to directly support — rather than replace — contact center agents. Technologies such as natural language understanding and speech recognition can be used live during a customer service interaction with a human agent to look up relevant information and make suggestions about how to respond. AI technologies also have an important role in analytics. They can be used to provide an overview of activities within a call center, in addition to providing valuable business insights from customer activity.

    There are many machine learning algorithms in use today, but the most popular ones are:

    • Decision Trees
    • Naive Bayes Classification
    • Ordinary Least Squares Regression
    • Logistic Regression
    • Support vector machines
    • Ensemble Methods
    • Clustering Algorithms
    • Principal Component Analysis
    • Singular Value Decomposition
    • Independent Component Analysis

    Highlights

    • icon

      Optimized Computation

    • icon

      Complete optimized R 3.3.3 environment with 10231 CRAN packages. Features include Rstudio, Rstudio Server, Anaconda.

    • icon

      Heightened security features actually adapt to protect you from attack.

    Application Installed

    • icon Predictive Analytics Framework R Hadoop
    • icon apache
    • icon linux
    • icon hadoop