About

It aims to provide a unified, high-throughput, low-latency platform for handling real-time data feeds. Kafka provides reliable, millisecond responses to support both customer-facing applications and connecting downstream systems with real-time data.

Miri Infotech is launching a product which will configure and publish Apache Kafka, to produce free implementations of distributed or otherwise scalable and high availability which is embedded pre-configured tool with Ubuntu and ready-to-launch AMI on Amazon EC2 that contains Hadoop, Hbase and Apache Kafka.

Before going into deep, one must learn that whatever we are using, what good it stands for?

And to understand this, we have two applications that are as follows:

Building real-time streaming data pipelines that reliably get data between systems or applications
Building real-time streaming applications that transform or react to the streams of data

It is one of the most popular tool among the developers around the world as it is easy to pick up and such a platform with 4APIs namely Producer, Consumer, Streams, and Connect.

The Producer API allows an application to publish a stream of records to one or more Kafka topics.
The Consumer API allows an application to subscribe to one or more topics and process the stream of records produced to them.
The Streams API allows an application to act as a stream processor, consuming an input stream from one or more topics and producing an output stream to one or more output topics, effectively transforming the input streams to output streams.
The Connector API allows building and running reusable producers or consumers that connect Kafka topics to existing applications or data systems. For example, a connector to a relational database might capture every change to a table.

Without having the basic knowledge, one cannot deeply understand its nature and how it works. For that we should understand a few basic concepts about Apache Kafka:

Kafka run as a cluster on one or more servers.
The Kafka cluster stores streams of records in categories called topics.
Each record consists of a key, a value, and a timestamp.

Topics and Logs

Let’s first dive into the core abstraction Kafka provides for a stream of records—The topic.
A topic is a category or feed name to which records are published. Topics in Kafka are always multi-subscriber; that is, a topic can have zero, one, or many consumers that subscribe to the data written to it.
Kafka stores messages which come from arbitrarily many processes called "producers". The data can thereby be partitioned in different "partitions" within different "topics". Within a partition the messages are indexed and stored together with a timestamp.
Other processes called "consumers" can query messages from partitions. Kafka runs on a cluster of one or more servers and the partitions can be distributed across cluster nodes.
Apache Kafka efficiently processes the real-time and streaming data when implemented along with Apache Storm, Apache HBase and Apache Spark. Deployed as a cluster on multiple servers, Kafka handles its entire publish and subscribe messaging system with the help of four APIs, namely, producer API, consumer API, streams API and connector API. Its ability to deliver massive streams of message in a fault-tolerant fashion has made it replace some of the conventional messaging systems like JMS, AMQP, etc.

Usage and 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 you have to follow the following steps:

After then follow the following commands

$ apt-get update

$ apt-get upgrade

Step 6: Use following Linux command to Start Kafka and Zookeeper

Step 6.1: $ sudo su

To change root user

Step 6.2: $ 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

Steps 6.3: To stop Kafka if already running

>> sudo /opt/Kafka/kafka_2.11-0.10.0.1/bin/kafka-server-stop.sh

Steps 6.4: How to start Kafka

>> sudo /opt/Kafka/kafka_2.11-0.10.0.1/bin/kafka-server-start.sh /opt/Kafka/kafka_2.11-0.10.0.1/config/server.properties

Kafka has started and its screen would look like this shown below:

Step 6.5: Testing Kafka Server

Open new Terminal:

1. Right click in current terminal

2. Select Duplicate Session

Enter ‘ubuntu’

>> sudo /opt/Kafka/kafka_2.11-0.10.0.1/bin/kafka-topics.sh --create --zookeeper localhost:2181 --replication-factor 1 --partitions 1 --topic <Your Test Name>

(Where <Your Test Name> should be unique name)

Example: >> sudo /opt/Kafka/kafka_2.11-0.10.0.1/bin/kafka-topics.sh --create --zookeeper localhost:2181 --replication-factor 1 --partitions 1 --topic miritech

Step 6.6: Now, ask Zookeeper to list available topics on Apache Kafka by running the following command:

>> sudo /opt/Kafka/kafka_2.11-0.10.0.1/bin/kafka-topics.sh --list --zookeeper localhost:2181

Step 6.7: Now, publish a sample messages to Apache Kafka topic called miritech by using the following producer command:

>> sudo /opt/Kafka/kafka_2.11-0.10.0.1/bin/kafka-console-producer.sh --broker-list localhost:9092 --topic miritech

Open new Terminal again:

3. Right click in current terminal

4 Select Duplicate Session

Enter ‘ubuntu’

>> sudo su

Step 6.7: Now, use consumer command to check for messages on Apache Kafka Topic called testing by running the following command:

>> sudo /opt/Kafka/kafka_2.11-0.10.0.1/bin/kafka-console-consumer.sh --zookeeper localhost:2181 --topic miritech --from-beginning

Step 7: If you need to work with Hadoop then please follow below steps:

Step 7.1: $ ssh-keygen -t rsa -P ""

This command is used to generate the ssh key.

Step 7.2: $ 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 7.3: ssh localhost

Step 7.4: hdfs namenode –format

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

Step 7.5: start-all.sh

Step 7.6: 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 8: Start Hbase

$ cd /usr/local/hbase/bin

$ start-hbase.sh

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: http://www.miritech.com/ContactUs.aspx

Contact Numbers:

(510) 298-5936
(510) 870-8668

Contact E-mail:

support@miritech.com

Other Useful Links:

Blog: http://support.miritech.com/blog/apache-kafka-a-distributed-streaming-platform-miri-infotech/

Product Demo: https://youtu.be/V5k_uCS2xWQ

Submit Your Request

Name:*

Email Address:*

Phone Number:

Company/Organisation:

Country:

Message:

Submit

You can subscribe Kafka to an AWS Marketplace product and launch an instance from the Mahout 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.

1What is Hadoop?

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.
2Where does Hadoop find applicability in business?

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.
3What is big data security analytics?

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.”
4Is there an easy way to migrate data from Hadoop into a relational database?

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.
5Are Intelligent Assistants the only application of AI for customer care, or are there other ways that AI technologies can impact the contact center?

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.
6What are the popular machine learning algorithms in use today?
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

Kafka	apache	linux	hadoop
Python

Kafka

About

Submit Your Request

1What is Hadoop?

2Where does Hadoop find applicability in business?

3What is big data security analytics?

4Is there an easy way to migrate data from Hadoop into a relational database?

5Are Intelligent Assistants the only application of AI for customer care, or are there other ways that AI technologies can impact the contact center?

6What are the popular machine learning algorithms in use today?

Highlights

Application Installed