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Functional Programming Introduction

 Greetings! One of the biggest changes happened to Java is, addition of Functional programming in Java 8. It is great because now we can use imperative, procedural, object-oriented, and functional techniques in Java. Java added functional programming to the language using Lambda expressions, Stream, Optional, default methods in interface, static methods in interface, functional interface. Let's dive into important concepts in functional programming. First of all, What is a Function? f(x) = y That is a function which gives us 'y' for a given 'x'. Let's see an easy one. f(x) = x + 1 This will give us the next value for a given 'x'. So what is the big deal here? Immutable, ie no mutation of data. No sate. No side effects. Always gives the same output for the same input. Important concepts Pure function First class function Higher order function Referential transparency Lazy evalutation C
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Kafka: Introduction to core concepts

Apache Kafka was developed by LinkedIn and donated to Apache. Apache Kafka is a distributed streaming platform that can handle high volume of data. Pull or Push? I initially misunderstood Kafka as a push based messaging system. However Kafka has chosen traditional pull approach. In Kafka, data is pushed to the broker by producers and pulled from the broker by the consumers. IMAGE1 Why Kafka? Kafka is a reliable messaging system which is fast and durable. We can list it's benifits as; Scalable - Kafka's partion model allows data to distributed across multipel servers, making it highly scalable.  Durable - Kafka's data is written to disk making it highly durable agaisnt server failures. Multiple producers - Kafka can handle multpile producers which publish to the same topic. Multiple consumers - Kafka is designed so that multipel consumers can read messages without interfering with each other. High performance - All these features allows high performace distributed messaging

Getting started with Kafka

This is a quick guide to set up Kafka environment for local development and learn Kafka. I use Kafka Udemy course and documentation for this. Setup and configuring Kafka echo system may be a boring task. However with Docker and Landoop (now they are Lenses) it is as easy as running a docker command. Note: You need Docker installed to follow this post. Get landoop docker image When you have setup docker in your environment you can pull landoop docker image. $ docker pull landoop/fast-data-dev Start the Kafka broker I'm going to run the docker container in interactive mode. $ docker container run --rm --name my-kafka-broker -it \ -p 2181:2181 -p 3030:3030 -p 8081:8081 \ -p 8082:8082 -p 8083:8083 -p 9092:9092 \ -e ADV_HOST= \ landoop/fast-data-dev This will bring up all necessary tools to work with Kafka. After about 1 minute you can access landoop's UI console from . If you scroll down, you can see r

Hexagonal Architecture

Invented by Alistair Cockburn, Hexagonal Architecture is one of many ways to design loosely coupled applications. This is also known as Ports and Adapters pattern. As domain is the king and every other layer should work around it, this solves the layer dependency by inverting them. Intent Allow an application to equally be driven by users, programs, automated test or batch scripts, and to be developed and tested in isolation from its eventual run-time devices and databases. (Alistair Cockburn) Principle Hexagonal architecture divided the system into manageable loosely coupled components centering application core domain. As the domain is at the center, all other layers such as web, database are directing at it. This is achieved by ports and adapters (hence the name). Each outer layers is connected through ports by implementing them as adapters. Thus core domain is fully independent of changes. This approach is an alternative to traditional layered architecture. Domain - sit center of t

Domain Driven Design (part 1)

We all have heard of Domain Driven Design and we all (including myself) are struggling to use it. Let's try to understand few things together. Domain Driven Design is first coined by Eric Evans in his book which is a concept to structure projects using the business domain. Domain is the King. While we can arrange our structure in varies ways, there is a common factor in every project, "business domain". No matter, project domain is the reason why the project exists. It is clear that domain is the most valuable thing. In his book, Eric Evans describes how we can build our projects centering the domain. Fair enough, for small projects this may be over engineering. In his book, he mainly focuses on the domain layer in our system. Domain -  Domain is the real world problem we are going to solve in our application. Domain refers to the specific subject that the project is being developed for. The subject area to which the user applies a program is the domain of the software. D

Message Broker

When we are building systems with multiple components, we need a way to communicate between components. One failed attempt will be direct communication between components. In this solution, components are higly depending on each other. A better solution will be to use a centralized middleman. All necessary components register with middleman. Middleman recieve all the requests where it find corresponding service to send it. A broker can: Register, unregister services. Locate services. Recieve and send messages. Error handling. Products There are many broker systems available. These are just few of them. Apache ActiveMQ, Apache Kafka, RabbitMQ, Websphere ESB, JBoss ESB, Amazon MQ Advantages Loose coupling between components. Scalable and maintainable as long as the interface remain the same. Components are reusable. Disadvantages Introduce single point of failure. Degrade performance due to additional routing.

Pipes and Filters Architecture

In Linux, when we want to combine results of varies commands to filer out our desired result we use pipe. We feed output of one program as the input of the next. This is fine example of Pipes and Filters pattern. $ ps aux | grep java Pipes and filters is a very helpful architectural design pattern for stream of data. Also, it is helpfull when there are data transformations through the sequence. Source code for the example application . It consists of number of components called Filters that transform data before handing over to next Filter via connectros called Pipes. Filter - transforms or filters data it receives via the pipe. Pipe - is the connector that passes data from and to filters. Pump - is the data producer. Sink - is the end consumer of the target data. A pipeline consists of a chain of processing elements, arranged so that the output of each element is the input of the next (Wikipedia). Filter can be a small class as well as a big component. Input, output can be decided by